At Microsoft, Windows 11 has been powering the 225,000 devices our employees and vendors use to do their work since it was released in the fall of 2021. Since then, the addition of many new features and the integration of AI have made it even more useful to us.

Like other enterprises, we’re benefitting from how AI is being woven into every part of the technology sector, including with Windows, where we’re using Copilot+ PCs, Microsoft 365 Copilot, and the rest of the broad range of AI-powered tools and features that we’re using across the company to get more out of our longtime, signature operating system today, while also preparing for how it will continue to power everything we do in the future.

According to our 2024 Work Trend Index (WTI) annual report, 79% of US business leaders believe their company needs to adopt AI to remain competitive. Yet, the numbers suggest that those that are just now starting to get ready for AI are already behind. Users say AI is saving them time now (90%), allowing them to focus on their work (85%, be more creative (84%), and enjoy their work more (83%).

The AI era is already here, and organizations must seize every opportunity to catch up and get ready for the future.

At Microsoft Digital, our internal IT organization, we’re harnessing Windows 11 and Copilot+ PCs to give our business and our employees a foundation to build on for future developments in AI. AI interactions are happening at the desktop, in the browser, across apps, and, with Windows 11 and Copilot+ PCs, right in the local operating system.

With Windows 10 end-of-support approaching in October 2025, every organization needs to assess their PC inventory and create a plan to move forward. Outdated PCs put users and businesses at risk, and the security and functionality updates that come with Windows 11 provide the best protection and productivity for Microsoft customers.

Learning from our own deployment of Windows 11

Our own first internal rollout of Windows 11 was the smoothest and quickest operating system upgrade in the history of the company. During the key phase of the rollout, we deployed Microsoft 11 to more than 190,000 devices in five weeks.

Starting small and growing from there is an essential part of the way we deploy any solution or tool, Windows 11 included.

“We followed a ring-based approach, which is pretty typical,” says Markus Gonis, a service engineer and deployment lead with Microsoft Digital. “The initial feature testing happened with a small group of Microsoft Digital users who were close to the feature sets and understood their key implications.”

The testing team subjected Windows 11 to an initial test process to ensure it met our organization’s internal standards, the same standards that we apply to any new software or solution, whether it was developed by Microsoft or by another provider.

Following initial testing, we deployed Windows 11 to a small, specifically selected proof of concept group to ensure that its overall functionality met our expectations and requirements. Pilot-testing followed, and then full implementation. This phased approach ensured that any potential issues were identified and addressed early, and that we could perform the majority of the deployment with few issues.

“We had a minimal number of standard incidents, and no major incidents reported through support channels directly related to the Windows 11 update nor the deployment itself,” Gonis says. “Despite the complexities of hardware eligibility and app compatibility with a new operating system being a typical challenge, we were able to execute the deployment with minimal disruption.”

Moving forward with deploying subsequent versions of Windows 11, we have refined the deployment process to include many more devices, now exceeding 225,000 with the 24H2 update, both by having users update their devices on their own and through pushed deployment.

Improving deployment with Windows Autopatch

The deployment process used several new features, including Windows Autopatch (which now includes Windows Update for Business).

“Windows Autopatch has been a game-changer for us,” says Harshitha Digumarthi, a senior product manager at Microsoft Digital. “It allows us to manage our updates more effectively and to ensure our devices are running the latest and most secure versions of Windows.”

Digumarthi’s team used Windows Autopatch to manage and control Windows 11 updates throughout the deployment. By using device group membership and a few deployment parameters, they had full control over when and how they deployed major updates to the entire organization. This approach allowed for a more streamlined and efficient update process, ensuring our devices received the updates without causing disruptions.

The team also integrated Windows Autopatch into the deployment process to further enhance the efficiency of updates. This feature keeps our devices patched and up to date, reducing the need for manual intervention as it reinforces our security posture and Zero Trust strategy.

Deploying Windows 11 with security and compliance

Feature testing, especially new features included in later builds, is an important part of the ongoing security and compliance practices at Microsoft Digital.

“When a new feature comes out, we need to ensure that we can deploy and govern it securely,” says Yulia Evgrafova, a principal security engineer with Microsoft Digital. Her team helps to ensure new features are ready for enterprise deployment at Microsoft.

Evgrafova points out the extra responsibility and privilege that comes with testing Microsoft products.

“With Windows 11, it’s a Microsoft product, but we’re also using that product as a customer,” Evgrafova says. “We call ourselves Customer Zero.”

Our Customer Zero relationship at Microsoft is a special one.

We in Microsoft Digital usually adopt products like Windows 11 before any other customer. Then, as part of the relationship, we test, use, and offer feedback on the product. It’s an internal feedback mechanism that we use for most of our products, and it leads to better, more complete products that are enterprise tested and enterprise ready.

“Our feature testing is comprehensive,” Evgrafova says. “We start with the basics: what is the scope of this feature and what’s the enterprise readiness of this feature for the rollout? Our goal is to understand not only the immediate risks that a feature might pose, but also the potential risks of that feature as it matures.”

However, deploying Windows 11 wasn’t simply testing and upgrading the operating system on existing hardware.

Windows 11 has specific hardware requirements, which meant not every device at Microsoft would be part of the deployment. Most of our devices were eligible, but communicating hardware requirements was an early step.

“Communicating with our employees about the requirements and how we would handle new devices was important,” Gonis says. “Since Windows 10 and Windows 11 can be managed side-by-side with no additional overhead, we could co-manage both upgraded and non-upgraded devices until all the older Windows 10 devices were replaced.”

Replacing Windows 10 devices with new hardware created an opportunity for us to examine our hardware refresh policy, assess the hardware options, and finally make Copilot+ PCs our device refresh of choice.

Turning to Copilot+ PCs

Integrating Copilot+ PCs into the mix was a very natural next step for us.

“Copilot+ PCs were the obvious choice to replace unsupported Windows 10 hardware,” says Pandurang Savagur, a senior product manager with Microsoft Digital. “Copilot+ PCs bring an entirely new level of hardware support and acceleration of Windows 11 capabilities, in AI and beyond.”

Copilot+ PCs offer a new hardware feature set that goes beyond the traditional PC. Those features are headlined by the neural processing unit (NPU) present in every Copilot+ PC.

Neural Processing Units (NPUs) have become a crucial component in modern computing, especially with the advent of AI-driven applications. Initially, devices like the Microsoft Surface Laptop Studio Two were introduced with NPUs primarily for Windows Studio effects. These NPUs offloaded processing tasks from the CPU, enhancing device performance and battery life.

With the introduction of Copilot+ PCs, the role of NPUs has expanded significantly. Copilot+ PCs can run AI features and processing locally on the device, using the NPU. The NPUs in these devices enable faster and more efficient on-device AI processing (they support over 40 TOPS, which means they can perform more than 40 trillion operations per second). For instance, tasks like natural language translation and generative AI features can be processed locally, reducing the need for cloud-based processing and accelerating processing times.

Built-in features that support NPU offloading are coming to Windows 11, including improved Windows search, across local and cloud-based files. With improved Windows search, Windows 11 will be able to use NPU-powered search capabilities to understand the context of each file, including contents, and return more accurate and complete results.

There is now no need to remember file names, settings locations, or even worry about spelling; just type your thoughts to find what you need on a Copilot+ PC. You can even locate photos in OneDrive by describing their content in the same way. With the over 40 TOPS NPU in Copilot+ PCs, it works even when you’re not connected to the internet. Improved search will initially be available in File Explorer and will later extend to Windows Search and Windows Settings. This means searches in Windows 11 for files will become faster and more intelligent.

Copilot+ PCs also will make Microsoft 365 Copilot better. Microsoft 365 apps will soon be able to use the NPU for AI-based tasks, so the same Microsoft 365 Copilot capabilities that work in the cloud also will be available offline and with lower latency.

This also happens in apps that might surprise you. For example, Microsoft Teams has several AI-based features including face tracking and voice isolation that can use the NPU directly, freeing up CPU resources, increasing performance, and improving battery life.

Boosting ARM-based Windows 11 mobility

We’ve found significant performance improvements from NPU integration, especially from ARM Copilot+ PCs. The reduction in CPU usage has provided significantly better overall performance across Windows 11. Many of our users with ARM-based Windows 11 devices are reporting battery life exceeding 20-22 hours of active usage.

Other benefits of the ARM-based Windows 11 Copilot+ PCs include cellular data connection, providing continuous network connectivity for a new generation of ultra mobile Windows laptops. ARM-based Windows 11 devices also support instant-on power capability, just like your mobile phone or tablet.

Our employees are seeing huge benefits.

“Windows 11 Copilot+ PCs have been a huge difference-maker for our employees,” Gonis says. “Their laptops have become truly mobile devices, and it changes how they use them and where they can take them.”

The deployment of Copilot+ PCs has also highlighted the importance of app compatibility. While many apps that we use run natively on ARM-based devices—including Microsoft 365 and a large percentage of our first party apps—some still use x64 emulation. We’re working to achieve 100 percent compatibility by the end of 2025, ensuring that all our tools can fully take advantage of the capabilities of NPUs and the ARM platform.

It’s a bright feature for hybrid AI, and we’re ready for it with Windows 11 Copilot+ PCs.

Looking forward

We’re continually evaluating and implementing new Windows 11 features as they come available in each release. We’re currently testing hotpatching in Windows 11 to allow updates without system reboots. We aim to reduce the number of required reboots to one per quarter, improving efficiency and maintaining system stability.

We’re also testing the Recall experience. Recall creates an explorable timeline of a Windows 11 PC’s past using snapshots and natural language queries. It helps users find past content on their PC by responding to natural language prompts with images, text, or even the exact location of the item you’re searching for.

Of course, we’re excited about the next generation of Copilot+ PCs and the hardware and software improvements coming to Windows 11. As AI continues its rapid evolution, we’ll be working alongside the Windows 11 team to bring advancements in productivity, accessibility, and security.

We believe that hybrid AI is the future and Windows 11 with Copilot+ PCs is the platform that will support it.

Here are some tips on getting started evolving your Windows ecosystem with Copilot+ PCs:

• Adopt Copilot+ PCs as the hardware platform of choice for Windows 11 devices.
• Explore the enhanced performance and battery life of ARM-based Windows 11 Copilot+ PCs.
• Use Windows Autopatch to manage your Windows 11 deployment.
• Consider the benefits of upcoming Windows 11 features, such as Hotpatch for Windows and Recall for improved efficiency and user experience.

Prepare to deploy Windows 11 at your company.

• Learn more about how hardware-backed Windows 11 is empowering us with secure-by-default baseline.
• Look back at our deployment of Windows 11 at Microsoft.
• Check out how we’re boosting Business Chat in Microsoft 365 Copilot with smart enterprise content management.

• Want more information? Email us and include a link to this story and we’ll get back to you.
• Please share your feedback with us—take our survey and let us know what kind of content is most useful to you.

The post AI in action: Unpacking our internal journey with Windows 11 and Copilot+ PCs appeared first on Inside Track Blog.

If you’re on a sales team, you know that there are all kinds of distracting tasks that eat away at your time and get in the way of what you do best—building relationships with and solving problems for customers.

There’s no doubt that modern salespeople need to rely on too many tools and services to get their jobs done. We in Microsoft Digital, the company’s IT organization, see firsthand the stress this puts on our sales teams.

“We wanted to alleviate as much of that pain as we could,” says Nathalie D’Hers, corporate vice president of Microsoft Digital. “We realized that the AI and automation that comes baked into Copilot for Sales could make the lives of our sellers much better.”

Microsoft is Customer Zero for our own products, which means we typically try them first, put them through their paces, and send our feedback to the product group. Usage has steadily increased since we adopted Microsoft 365 Copilot for Sales internally.

“We’ve had a great Customer Zero experience with Copilot for Sales,” D’Hers says. “We’ve been very pleased with how much it has simplified the lives of our sellers and enabled them to focus more on selling.”

{Check out our full content suite on how we use Microsoft Viva internally at Microsoft. See how we’re evolving our culture with Microsoft Viva. Learn about our journey as the company’s Customer Zero.}

Unlocking human potential with AI and automation

It’s hard to overstate how complicated selling is—there seems to be no end to the countless small tasks that sellers need to accomplish to keep their day-to-day moving. From managing communications to pulling in relevant stakeholders to inputting information into customer relationship management (CRM) software, sales professionals are constantly allocating and reallocating their attention across different apps and work modes.

During internal simplification research at Microsoft, we discovered that our sellers were using as many as 40 tools per day. Flipping back and forth between those different workspaces results in a lot of wasted time.

“Sixty-eight percent of sellers’ time gets spent on critical but tedious sales tasks,” says Cory Newton-Smith, head of product management for Microsoft 365 Copilot for Sales. “If we can identify what they’re doing in this non-selling space and recover time from that, they can spend more of their day where humans excel.”

We wanted to design a way for salespeople to keep essential tasks within the flow of work, then introduce powerful features to speed up their efforts. It’s especially important to minimize the time they spend in CRM programs like Microsoft Dynamics 365 or Salesforce. Although those solutions are essential to modern sales and contain many powerful features, they add steps into a seller’s workflow.

“You have the CRM space and then you have the productivity space,” says Smita Shrivastava, product strategy and growth lead for Microsoft 365 Copilot for Sales. “Sellers mostly work in Microsoft Outlook and Teams, so juggling apps to work within the CRM is a constant drain on productivity.”

Microsoft 365 Copilot for Sales maximizes sales teams’ productivity with AI-assisted content creation and meeting summaries across Microsoft 365 apps. It seamlessly connects data to Microsoft Dynamics 365 and Salesforce CRMs from the apps where salespeople get their work done—within Microsoft Outlook and Teams.

Microsoft 365 Copilot for Sales saves sellers time through three main functionalities:

• Automating and simplifying tasks with AI-generated emails, meeting summaries, data collection, and data entry
• Getting actionable insights in the flow of work by bringing together data from Microsoft 365 apps and CRM systems
• Maintaining momentum with AI-powered analytics that provide recommendations and reminders

“It’s really all about seller productivity,” says Peter Macy, technical specialist within our SaaS organization and pilot program participant for Microsoft 365 Copilot for Sales. “It helps maintain that focus and streamlines your work so you don’t have to jump back and forth and lose attention.”

Deploying Microsoft 365 Copilot for Sales

To deploy Microsoft 365 Copilot for Sales thoughtfully internally here at Microsoft, we engaged our team of change management professionals, product specialists, and internal early adopters to make sure the tool landed just right. Fortunately, we’ve built out a robust deployment and adoption framework that we’ve iterated over several large-scale product rollouts.

“We have a repeatable process for landing changes,” says Alexandra Jones, senior business program and change manager in Microsoft Digital. “We can take advantage of a framework that’s already in place, including local adoption teams in each subsidiary and well-structured pilot programs.”

Deploying Microsoft 365 Copilot for Sales

We built a five-step plan to deploy Microsoft 365 Copilot for Sales to around 60,000 employees worldwide.

01

Build a change management plan

02

Provide landing toolkit

03

Build a change management plan

04

Build a change management plan

05

Build a change management plan

We’ve developed a tried and tested method for deployment that was instrumental in our Microsoft 365 Copilot for Sales deployment.

Through conversations with salespeople across Microsoft, our change management team focused on identifying how the tool would interact with different roles, then built communications around value propositions for each of those use cases. That helped produce readiness toolkits that demonstrated Microsoft 365 Copilot for Sales’ value.

From there, it was time to begin a phased deployment—starting with a pilot. Generative AI drove a lot of uptake thanks to its popularity in the public imagination.

“The second I put out a post asking who wanted to be involved in a pilot, I had virtual hands up all over the world,” Jones says.

Real-world usage by our early adopters in the pilot helped guide our wider deployment of Microsoft 365 Copilot for Sales. One thing we determined was that as a companion app designed to function intuitively, the training burden for Microsoft 365 Copilot for Sales was much lower than for standalone programs. As a result, change managers simply dropped into existing monthly team trainings and town halls to get the message out.

The value of Microsoft 365 Copilot for Sales was immediately apparent. That helped drive adoption across Microsoft.

“The moment sellers launch Copilot for Sales, they see CRM data infused into emails and Teams conversations,” Shrivastava says. “They can see the power of Copilot for Sales very quickly.”

Clearly, Microsoft 365 Copilot for Sales has struck a chord with our sellers. Since general availability in October 2022, we deployed it to nearly all of the company.

We have since moved on to listening and gathering customer feedback. That feedback helps inform both our future deployment efforts and the month-over-month rollouts for new Microsoft 365 Copilot for Sales features. In the meantime, sellers are saving time every day.

Putting time back in salespeople’s days

For sellers like Macy, the most substantial benefit of Microsoft 365 Copilot for Sales is the newfound efficiency that comes from automation. It’s the result of powerful features like the sales pane in Microsoft Outlook, Microsoft 365 Copilot responses, and automated data connections that pull information out of CRMs and prompt you to input new contacts and opportunities.

Research has shown that sellers spend upwards of 60 percent of their time managing their inbox. Microsoft 365 Copilot for Sales helps lighten some of this burden through AI-generated email summaries and responses. According to Macy, this tool can help sellers recapture 20% to 30% of their time.

But it’s more than just time savings. Those Copilot features help sellers reclaim cognitive space that’s better spent on building relationships.

“What I find is that it frees you up to be present in the conversation,” Macy says. “There’s no more going silent or pausing to take hurried notes in the midst of a chat because the technology captures that value for you.”

And perhaps most powerfully, there’s no more broken focus or juggling apps from jumping between Microsoft Outlook, Microsoft Teams, and CRM systems. Contact and opportunity management happen within the flow of work, where sellers spend their time.

As Microsoft 365 Copilot for Sales continues to evolve, our product team has its eye on features that extend its value even further across the Microsoft 365 productivity suite. Those features include intelligent contract authoring in Microsoft Word and automated collaboration space creation with partner channels in Microsoft Teams.

“Our productivity suite is so powerful, but up until now it’s remained relatively generic to suit many different tasks,” Newton-Smith says. “Our new concept is that apps like Copilot for Sales can show up and make these tools more powerful because they’re more contextually relevant to specific jobs.”

For our sellers, the bottom line is that Microsoft 365 Copilot for Sales is saving time and cognitive effort to help them be their fullest selves at work.

“The tool isn’t there to do your job,” Macy says. “It’s there to learn how to work alongside you and accelerate your productivity.”

Here are some tips for getting started with Microsoft 365 Copilot for Sales at your company.

• Leverage the easiest-to-use features first: email summary and conversation intelligence.
• Start with adding new contacts from Outlook to gain easy wins as you familiarize your team with the app.
• Use Microsoft 365 Copilot for Sales as an introduction to generative AI and intelligent co-pilots.
• Get your CRM admins, senior decision makers, and core IT onboard by demonstrating the most useful features.
• Pilot with your all-stars to gain insights and build groundswell for your deployment.
• Connect with your users to see where they’re finding value, then promote those features.
• Sellers like to hear from their peers. Be sure to leverage the champions that develop out of your pilots.

Click here to try or learn more about Microsoft 365 Copilot for Sales.

• Check out our full content suite on how we use Microsoft Viva internally at Microsoft.
• See how we’re evolving our culture with Microsoft Viva.
• Learn about our journey as Microsoft’s Customer Zero.

• Want more information? Email us and include a link to this story and we’ll get back to you.
• Please share your feedback with us—take our survey and let us know what kind of content is most useful to you.

The post See how we’re simplifying our sales with AI-powered Microsoft 365 Copilot for Sales appeared first on Inside Track Blog.

Since generative AI exploded onto the scene, it’s been unleashing our employees’ creativity, unlocking their productivity, and up-leveling their skills.

But we can fly into risky territory if we’re not careful. The key to protecting the company and our employees from the risks associated with AI is adopting proper governance measures based on rigorous data hygiene.

Technical professionals working within Microsoft Digital, our internal IT organization, have taken up this challenge. They include the AI Center of Excellence (AI CoE) team and the Microsoft Tenant Trust team that governs our Microsoft 365 tenant.

Since the widespread emergence of generative AI technologies over the last year, our governance experts have been busy ensuring our employees are set up for success. Their collaboration helps us ensure we’re governing AI through both guidance from our AI CoE and a governance model for our Microsoft 365 tenant itself.

{Learn how Microsoft is responding to the AI revolution with a Center of Excellence. Discover transforming data governance at Microsoft with Purview and Fabric. Explore how we use Microsoft 365 to bolster our teamwork.}

Generative AI presents limitless opportunities—and some tough challenges

Next-generation AI’s benefits are becoming more evident by the day. Employees are finding ways to simplify and offload mundane tasks and focus on productive, creative, collaborative efforts. They’re also using AI to produce deeper and more insightful analytical work.

“The endgame here is acceleration,” says David Johnson, a tenant and compliance architect with Microsoft Digital. “AI accelerates employees’ ability to get questions answered, create things based on dispersed information, summarize key learnings, and make connections that otherwise wouldn’t be there.”

There’s a real urgency for organizations to empower their employees with advanced AI tools—but they need to do so safely. Johnson and others in our organization are balancing the desire to move quickly against the need for caution with technology that hasn’t yet revealed all the potential risks it creates.

“With all innovations—even the most important ones—it’s our journey and our responsibility to make sure we’re doing things in the most ethical way,” says Faisal Nasir, an engineering leader on the AI CoE team. “If we get it right, AI gives us the power to provide the most high-quality data to the right people.”

But in a world where AI copilots can comb through enormous masses of enterprise data in the blink of an eye, security through obscurity doesn’t cut it. We need to ensure we maintain control over where data flows throughout our tenant. It’s about providing information to the people and apps that have proper access and insulating it against ones that don’t.

To this end, our AI CoE team is introducing guardrails that ensure our data stays safe.

Tackling good AI governance

The AI CoE brings together experts from all over Microsoft who work across several disciplines, from data science and machine learning to product development and experience design. They use an AI 4 ALL (Accelerate, Learn, Land) model to guide our adoption of generative AI through enablement initiatives, employee education, and a healthy dose of rationality.

“We’re going to be one of the first organizations to really get our hands on the whole breadth of AI capabilities,” says Matt Hempey, a program manager lead on the AI CoE team. “It will be our job to ensure we have good, sensible policies for eliminating unnecessary risks and compliance issues.”

As Customer Zero for these technologies, we have a responsibility for caution—but not at the expense of enablement.

“We’re not the most risk-averse customer,” Johnson says. “We’re simply the most risk-aware customer.”

The AI CoE has four pillars of AI adoption: strategy, architecture, roadmap, and culture. As an issue of AI governance, establishing compliance guardrails falls under architecture. This pillar focuses on the readiness and design of infrastructure and services supporting AI at Microsoft, as well as interoperability and reusability for enterprise assets in the context of generative AI.

Operational pillars of the AI Center of Excellence

Strategy

Working
with feature crews to determine what we want to achieve with AI at the Microsoft
Digital level and prioritize those AI investments.

Architecture

Enabling infrastructure data, services, access, security, privacy, scalability, accessibility, and interoperability for AI for cases.

Roadmap

Building implementation plans for AI projects, including tools, technologies, responsibilities, targets, and KPIs.

Culture

Fostering collaboration, innovation, education, and ethics among stakeholders.

We’ve created four pillars to guide our internal implementation of generative AI across Microsoft: Strategy, architecture, roadmap, and culture. Our AI certifications program falls under culture.

Building a secure and compliant data foundation

Fortunately, Microsoft’s existing data hygiene practices provide an excellent baseline for AI governance.

There are three key pieces of internal data hygiene at Microsoft:

1. Employees can create new workspaces like Sites, Teams, Groups, Communities, and more. Each workspace features accountability mechanisms for its owner, policies, and lifecycle management.
2. Workspaces and data get delineated based on labeling.
3. That labeling enforces policies and provides user awareness of how to handle the object in question.

With AI, the primary concern is ensuring that we properly label the enterprise data contained in places like SharePoint sites and OneDrive files. AI will then leverage the label, respect policies, and ensure any downstream content-surfacing will drive user awareness of the item’s sensitivity.

AI will always respect user permissions to content, but that assumes source content isn’t overshared. Several different mechanisms help us limit oversharing within the Microsoft tenant:

1. Using site labeling where the default is private and controlled.
2. Ensuring every site with a “confidential” or “highly confidential” label sets the default library label to derive from its container. For example, a highly confidential site will mean all new and changed files will also be highly confidential.
3. Enabling company sharable links (CSLs) like “Share with People in <name of organization>” on every label other than those marked highly confidential. That means default links will only show up to the direct recipient in search and in results employees get from using Copilots.  
4. All Teams and sites have lifecycle management in place where the owner attests that the contents are properly labeled and protected. This also removes stale data from AI.
5. Watching and addressing oversharing based on site and file reports from Microsoft Graph Data Connect.

Microsoft 365 Copilot respects labels and displays them to keep users informed of the sensitivity of the response. It also respects any rights management service (RMS) protections that block content extraction on file labels.

If the steps above are in place, search disablement becomes unnecessary, and overall security improves. “It isn’t just about AI,” Johnson says. “It’s about understanding where your information sits and where it’s flowing.”

From there, Copilot and other AI tools in question can then safely build a composite label and attach it to its results based on the foundational labels it used to create them. That provides the context it needs to decide whether to share its results with a user or extend them to a third-party app.

“To make the copilot platform as successful and securely extensible as possible, we need to ensure we can control data egress from the tenant,” says Keith Bunge, a software engineering architect for employee productivity solutions within Microsoft Digital.

We can also use composite labels to trigger confidential information warnings to users. That transparency provides our people with both agency and accountability, further cementing responsible AI use within our culture of trust.

Ultimately, AI governance is similar to guardrails for other tools and features that have come online within our tenant. As an organization, we know the areas we need to review because we already have a robust set of criteria for managing data.

But since this is a new technology with new functionality, the AI CoE is spending time conducting research and partnering with stakeholders across Microsoft to identify potential concerns. As time goes on, we’ll inevitably adjust our AI governance practices to ensure we’re meeting our commitment to responsible AI.

“Process, people, and technology are all part of this effort,” Nasir says. “The framework our team is developing helps us look at data standards from a technical perspective, as well as overall architecture for AI applications as extensions on top of cloud and hybrid application architecture.”

As part of getting generative AI governance right, we’re conducting extensive user experience and accessibility research. That helps us understand how these tools land throughout our enterprise and keep abreast of new scenarios as they emerge—along with the extensibilities they need and any data implications. We’re also investing time and resources to catch and rectify any mislabeled data, ensuring we seal off any existing vulnerabilities within our AI ecosystem.

Not only does this customer zero engagement model support our AI governance work, but it also helps build trust among employees through transparency. That trust is a key component of the employee empowerment that drives adoption.

Realizing generative AI’s potential

As our teams navigate AI governance and drive adoption among employees, it’s important to keep in mind that these guardrails aren’t there to hinder progress. They’re in place to protect and ultimately inspire confidence in new tools.

“In its best form, governance is a way to educate and inform our organization to move forward as quickly as possible,” Hempey says. “We see safeguards as accelerators.”

We know our customers also want to empower their employees with generative AI. As a result, we’re discovering ways to leverage or extend these services in exciting new ways for the organizations using our products.

“As we’re on this journey, we’re learning alongside our industry peers,” Nasir says. “By working through these important questions and challenges, we’re positioned to empower progress for our customers in this space.”

Consider these tips as you think about governing the deployment of generative AI at your company:

• Understand that IT organizations have inherently cautious habits.
• Leverage what industry leaders like the Responsible AI Initiative are sharing.
• Recognize that employees will adopt these tools on their own, so it’s best to prepare the way beforehand.
• Consider your existing data hygiene and how it needs to extend to accommodate AI.
• Make sure you have an enterprise plan for ensuring labeling and security, because AI tools will provide the most complete access by default.

Get started on your own next-generation AI revolution—try Microsoft 365 Copilot today.

• Learn how Microsoft is responding to the AI revolution with a Center of Excellence.
• Discover transforming data governance at Microsoft with Purview and Fabric.
• Explore how we use Microsoft 365 to bolster our teamwork.

• Want more information? Email us and include a link to this story and we’ll get back to you.
• Please share your feedback with us—take our survey and let us know what kind of content is most useful to you.

The post Getting the most out of generative AI at Microsoft with good governance appeared first on Inside Track Blog.

Editor’s note: This is the fourth video in our ongoing series that showcases our in-house experts using real-world scenarios to explore the transformative capabilities of Microsoft 365 Copilot.

For Robert Epstein, the key to a successful Microsoft 365 Copilot demo is relevance. It’s about showing your audience something that resonates with their daily tasks and makes them think.

He wants them to walk away thinking, “this could really improve my workday,” Epstein says.

Press play to hear Epstein, a partner account manager in the Global Partner Solutions organization, share his tips for getting your employees to start using Copilot at your company.

Epstein says it’s key to research your audience before you begin.

Whether you’re addressing internal teams, partners, or customers, this will allow you to understand their specific needs and pain points is crucial. What are their roles? How familiar are they with Copilot and what it can do?

Tailoring your demo to their level of expertise and interests ensures that your message will have impact. Epstein highlights the importance of setting the right expectations and adjusting your approach based on who you’re presenting to.

Tell an engaging story

Epstein advises keeping your demo focused. Instead of trying to cover every feature, home in on one or two key aspects that will leave your audience with a “wow” moment. This could be a feature that saves them significant time, improves the quality of their work, or helps them accomplish a task they previously found challenging.

In one of Epstein’s demos, he used a real-world scenario about a time he presented Copilot to HP salespeople. He demonstrated how Copilot could quickly summarize a lengthy document from a government website, identify suitable HP products, and draft a formal tender response—all within minutes. This kind of practical, relatable example helps the audience see the immediate benefits of Copilot.

Digging deeper

Epstein’s goal in any demo is to create that one unforgettable moment, using real-world examples, where the audience realizes how transformative Copilot can be. He once showed how Copilot could generate a PowerPoint presentation from a simple Word document in seconds—complete with speaker notes and relevant images.

“It’s important to create a jaw-dropping wow moment for the audience. It can significantly change their perspective or behavior toward a product or solution,” says Epstein.

Epstein also recommends ending your demo with a call to action, encouraging your audience to explore and experiment with Copilot on their own.

Before you demo Copilot

Epstein suggests that anyone preparing a Copilot demo always starts with three key considerations:

• Know your audience. Their familiarity with Copilot, their roles, and their interests
• Focus on one or two aspects, such as a feature that saves your audience time or improves the quality of their work
• Use a real-world scenario to demonstrate the value of Copilot

Thank you for watching Epstein’s presentation! We hope it helps you get started with your Copilot demoes efforts at your company.

• Check out Microsoft 365 Copilot.
• Interested in becoming a Copilot Champ?

• Watch the first video in our Copilot Champs series: Showcasing how our product managers are using Microsoft Copilot.
• Watch the second video in our Copilot Champs series: Using Microsoft Copilot as a trusted advisor for your Six Sigma projects.
• Watch the third video in our Copilot Champs series: Getting your Microsoft 365 Copilot training right
• Learn more about how our Copilot Champs Community is helping drive Copilot for Microsoft 365 adoption here at Microsoft.

• Want more information? Email us and include a link to this story and we’ll get back to you.
• Please share your feedback with us—take our survey and let us know what kind of content is most useful to you.

The post How we’re delivering demos in Microsoft 365 Copilot at Microsoft appeared first on Inside Track Blog.

“Now it’s like creating a book where the pages are always changing,” says Yannis Paniaras, a principal designer in the Microsoft Digital Studio. “At the critical junction in the UX, where humans interact with Copilot, the AI transforms into the conductor of the user experience. This shift is enabling our designers to move away from defining fixed flows to embracing a non-deterministic design style orchestrated by the AI.”

Microsoft Digital Studio is our team of designers and researchers in Microsoft Digital. The Microsoft Digital Studio team is committed to using their expertise in design, research, content strategy, accessibility, and product planning to create experiences that empower Microsoft employees to achieve more in their lives.

Paniaras has observed that designing an AI-enabled product is very different from designing a traditional desktop or mobile app. In conversations with designers, program managers, and developers, he frequently encounters questions about how various product-making disciplines should coordinate their work in this new context.

“We have Copilot, powered by a large language model (LLM), and we use Fluent AI design language for experiences that rely on lean graphical user interfaces with dynamic prompts and dynamically generated, contextual cards,” Paniaras says. “These provide just-in-time user interface elements that map to the generative flow. Consequently, designers are shifting their focus from standard UI towards the vocabulary of prompts, dynamically designed adaptive cards, and on finding consistency withing the UX context. These elements are becoming the new building blocks of AI-based UX design.”

The Microsoft Digital Studio team’s designers still work in Figma, the popular design and prototyping tool, but their designs need to remain open-ended and sometimes more abstract, rather than a set of fixed linear designs.

“The design becomes a set of probabilities,” Paniaras says. “While this poses a challenge for designers, it also encourages us to collaborate more closely with everyone else.”

Laura Bergstrom, a principal UX manager for the Unified Employee Experience team, adds that content designers and designers on her team developed guidance for engineers to scale Copilot responses creating consistent, reliable responses with the right tone of voice at the right time.

“With all the power of generative AI, user experience and design are still responsible for the quality of the experience and the outcome, so we’re finding ways to scale working with engineering and data science,” Bergstrom says.

Spurring collaboration with AI

Using AI to quickly align plans and goals is causing a shift in the way the entire product-making crew works together. “All the different disciplines are working together to get things in place,” Paniaras says.

He tells a story of a designer who worked concurrently with PMs and engineers to design prompts, comparing it with the previous way of doing things.

“It used to be different: you had research, based on that you would have ideas, prototype certain things, build them, then engineers would test them,” Paniaras says. “It was more linear.”

Modern engineering with AI requires a shift to a more collaborative culture on product teams, where there aren’t clear lines of ownership and people can work flexibly together. It’s similar to the shift that engineering went through from the waterfall approach to agile, when instead of owning specific pieces, engineers swarmed over one part of the product for a sprint, then swarmed on another part in the next sprint.

Transitional UI interfaces

Victor Albahadly, a senior UX designer on the Microsoft Digital Studio team, says AI has potential to transform the way he does his core job, which is to test to find out where the designs he and his team build breakdown and fail to meet the needs of the people who will use them.

“I need to figure out what the user wants,” Albahadly says. “When we build an application, I need to know where they are coming from, what they want to do, and where the experience that we’re building for them will break down.”

The challenge is that he has to sample the experiences users have with his designs and extrapolate what he learns to the rest of the design. And importantly, he does this at scale—not for just one person, but for all the people who use the application.

“I need to test how the experience will work for many people,” he says. “That’s an intense process.”

AI has the potential to change that because it will be able to see everything—something a human will never be able to do on their own.

“With AI’s help, someday in the near future, I’ll be able to test the entire application,” Albahadly says. “There will be a lot of power in that.”

AI can help designers get this kind of scale at every step in the process, which not only makes the results far more accurate, but also much faster.

Transforming user testing with AI

The future of ideation

Albahadly also envisions AI enhancing parts of the design process. Today, ideation is done by talking to experts and customers, holding brainstorming sessions, and doing workshops. In the future, he suggests he could do similar ideation with his teammates and AI.

“In your app, say there’s a huge drop-off of traffic coming from Japan,” he says. “Now we need to do a workshop to find out why this is happening. The AI could point to specific stuff like a language barrier or culture barrier, or a time issue like a holiday. Instead of taking a week to ideate, it could become a step in the process the same day.”

In addition to changes in design processes, generative AI is changing the user experience.

“We’ve had a linear way of pumping out experiences—an OS, products on top of it, and apps,” Bergstrom says. “Now there are different copilots, different extensibility, ways of doing things on surfaces. This all has to make sense to a user end-to-end.”

It requires a lot of design thinking to produce that experience.

Data quality is also crucial to producing an experience that makes sense. “Generative AI is a wildcard, which requires data to be more pristine,” Bergstrom says.

For example, the LLM for Microsoft 365 can go through all your emails and SharePoint sites. If you type in “benefits,” it should identify the authoritative source and display that information—not go through your email to find every benefits-related message you’ve ever gotten.

Transforming work with AI

What about the potential of AI to do routine, repetitive work and give people the time to do higher value work? Bergstrom sees a wide range of opportunities.

“We can use generative AI to help employees with everyday tasks, from finding the best place to park to managing the immigration process to identifying the best selections for employee benefits,” Bergstrom says. “And for large enterprises, we can use generative AI to help manage facilities by identifying cost-to-benefit ratios, building usage, and for finding the best locations to have offices.”

Both Bergstrom and Albahadly see an opportunity for AI to help employees write their performance reviews. Bergstrom notes that it could help managers combine review feedback from multiple sources and tie it to OKRs.

And Albahadly says that for employees, AI can help with writing their own performance reviews.

“That’s been a challenge for most Microsoft employees, because at the end of the year, you have to sit and remember everything you worked on,” he says.

Because AI will be exposed to your meetings, your calendar, your projects, it will be easy for it to co-write your review with you.

“In the future, it will be less writing and more selecting stuff, and AI will generate a whole year for you,” Albahadly says.

With all this transformation happening, some people worry about the future of work.

Paniaras is optimistic.

“Everything around us, including our roles, work, processes, and definitions of values, has been created by us humans” he says. “Whenever any of these dimensions change, we inevitably end up redefining them or filling the void. But you need to have that thinking attitude, and the recognition that everything around us is a result of our own making.”

Bergstrom agrees.

“Durable problems don’t change,” she says. “But now we have infinitesimally more ways to solve for those problems with an intelligent assistant that can anticipate needs and predicts possibilities—we’re just trying to figure out how to harness all the capability in our designs.”

Try out Microsoft 365 Copilot to learn what you can do with AI.

Watch John Maeda’s LinkedIn Learning class—UX for AI: Design Practices for AI Developers—to learn more about how collaboration works with AI.

Here are some tips for getting started with generative AI at your company:

1. Embrace AI as a collaborator:
   • Consider AI as a creative partner. It can augment your design process by suggesting patterns, layouts, and interactions.
   • Collaborate with AI tools to generate design variations, explore possibilities, and iterate faster.
2. Understand AI’s capabilities and limitations:
   • Familiarize yourself with the types of AI algorithms commonly used in design, such as neural networks, generative adversarial networks (GANs), and reinforcement learning.
   • Recognize that AI has limitations—it can’t replace human intuition, empathy, or domain expertise. Use it as a tool to enhance your creativity.
3. Design for adaptability and personalization:
   • AI-driven UX should be adaptable and personalized. Create interfaces that adjust dynamically based on user behavior, context, and preferences.
   • Use AI to tailor experiences for individual users, providing relevant content and recommendations.
4. Collect and curate data:
   • AI models require data to learn and improve. Collect relevant user data (with privacy considerations) to train AI algorithms.
   • Curate high-quality datasets that represent diverse user scenarios and behaviors.
5. Iterate and refine AI models:
   • Start with simple AI models and gradually increase complexity. Iterate based on user feedback and real-world usage.
   • Regularly evaluate and fine-tune AI models to ensure they align with user needs and business goals.
6. Ethical considerations:
   • Be mindful of biases in AI algorithms. Ensure fairness, transparency, and inclusivity.
   • Understand the ethical implications of AI-driven decisions and design accordingly.
7. Learn from existing AI-driven products:
   • Study successful AI-powered products and services. Analyze how they integrate AI seamlessly into the user experience.
   • Learn from industry leaders and adapt their best practices to your own projects.

Remember, AI is a powerful tool, but it’s most effective when combined with human creativity and empathy. By embracing AI and understanding its role, UX designers can create innovative, personalized, and adaptive experiences for users.

Find out what you can do with Microsoft 365 Copilot.

• Take this UX for AI: Design Practices for AI Developers class with Microsoft’s John Maeda.
• Explore these five communications-based tips for prompting Microsoft 365 Copilot.
• Unpack deploying Microsoft 365 Copilot internally at Microsoft.
• Discover embracing emerging technology at Microsoft with new AI certifications.

• Want more information? Email us and include a link to this story and we’ll get back to you.
• Please share your feedback with us—take our survey and let us know what kind of content is most useful to you.

The post Redesigning how we work at Microsoft with generative AI appeared first on Inside Track Blog.

AI is a game changer when it comes to improving how our corporate functions operate. At least that is what we at Microsoft, and many in the tech industry, have been claiming over the past year or so… but where is the proof?

This article is the first in a series dedicated to showing how our Microsoft Digital team, the IT organization here at Microsoft, is collaborating with our internal partners to use AI to accelerate growth and radically improve operational efficiencies, specifically for corporate functions such as HR, legal, and real estate. The hope is that by providing concrete examples and outcomes, we can provide our customers with inspiration, a blueprint, and in some cases, a solution, to do the same.

Within Microsoft Digital, the organization that powers, protects, and transforms the digital experience here at Microsoft, we have the pleasure of working day in and day out with our corporate function partners across the company. From HR and legal, to our real estate team, all are being asked to do more with less, with a focus on keeping operational costs down while maintaining or improving productivity. As a partner to these organizations, it’s our job to find ways to allow them to do just that!

And we’re sure it comes as no surprise that AI has been at the center of all this, playing a fundamental role in transforming business workflows while improving operational efficiency, user productivity, regulatory and corporate compliance, and data-driven decision making.

Over the last year, we’ve seen how it can revolutionize the way our internal corporate functions operate by automating repetitive and time-consuming operational tasks. Let’s look at our internal project, an AI-powered document lifecycle management platform, as one of the first examples of this. 

“With AI, we have so many new ways to innovate. From saving valuable time for our legal professionals, to optimizing building occupancy, to helping our HR professionals support employees in the hybrid workplace, to enabling many self-service experiences for our employees; we have incredible potential to make our corporate functions more efficient and impactful,” says Patrice Pelland, a partner software group engineering manager for HR & CELA in Microsoft Digital.

Document management gets a major makeover

Our new AI-powered platform aims to empower our corporate functions teams by revolutionizing end-to-end document management. From crafting templates, authoring documents, and facilitating collaboration to orchestrating seamless workflows, offering secure storage, and managing records, this system uses AI enriched capabilities to bring operational efficiencies, reduce costs, and ensure accurate compliance to any document-based process.

“This platform was developed to address the critical need for end-to-end document management across various verticals within Microsoft,” says Mohit Chand, a principal group engineering manager in Microsoft Digital. “It was created to streamline processes like digitizing documents and address the common pain points that typically makes this activity take months to complete.”

The Microsoft Digital team set out to develop the document lifecycle management platform with six core principles in mind:

1. Automation empowerment: Automate document management to enhance productivity and efficiency.
2. Seamless integration: Integrate with Microsoft 365 and Azure for a seamless user experience.
3. AI-driven innovation: Use cutting-edge AI technology to enhance functionalities in search and analysis.
4. User-centric design: Focus on intuitive interfaces that simplify complex functionalities.
5. Scalable flexibility: Adapt to the needs of different organization sizes and processes.
6. Cost efficiency: Reduce operational costs through optimized document processes.

Transforming our document lifecycle

The team used Microsoft 365, Azure Open AI, Azure Cognitive Services, and Microsoft Purview to create the following system capabilities:

• Template digitization and management: Digitize and manage templates by creating and modifying snippets and operational data fields.
• Secure and controlled editing: Easily manage and update templates and snippets with controlled workflows to ensure only approved and published templates are used.
• Efficient document drafting: Start with standard templates and dynamically assemble documents, incorporating required metadata and content snippets seamlessly in Word.
• Streamlined approval processes: Automate review and approval workflows, integrate eSignatures, and keep everyone updated with real-time notifications and status changes.
• Smart ingestion and storage: Automatically ingest documents, perform validation checks, and securely store them while keeping track of all changes and updates.
• Intelligent content analysis: Extract and use metadata and content snippets for enhanced document classification, improving search capabilities and document retrieval using both keyword and natural language processing (NLP) techniques.
• Automated compliance enforcement: Apply retention labels, manage document lifecycles, and enforce policies to ensure compliance with legal and regulatory standards.

“Our intention after aligning on the core principles and key platform capabilities was to reduce the digitization process from three to six months to less than fourteen days,” says Andrew Voss, a senior product manager in Microsoft Digital. “It was a North Star goal that I’m happy to say has now been achieved for all of our onboarded processes thus far.”

No gaming around: The results speak volumes

One of the first internal organizations to put the new platform to the test was Xbox as they looked to automate one of their most frequent contract types, a critical process for onboarding new games into the Xbox ecosystem. Historically, this process was manual, involving non-digitized templates and redundant data entry across multiple systems, consuming 1,800 hours annually. The manual contract creation process was more than just time-consuming, it could also be error-prone and significantly delay the onboarding of new content and impact service level agreements (SLAs).

In fact, the solution has saved the Xbox team over 1,600 hours resulting in an 88% time savings in the contract generation process, reducing the time it takes for these contracts from 1,800 hours to just 158 hours annually!

“The amount of business impact and return on investment that we’ve been able to deliver by partnering with the Microsoft Digital team has been outstanding,” says Hoss Hostetler, a senior service engineer in Xbox. “The ability to automate initial contract generation from configured templates through to sending out signatures and getting notified of fully signed contracts via application programming interfaces (APIs) has been absolutely game-changing for our team.”

Xbox has been so encouraged by the initial outcome of their results that they are preparing to extend the solution to automate two more of their standard contracts. By doing this, the team is anticipating an additional 600+ hours per year in time savings.

“Our collaboration with Xbox showcases the effectiveness of this solution for optimizing complex business processes,” says Alpa Jain, a senior product manager in Microsoft Digital. “As Xbox continues to expand their use across a wider range of contract types, we are committed to introducing new technical advancements that will contribute to the platform’s growing autonomy, adaptability, and sophistication.”

Making its way to our customers through SharePoint Premium

While the AI-powered platform started as an end-to-end document management solution for our internal Microsoft Corporate Functions teams, many of its capabilities will be showing up in SharePoint Premium. SharePoint Premium is Microsoft’s advanced content management and experiences platform for customers and brings AI, automation, and added security to content experiences, processing, and governance.

This collaboration with the SharePoint team exemplifies Microsoft Digital’s internal innovation being leveraged for external product development. The transfer of knowledge, capabilities, and insights from the internal document management product and Microsoft Digital team is sure to make the SharePoint Premium product much more effective for our customers from the get-go.

“This represents a unique case where Microsoft Digital, as Customer Zero, developed a product to solve the needs and challenges that our internal corporate function customers face, and that solution is now being incorporated into an external customer-facing product,” says Bidyadhar Patra, a principal software engineering manager in Microsoft Digital. “For us, this approach highlights a new way of leveraging internal needs for broader product development.”

Here are some suggestions for how you can take a similar approach to transforming your content lifecycle with AI at your company:

• AI is accelerating corporate functions growth across HR, legal, and real estate through operational efficiency, automated compliance, data-driven insights, and productivity for individuals. 
• By using AI and natural language processing, corporate function leaders can digitize templates for any business process, streamline reviews with AI-assisted analysis, and easily govern their documents with considerable time savings results. The document lifecycle management platform, developed within Microsoft Digital, is a great first example of this.
• Don’t fall behind when it comes to AI, the time is now to start experimenting with and using these technologies to improve business results and maximize return on investment.

Learn more about SharePoint Premium and give it a try.

• Learn how we’re reimagining content management at Microsoft with SharePoint Premium.
• Find out how our employees are leveraging the cloud for file storage with OneDrive Folder Backup.
• Check out how we’re empowering employee self-service with guardrails with sensitivity labels.

• Want more information? Email us and include a link to this story and we’ll get back to you.
• Please share your feedback with us—take our survey and let us know what kind of content is most useful to you.

The post AI is revolutionizing the way we support corporate functions at Microsoft appeared first on Inside Track Blog.

However, for companies considering the adoption of GenAI, there are a multitude of challenges and risks that must be navigated. These range from data exposure or exfiltration where your company’s sensitive data can be accessed by unintended audiences to direct attacks on the models and data sources that underpin them. Not acting and waiting until the world of GenAI settles down poses its own risk. Employees eager to try out the latest and greatest will start using GenAI tools and products that aren’t vetted for use in your enterprise’s environment. It’s safe to say that we’re not just in the era of Shadow IT but Shadow AI, too.

Add to that the fact that threat actors have begun to use these tools in their activities, and you get a real sense that navigating the cyberthreat landscape of today and tomorrow will be increasingly difficult—and potentially headache-inducing!

Here at Microsoft, our Digital Security & Resilience (DSR) organization’s Securing Generative AI program has focused on solving this problem since day one: How do we enable our employees to take advantage of the next generation of tools and technologies that enable them to be productive, while maintaining safety and security?

Building a framework for using GenAI securely

At any given moment, there are dozens of teams working on GenAI projects across Microsoft and dozens of new AI tools that employees are eager and excited to use to boost their productivity or use to be more creative.

When establishing our Securing AI program, we wanted to use as many of our existing systems and structures for the development, implementation, and release of software within Microsoft as possible. Rather than start from scratch, we looked at processes and workstreams that were already established and familiar for our employees and worked to integrate AI rules and guidance into those processes, such as the Security Development Lifecycle (SDL), and the Responsible AI Impact Assessment template.

Successfully managing the secure roll-out of a technology of this scale and importance takes the collaboration and cooperation of hundreds of people across the company, with representatives from diverse disciplines ranging from engineers and researchers working on the cutting edge of AI technology, to compliance and legal specialists, through to privacy advocates.

We work extensively with our partners in Microsoft Security, Aether (AI Ethics and Effects in Engineering and Research), the advisory body for Microsoft leadership on AI ethics and effects, and the extended community of Responsible AI. We also work with security champions who are embedded in teams and divisions across the enterprise. Together, this extended community helps develop, test, and validate the guidance and rules that AI experiences must adhere to for our employees to safely use them.

One of the most popular frameworks for successful change management is the simple three-legged stool. It’s a simple metaphor, emphasizing the need for even efforts across the domains of technology, processes, and people. We’ve focused our efforts to secure GenAI on strengthening and reinforcing the data governance for our technologies, integrating AI security into existing systems and processes, and addressing the human factor by fostering collaboration and community with our employees. The recent announcement of the Secure Future Initiative with its six security pillars emphasizes security as a top priority across the company to advance cybersecurity protections.

Incorporating AI-focused security into existing development and release practices

The SDL has been central to our development and release cycle at Microsoft for more than a decade, ensuring that what we develop is secure by design, by default, and secure in deployment. We focused on strengthening the SDL to handle the security risks posed by the technology underlying GenAI.

We’ve worked to enhance embedded security requirements for AI, particularly in monitoring and threat detection. Mandating audit logging at the platform level for all systems provides visibility into which resources are accessed, which models are used, and the type and sensitivity of the data accessed during interactions with our various Copilot offerings. This is crucial for all AI systems, including large language models (LLMs), small language models (SLMs), and multimodal models (MMMs) that focus on partial or total task completion.

Preventative measures are an equally important part of our journey to securing GenAI, and there’s no shortage of work that’s been done on this front. Our threat modeling standards and red teaming for GenAI systems have been revamped to help engineers and developers consider threats and vulnerabilities tied to AI. All systems involving GenAI must go through this process before being deployed to our data tenant for our employees to use. Our standards are under constant review and are updated based on the discoveries from our researchers and the Microsoft Security Response Center.

By integrating AI into these existing processes and systems, we help ensure that our people are thinking about the potential risks and liabilities involved in GenAI throughout the development and release cycle—not only after a security event has occurred.

Improving data governance

While keeping Gen-AI models and AI systems safe from threats and harms is a top priority, this alone is insufficient for us to consider GenAI as secure and safe. We also see data governance as essential to prevent improper access, improper use, and to reduce the chance of data exfiltration—accidental or otherwise.

At the heart of our data governance strategy is a multi-part expansion of our labeling and classification efforts, which applies at both the model level and the user level.

We set default labels across our platforms and the containers that store them using Purview Information Protection to ensure consistent and accurate tagging of sensitive data by default. We also employ auto-labeling policies where appropriate for confidential or highly confidential documents based on the information they contain. Data hygiene is an essential part of this framework; removing outdated records held in containers such as SharePoint reduces the risk of hallucinations or surfacing incorrect information and is something we reinforce through periodic attestation.

To prevent data exfiltration, we rely on our Purview Data Loss Prevention (DLP) policies to identify sensitive information types and automatically apply the appropriate policies at the controls at the application or service level (e.g. Microsoft 365), and Defender for Cloud Apps (DCA) to detect the use of risky websites and applications, and if necessary, block access to them. By combining these methods, we’re able to reduce the risk of sensitive data leaving our corporate perimeter—accidentally or otherwise.

Encouraging deep collaboration and sharing of best practices

So far, we’ve covered the management of GenAI technologies and how we ensure that these tools are safe and secure to use. Now it’s time to turn our attention to our people, the employees who work with and build with these GenAI systems.

We believe that anyone should be able to use GenAI tools confidently, knowing that they are safe and secure. But doing so requires essential knowledge, which might not be entirely self-evident. We’ve taken a three-pronged approach to solving this need with training, purpose-made resource materials, and opportunities for our people to develop their skills.

All employees and contract staff working at Microsoft must take our three-part mandatory companywide security training released throughout the year. The safe use of GenAI is comprehensively covered, including guidance on what AI tools to use and when to use them. Additionally, we’ve added extensive guidance and documentation to our internal digital security portal ranging from what to be mindful of when working with LLMs to the tools which are best suited to various tasks and projects.

With so many of our employees wanting to learn how to use GenAI tools, we’ve worked with teams across the company to create resources and venues where our employees can roll up their sleeves and work with AI hands-on in a way that’s safe and secure. Hackathons are a big deal at Microsoft, and we’ve partnered with several events including the main flagship event, which draws in more than 50,000 attendees. The Skill-Up AI presentation series hosted by our partners at the Microsoft Garage allows curious employees to learn the safe and secure way to use the latest GenAI technologies not only in their everyday work, but also in their creative endeavors. By integrating guidance into the learning journey, we help enable safe use of GenAI without stifling creativity.

Here are our suggestions on how to empower your employees with GenAI while also keeping your company secure:

• Understand the challenges and risks associated with adopting GenAI technology at your company. Good places to start are assessing the potential for data exposure, direct attacks on models and data sources, and the risks associated with Shadow AI.
• Develop resources and guidance for your employees to educate them on the risks of using AI. Fostering collaboration and a strong community in support of secure use of GenAI.
• If applicable, incorporate AI-focused security into existing development and release practices. Check out the Security Development Lifecycle (SDL) and the Responsible AI Impact Assessment template for inspiration.
• Work to bolster your data governance policies. We strongly recommend starting with labeling and classification efforts, employing auto-labeling policies, and improving data hygiene. Consider tools such as Purview Data Loss Prevention (DLP) and Defender for Cloud Apps to prevent data exfiltration and limit improper data access.

Learn more about our overall approach to GenAI governance internally here at Microsoft.

• Learn how we’re providing further transparency on our responsible AI efforts at Microsoft.
• See how we’re staying ahead of threat actors in the age of AI.
• Learn more about implementing a Zero Trust security model at Microsoft.
• Start reducing your organization’s Shadow IT risk in 3 steps.

Want more information? Email us and include a link to this story and we’ll get back to you.

Please share your feedback with us—take our survey and let us know what kind of content is most useful to you.

The post Empowering our employees with generative AI while keeping the company secure appeared first on Inside Track Blog.

How works councils work

Our works councils serve as the voice of our employees in some geographies, advocating for their rights and interests within the workplace. As AI technology grows in influence across industries, these internal organizations, and labor in general, are at the forefront of discussions regarding the implications of AI for the modern workplace.

While our relationship with our works councils has always been cooperative and collaborative, how we engaged with our works councils for product reviews has evolved over time from impromptu and inconsistent engagements to more strategic and programmatic opportunities for feedback that can improve our products for the benefit of all our customers.

Irina Chemerys, a global program manager overseeing the intake process for works councils at Microsoft Digital, is among those who sought to streamline the approval process for new technology across works council countries from around the globe.

Chemerys proposed a global approach using a single request form and platform for works councils worldwide to communicate with Microsoft Digital, product groups, legal, HR, and others at the company. This streamlined communication across the board and facilitated collaboration among all works councils, allowing smaller countries to take advantage of resources from larger ones and creating a more cohesive global community. The unified approach significantly improved coordination, collaboration, and, importantly, trust among works councils.

“We built this standardized community, and we were able to discuss Copilot as an AI technology and how we should proceed with this in a globalized setting,” Chemerys says.

When it came time to deploy Microsoft 365 Copilot products, this process was in place and ready to help the works councils quickly evaluate it. “This helped us navigate the tolerance phase that Germany introduced not long after,” Chemerys says.

Germany opens tolerance phase for Copilot

Our German works council initially resisted allowing AI technology development and deployment, raising a number of concerns about how Copilot was responding in ways that could be interpreted as evaluating individual employee performance or making impermissible inferences about individual employees without the data to support those inferences. Building trust with the works councils was the first step in alleviating concerns and building a collaborative approach to AI technologies.

“In my conversations with works councils, I would emphasize that AI is akin to a speeding train—the technology is evolving faster than we can review all aspects of it,” Chemerys says. “Our best course of action is to prepare and steer its direction.”

The country’s works council eventually agreed to a tolerance phase for Copilot and other AI tools, with an emphasis on the need for controlled deployment rather than attempting to halt inevitable technological advancement.

“From a legal and ethical perspective, generative AI is a tool that could be used to establish performance and behavior control in a company,” says Carsten Schleicher, chairman of the Microsoft works council in Germany. “But we don’t give resistance or feedback because we don’t want AI—we want to address the potential impact of a tool.”

The Copilot might, if prompted, generate a summary and ranking of employee performance during a meeting. That kind of assessment fell outside the aims of our Microsoft AI principles. Recognizing the importance of getting these issues right, our engineers engaged directly with our works councils to understand their feedback and identify ways to address it in the product.

“Another market-wide concern is the potential for AI tools to hallucinate false information it generates without a clear source,” Schleicher says. “AI represents an exciting evolution in our interaction with computers, yet the ultimate decision-making should always remain in human hands, ensuring thoughtful analysis of the insights provided by AI.”

Some members of works councils were early adopters who took part in the first Copilot deployment wave, and as such, they had time to get to know the tool by trying it out and by asking questions during regular meetings. Their feedback was channeled to the product engineering team. This early access helped the works councils quickly reach an agreement that the deployment of Copilot could continue and led to product improvements that will benefit all our customers.

France agrees to the tolerance phase

Because of how fast our AI products are evolving, France became one of the countries where we had to shift the typical way we work with our works councils.

“We didn’t have all the answers regarding what the impact of Copilot would be,” says Juliette Reigner, a manager of works councils in France. “Usually, in a consultation process, we are required to have all the details—but AI requires us to be more agile and flexible in our approach than ever before.”

Our works council in France decided to also implement a tolerance phase that was more flexible and innovative than usual.

Microsoft France asked the councils to nominate people to be part of a new technology committee. The committee organized weekly sessions to examine new technologies such as Copilot, with council members having deep involvement in testing new technologies.

“We suggested that works council members be part of pre-deployment testing and product planning to be part of innovation, and to better understand the impact of new technologies like Copilot,” says Edith Dubuisson, a senior business program manager in Microsoft Digital who manages our relationship with the Microsoft works council in France. “Copilot is not proactive in what it does—it will not perform tasks that it is not tasked with and has limitations in place to protect workers rights and well-being.”

Final consultations with French works councils happened in February 2024. The consultation results? A green light from the council to continue with Copilot development and deployment.

After Germany and France were able to get to a state of tolerance, other countries followed quickly with the Netherlands being the last to agree to tolerate the rollout after its works council had the time to review its potential impacts on our employees in that country.

In the end, our works councils continue to be a source of invaluable feedback in this new fast-moving AI era; playing a role that transcends mere oversight and instead embraces proactive engagement. For us, works councils serve as trusted partners in product development and innovation, spotting potential issues, and opportunities.

“If the councils raise concerns about a feature or capability, it’s likely our customers will share those concerns,” Chemerys says. “By capturing their feedback in early stages, we can design better products, so we have shifted to thinking about works councils as competitive advantages and co-innovators.”

Here are some tips for working with your works councils as you deploy AI products like Microsoft 365 Copilot at your companies:

• Works councils can play a powerful role in driving digital transformation and representing employees’ interests in the new era of AI. They can be co-innovators, early adopters, champions, and business partners, instead of showstoppers.
• Enabling your works councils to be early adopters can improve your partnership with them, especially if you take their feedback seriously.
• Offer training and education to your works councils members to help them address their concerns and empower them to deeply understand the product or service you want their help to deploy.
• Trust can only be established if you ensure works councils are involved early, and if you are fully transparent with them.

Try out Microsoft 365 Copilot at your company.

• Get our tips for partnering with your works councils.
• Read our story on how we deployed Microsoft 365 Copilot internally at Microsoft.
• Learn how we’re getting the most of generative AI with good governance.
• Visit our content suite where we share the story of how we’re deploying AI internally at Microsoft.

• Want more information? Email us and include a link to this story and we’ll get back to you.
• Please share your feedback with us—take our survey and let us know what kind of content is most useful to you.

The post Deploying Microsoft 365 Copilot and AI at Microsoft with our works councils appeared first on Inside Track Blog.

[Learn about our strategy for deploying Microsoft 365 Copilot for Sales internally at Microsoft and the progress we’ve made against our vision. Check out our full content suite on how we use Microsoft Viva internally at Microsoft. See how we’re evolving our culture with Microsoft Viva.Learn about our journey as Microsoft’s Customer Zero.] 

Unleashing the potential of Copilot for Sales

Lori: It’s been six months since you’ve deployed Copilot for Sales, what results are you seeing? What key considerations did you have when rolling out a generative AI tool like Copilot for Sales on a global scale?

Nathalie: Copilot for Sales is deployed across Microsoft. Being customer zero has been invaluable in this process. It has allowed us to confirm the product, learn important insights, and make improvements along the way. We’ve been focused on turning on Copilot features to enhance the seller experience, and the feedback we’ve received from our own teams has been instrumental in refining and perfecting the deployment. I’m so excited to partner with our teams to see the first commercial solution at Microsoft to combine Copilot and Copilot for Sales.

Since the launch of Microsoft Dynamics 365 Copilot in March, we have seen incredible adoption with nearly 4,000 users taking advantage of its capabilities. The impact has been significant, with approximately 37,500 draft emails generated through the power of generative AI. It’s encouraging to see the positive response from our users and the value they are experiencing. In fact, during a recent customer conversation, the Senior VP of Sales expressed their enthusiasm to partner with us as early adopters, emphasizing their willingness to invest in any technology that enhances the productivity of their sellers. It’s a testament to the effectiveness of Copilot and its ability to drive tangible benefits in the workplace.

Nathalie: It’s been quite the journey since we launched Copilot for Sales to our Microsoft sellers. What were the main goals your team hoped to achieve with this product?

Lori: We’ve been focused on seller productivity gains through taking advantage of conversation intelligence, enabling Copilot features, and ultimately improving customer connection, job satisfaction, and revenue for our sellers. Microsoft being customer zero has provided us with a unique advantage. It has allowed us to test these features within our own organization, gather valuable feedback, and fine-tune the experiences before rolling them out to more customers.

In the new update, we are adding some exciting capabilities to Copilot for Sales that have been influenced by your team’s customer zero work. Sellers can get real-time suggestions and guidance as they craft emails, pulling insights from automated email summaries. It’s like having a virtual assistant right at their side, helping them to generate compelling content and ensuring that no opportunity is missed. Our sellers have embraced these features with enthusiasm, recognizing how it significantly boosts their productivity and enables them to focus on building strong customer relationships.

Nathalie: Speaking of Copilot, how does your organization ensure that the implementation of Copilot features align with Microsoft’s ethical and responsible AI principles?

Lori: Supporting ethical and responsible AI practices is of paramount importance to us and our customers. As we use generative AI, we are committed to helping our customers be transparent, fair, and accountable to their employees and their customers.

As you know, one of the ways we do this here is with our works councils, where a few of our colleagues volunteer to help us protect the privacy of all our employees when we deploy new technology like Copilot for Sales. More importantly, they make sure we follow privacy laws in each of the countries and regions where we operate. We roll the feedback that we get from them directly into our products, which helps our customers protect their own employees. It’s this kind of thinking—and these kinds of checks and balances—that helps us be ethical in how we use AI in Copilot for Sales.

Lori: We were so excited to be the first Microsoft product to bring Copilot to our users; the feedback we have received from sellers has been incredibly positive! How have our newest Copilot in Copilot for Sales features influenced your thinking about supporting the employee experience?

Nathalie: It helped a lot! Seeing a tangible implementation of Copilot with real value opened our eyes to what was possible and is influencing ways that we’ll incorporate generative AI into our own employee experience. Kudos to you and your team for dreaming big and acting fast to bring that experience to the market!

Lori: Thank you. So, tell me more about this employee experience and how deploying Copilot for Sales Copilot in Microsoft has given your team insights and learnings that shaped your approach to using AI?

Nathalie: The success of Copilot for Sales really inspired my team to think more deeply about how we could further use AI in our employee experience at Microsoft. Just like Copilot for Sales provides conversation summaries and next actions for sales opportunities, we’re thinking through scenarios that will enable us to transform the way employees interact with our different services—like support and HR—to make them more personalized and efficient.

Broadly, our efforts fall into three categories—AI for IT, AI for the hybrid workplace, and AI for the employee experience. AI for IT includes investments to help us proactively detect and remediate issues in our employee services and IT infrastructure. AI for the hybrid workplace includes investments to help us perfect space planning and to enhance the experience when employees come into the office. Finally, AI for the employee experience is all about transforming the ways that Microsoft employees interact with our services and support. Across each of these investment areas, Copilot for Sales provided us with a great benchmark for how AI can really propel employee productivity.

Works councils and deployment

Lori: Nathalie, as the leader responsible for deploying Copilot for Sales across Microsoft, I understand that your team has been actively engaging with works councils. Can you provide insights into the impact of working with works councils during the deployment process?

Nathalie: Absolutely, Lori. Works councils play a critical role in standing for the interests of employees within our organization, particularly in European countries where they are prevalent, and they make sure that whatever we deploy internally within the company protects the privacy of the employees who live in that region. Engaging with works councils ensures that we consider the perspectives and concerns of the workforce during the deployment of Copilot for Sales. Their input is valuable in addressing compliance, privacy, and employee relations matters, making our deployment process more robust and aligned with local regulations.

Lori: What have you found to be some of the challenges in managing a global-scale deployment of Copilot for Sales?

Nathalie:Deploying any new technology globally has challenges, but the speed and efficiency with which we were able to roll out this transformative product was truly remarkable. We are working on a brand-new solution that is revolutionizing the way generative AI changes the workplace, and being customer zero has given us some unique advantages. We’ve had to navigate compliance and obtain necessary approvals for deploying AI features on a global scale. Our active engagement process, which includes working closely with works councils, has been instrumental in streamlining the deployment process and ensuring that our global teams can receive help from Copilot for Sales. Despite the challenges, the feedback from sellers has been incredibly positive, especially with the AI-generated email content enhancements we’re introducing. The best part is how easy and painless it is to enable Copilot for Sales, allowing our teams to quickly harness its productivity-boosting capabilities and experience a seamless transition to a more efficient way of working.

Lori: It seems like building an effective approval process is crucial. How replicable has Microsoft made this process for other companies?

Nathalie: At Microsoft, we have developed a globally recognizable, efficient process for enabling Copilot scenarios. By supporting open dialogue, we can gather feedback, address emerging concerns, and align our deployment approach with evolving regulations. We recently set up a framework with European works councils to supply valuable insights into employee needs and expectations, enabling Microsoft to tailor the product and deployment process accordingly. We encourage all companies to get connected with their respective works counsels to achieve a balance between rapid implementation and compliance, ensuring that their employees are protected, and the organization meets regulatory requirements.

Lori: It’s truly exciting to see the transformative power of Copilot for Sales in action and see the positive impact it’s having on our organization!

To learn more about our internal deployment of Microsoft 365 Copilot for Sales, read our “See how we’re simplifying our sales with AI-powered Microsoft 365 Copilot for Sales” blog post.  You can also read more about our internal deployment of Microsoft Viva at Microsoft by visiting our “Viva la vida! Work life is better at Microsoft with Viva” content suite. Learn more about other applications and capabilities in Microsoft Dynamics 365 Copilot for Sales using the links below:

• Learn more about tips Microsoft has for working with works councils.
• Take a look at Dynamics 365 Sales and Copilot for Sales release wave documentation on Microsoft Learn.
• Watch the Copilot in Copilot for Sales demo.
• Stay up-to-date on Copilot for Sales features and updates on the Copilot for Sales Blog.

If you’re not yet a Microsoft Dynamics 365 Sales customer, check out our Dynamics 365 Sales webpage where you can take a guided tour or get a free 30-day trial.

We’re always looking for feedback and would like to hear from you. Please head to the Dynamics 365 Community to start a discussion, ask questions, and tell us what you think!

Click here to try or learn more about Microsoft 365 Copilot for Sales. 

• Find out how we’re simplifying our sales with AI-powered Microsoft 365 Copilot for Sales.
• Check out these seven things we learned deploying Microsoft 365 Copilot for Sales at Microsoft.
• Read the Microsoft 365 Copilot deployment and adoption guide we put together based on our internal experience here at Microsoft.
• Take a look at our Microsoft 365 Copilot deployment and adoption guide for executives.

• Want more information? Email us and include a link to this story and we’ll get back to you.
• Please share your feedback with us—take our survey and let us know what kind of content is most useful to you.

The post The power of AI in Microsoft 365 Copilot for Sales: Insights from Lori Lamkin and Nathalie D’Hers appeared first on Inside Track Blog.

Here at Microsoft, we have a rich IT history that we look to for inspiration and clarity as we help build the future of technology, especially in the burgeoning generative AI space. There are few on our team who understand this better than Patrice Trousset.

In his more than 25 years at Microsoft, Trousset has lived through important moments in our history and has learned a thing or two. It remains his goal to share his experience and help future leaders understand where we’ve been to better prepare the company for where we are going. His ultimate message? “The only limit is the imagination,” Trousset says.

In part two of our interview with Trousset, we hear about some of his best memories from his storied career. Often, these moments revolve around the people he had the pleasure of working with, customers and teammates included.

Click through here to view our “Pivot to generative AI” part one of our series with Trousset.

• Learn more about Microsoft Azure AI.
• Sign up for a free Azure AI Studio trial by signing up for a free Microsoft Azure account.

• Explore the spotlight on Digital Transformation collection.
• Discover reinventing Microsoft’s Employee Experience for a hybrid world.
• Unpack the digital transformation through mastery of the Microsoft employee experience.

The post How Microsoft’s IT legacy is powering its future appeared first on Inside Track Blog.

Microsoft has been digitally transforming since long before the term became a buzzword. In fact, it’s that spirit of continuous transformation and innovation that has enabled the company to pivot and embrace generative AI internally so quickly, says Patrice Trousset, a longtime member of our IT organization, Microsoft Digital Employee Experience.

Trousset would know since he’s been part of IT at Microsoft for so long—more than 25 years—that he is an unofficial historian. Watch this interview with him, the first of a two-part series where he shares how our long history of focusing on the experience our employees have at work has set us up to be ready for our shift to generative AI.

“The purpose has always been the same, even if the role has changed: Support, simplify, optimize everything for our end users, our employees and the organization—to make their lives easier,” Trousset says. “So, every morning when I have my nose in my coffee cup, I’m thinking about that.”

• Learn more about Microsoft Azure AI.
• Sign up for a free Azure AI Studio trial by signing up for a free Microsoft Azure account.

• Read more about how Microsoft’s IT legacy is powering its future.
• Explore the spotlight on Digital Transformation collection.
• Discover reinventing Microsoft’s Employee Experience for a hybrid world.
• Unpack the digital transformation through mastery of the Microsoft employee experience.

The post How Microsoft’s pivot to generative AI is being fueled by its rich IT history appeared first on Inside Track Blog.

When Microsoft recently opened its new Microsoft Canada headquarters building in downtown Toronto, it did so with a lot of transformative smart building capabilities that people keep asking Eric Wand about.

Wand, a Toronto-based director of business programs on the Microsoft Digital Employee Experience team, talks with customers a lot, and lately they’ve been asking him about his new office.

Watch our interview with Wand to learn more about his role, including his view on deploying Signature Microsoft Teams Rooms at the new Toronto headquarters building. “It bridges that divide between being physically present in the room and those who are remote,” Wand says. “It allows any attendee—whether they’re remote or in the room—to be seen, to be heard, and to feel included.”

He also speaks to how AI is transforming everything about our work here at Microsoft among other topics.

• Check out our blog post on deploying Signature Microsoft Teams Rooms at Microsoft.
• Explore how we’re rethinking meetings at Microsoft with Microsoft Teams Rooms.
• Unpack the spotlight on Digital Transformation series.

The post Deploying Signature Microsoft Teams Rooms, generative AI at new Microsoft Canada headquarters appeared first on Inside Track Blog.