The world stands on the brink of a productivity revolution as artificial intelligence (AI) creates a new wave of opportunity for businesses of all sizes.

Whether it’s using chatbots or more advanced AI, uncovering deeper insights about customer needs, or speeding up product development, no business wants to miss out on the uplift in output offered by AI. For some organisations, the arrival of generative AI tools such as ChatGPT and Dall-E, which generate content and images, has further boosted the business cases for adopting an AI strategy.

But while business leaders are keen to make the most of the technology’s advantages, they’ll also need to understand the wider responsibilities that come with it (for example, considerations around data privacy, unintentional bias, and copyright infringement) and how to make the most of opportunities that are evolving quickly.

To help boardroom executives and IT leaders navigate a successful AI strategy, Michael Wignall, director of infrastructure in the Customer Success Unit at Microsoft’s Azure business, sets out the first five steps he believes leaders should take ahead of utilising AI.

1. Make AI part of a broader cloud computing strategy

First and foremost, says Wignall, businesses should think about collaborating with an established technology provider.

AI works best when it is part of a broader cloud computing strategy, which is where IT operations are outsourced to externally run data centres, such as the cloud platform offered by Microsoft Azure, he says.

“AI is born in the cloud, and you need to be in the cloud to take advantage of this wave of innovation,” he adds. He points to the three main components of AI – computing power, data and algorithms – all of which are best provided through a cloud service. He believes businesses should adopt a “cloud native” approach, where their entire AI infrastructure is built on a cloud platform.

Such an approach brings many benefits, including: cost savings achieved by paying for only the resources used, rather than maintaining and updating costly on-premises equipment; flexibility and scalability, which allows customers to easily add or remove resources as needed; access to enhanced security tools, which can better detect, assess and warn customers about threats to their data; and disaster recovery, as in the cloud data can be easily backed up and quickly restored in the event of an outage or disaster.

2. Locate your data

Next, businesses need to get a firm handle on where data is located in their organisations and then migrate it to the cloud platform.

Success in AI depends on analysing large sets of relevant data. To fine-tune AI to achieve the best business results, it should be powered by the company’s own data from customer lists, inventories, sales information, financial and other key data. “It’s about making sure that your data platform and your data strategy are the best they can be and that you know where your data is located and how to access it,” says Wignall.

Overall, organisations need to become more data literate. “To succeed with AI, most of our customers, big or small, need to create a more data-led corporate culture,” he adds.

3. Protect your data

Once the cloud infrastructure is in place and the relevant data is migrated, the next crucial step is to protect and secure that data. With all of a company’s key data in one place – the cloud – it’s important to have peace of mind when multiple threats, such as hackers, exist. “Make sure you are protected with best-in-class security capabilities, with well-defined policies and governance around who can access the data as well as the ability to audit what they do with it,” says Wignall.

He adds that Azure offers a full set of built-in security capabilities with products such as Microsoft Defender for Cloud, a cloud native cybersecurity platform. Meanwhile, Microsoft Purview offers unified data governance, allowing users to map their data landscape and ensure their data complies with rules and regulations.

4. Decide what functions or tasks to use AI for

With the infrastructure, data and security in place, businesses can move on to deciding the best uses for AI – whether to automate office processes, extract insights from data, handle copywriting or a range of other tasks.

Over the past five years, general AI has offered what are known as “cognitive services” such as data analytics and product recommendations.

Generative AI takes the technology to a new level. With a few keystrokes, users can create content such as reports, adverts, images, copy, automatic emails and personalised connections with users.

Generative AI can also analyse a large selection of documents, call centre logs or financial results and summarise the information in a short precis.

Microsoft is building a range of AI capabilities into its workplace tools through Microsoft Copilot, which combines AI with applications such as Word, Excel and Teams – for instance, automatically summarising the main points of a Teams meeting.

Another area that can be enhanced by generative AI is rapid prototyping, where designers and product engineers can develop their ideas in days or hours rather than weeks or months.

5. Put in place responsible AI policies

Once a company puts these steps in place, its AI strategy is ready for rollout. But before launch, the business should make sure it has implemented responsible AI policies throughout. The business must make sure that the AI is not embedding bias, that it has adequate governance around its use, that it is being used ethically and does not produce unexpected or unwanted results.

Microsoft provides responsible AI policy guidance and offers tools to check for bias, ensure inappropriate data is excluded and run sentiment checks that vet the output. Ultimately, though, it is essential the business makes sure responsible AI policies are in place.

With many organisations just setting out on their AI journey, Wignall sums up the thinking that businesses should adopt when considering AI: “Urgency is key. Partnership is key. Cloud is key. Prioritise the business benefits that matter to your organisation. And get started today.”

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Non-independent content produced as part of a commercial deal with Guardian Labs.

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As organisations move their computing infrastructure into the cloud, they are harnessing the power of data as never before. Cloud-based services are using artificial intelligence (AI) to make data more accessible, easier to search and simpler to understand. Rather than data being the preserve of a team of data scientists and analysts, the new cloud-based tools and technologies are opening up this specialised area to a wider cohort of employees across organisations.

Leighton Searle, director of Azure Solutions UK at Microsoft, sees strong benefits for businesses that run their IT infrastructure through the Microsoft Azure cloud platform. “The huge potential of new generative AI technology has triggered renewed urgency and focus on the quality and availability of an organisation’s data,” he says. Once businesses migrate their data to the Microsoft Azure cloud platform they can instantly access tools and services to unlock its value for both employees and customers. This is leading to a transformation of company culture and the embedding of data more deeply across businesses.

Searle identifies four areas where cloud is boosting the use of data, empowering employees, and enhancing productivity.

1. Empowering employees to make data-driven decisions

Searle highlights that the cloud is helping to democratise data, making it accessible to employees directly in their daily workflows, rather than stuck in management reports or individual line-of-business applications. “To unlock the value – and realise the potential – of data, it’s got to be accessible to the people who need it,” says Searle. “That could mean empowering a contact centre agent with a scannable summary of all customers’ previous engagements, transactions and support calls alongside immediate access to the entire company’s knowledge base of specialist information to provide a world class customer experience, or a mobile mechanic so they are able to identify a part and inventory status from a photograph captured on their phone.”

Almost every role can benefit from timely, secure and relevant data, says Searle. If staff are to become responsible for managing the data relevant to their roles, they will need tools that simplify the process. Data visualisation tools help employees create simple representations of data to glean insights and improve the customer experience. For instance, Heathrow Airport is using the Microsoft Power BI data visualisation tool through Microsoft Teams to turn data from its admin systems into easy-to-read visualisations for staff. These offer employees an at-a-glance look at how airport passenger traffic is changing in real time, enabling airport staff to prepare for passenger traffic peaks and troughs rather than simply react to them.

2. Breaking down data silos

To achieve greater data democracy, data must be available across an organisation rather than being locked up in a central repository. “With the right guidance, governance and guardrails in place, you can then enable the rest of the business and provide them access to the data they need,” says Searle.

For instance, a group of five south London boroughs formed the South London Partnership and worked to create a universal data platform with Microsoft Azure. This includes sharing data from “internet of things” (IoT) sensors that monitor at-risk residents – which the partnership estimates has already helped to save four lives. The IoT sensors also monitor air quality and flood risks. “We’ve been able to break down data silos through cloud technology’s ability to share data while maintaining the permissions and privacy of that data,” says Searle.

3. Building AI and modern search to accelerate business

Customer and employee expectations have changed as AI-powered experiences play a greater role in everyday life. Along with a good data foundation and a good data culture these experiences are rapidly becoming table stakes for both employee and customer retention. Employees need to delve deep into institutional knowledge, from finding data in the company’s in-house apps or accessing historical information in either “structured” tables and charts or in “unstructured” form in documents, images and other sources.

Searle points to the Azure Cognitive Search platform and Azure Open AI Service, which allows users to input a general, natural language query into a search bar – which the AI-powered system will process to deliver back a natural language summary from the most relevant sources, referencing all of the data sources used for verification or further research. He says this type of AI-powered experience can help businesses unlock insights and make data-driven decisions intuitively and at a speed never seen before.

For instance, Cambridge and Peterborough NHS foundation trust moved its computing infrastructure into the cloud and made patient records more easily searchable by clinicians using Azure Cognitive Search. The trust uploaded all of its records to Azure, and these included data in all sorts of unstructured formats such as handwritten records, doctors’ notes, scans and pictures.

Clinicians said it was “mind blowing” to discover that Azure Cognitive Search made these diverse formats discoverable, and they could quickly locate handwritten notes and records from previous years.

4. Creating a data-driven culture

From frontline workers to boardroom executives, all employees should be open to embedding data into their working practices, says Searle. He believes they can all learn from the data that is flowing to them and contribute to enriching it. Employees involved in managing their own data are also well placed to reduce the risks of bias and incorrect assumptions in their data-driven decision making.

Data democratisation requires a significant shift in corporate culture, Searle believes. Departments across an organisation, whether HR, marketing, operations, sales or finance, have an important role to play in the data that they produce and consume. For example, these business users of organisational data are best placed to set the security and access policies for their data and to curate it in a way that other parts of the business can confidently make use of it.

The pace of change can be daunting for leaders at all levels. To help organisations upskill, Microsoft has partnered with European business school Insead to create a free online course called AI Business School.

Searle sums up the steps businesses need to take to get the most out of their data. “Bring your data securely into the Microsoft cloud. Lead from the top to create a data-led culture across the organisation and then move quickly on projects that are going to deliver business value. The positive experience will cascade across the business and help embed this data-led approach to scale even further.”

Read more about Microsoft AI-powered industry solutions

Explore the Microsoft UK AI Hub

Non-independent content produced as part of a commercial deal with Guardian Labs.

Header photograph: Charday Penn/Getty Images

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