{"id":3140,"date":"2025-05-08T07:00:00","date_gmt":"2025-05-08T15:00:00","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/startups\/blog\/?p=3140"},"modified":"2025-06-25T05:34:59","modified_gmt":"2025-06-25T13:34:59","slug":"5-prevalent-ai-themes-for-both-startups-and-enterprise","status":"publish","type":"post","link":"https:\/\/www.microsoft.com\/en-us\/startups\/blog\/5-prevalent-ai-themes-for-both-startups-and-enterprise\/","title":{"rendered":"5 prevalent AI themes for both startups and enterprise"},"content":{"rendered":"\n
Since the beginning of 2025, Microsoft for Startups team members have traveled to three continents and multiple countries (USA, UK, Barcelona, Eastern Europe, and India), served on more than 10 panels, and consumed more airport coffee than I care to admit<\/em>. But it\u2019s all been worth it, because I have the opportunity to share these insights with you. Okay, maybe not the coffee. <\/em><\/p>\n\n\n\n With Microsoft Build 2025<\/a> coming up, I\u2019ve spent some time reflecting on the events I\u2019ve already had the opportunity to attend in 2025\u2014and the insights startups can garner from these industry gatherings. This year, the Microsoft for Startups<\/a> team has been hopping from city to city\u2014London to New York to Bengaluru\u2014to take the opportunity to meet with and listen to early\u2011stage AI startup founders. And I mean truly listen<\/strong>.<\/p>\n\n\n\n Pro tip: As a startup founder, treat these face-to-face moments as golden opportunities for customer discovery. There\u2019s nothing quite like an in-person chat to get unfiltered feedback on your product or idea. No survey or call can replicate the spontaneous insight from a hallway conversation.<\/p>\n<\/blockquote>\n\n\n\n After the keynotes and clapping, we actively sought out individual founders and corporate contacts, grabbing time in quiet corners to ask two simple and fluff\u2011free questions:<\/p>\n\n\n\n Through their responses, we picked up on five consistent themes and challenges. And if you\u2019re hearing similar issues or objections in your organization, we\u2019ve also provided some options to help you resolve them.<\/p>\n\n\n\n Here are the themes we identified:<\/p>\n\n\n\n \u201cAI agents\u201d are dominating the headlines. Every major keynote and panel seem to talk about them. The startups leaning into agentic AI are getting attention\u2014and often massive fundraising rounds. From a corporate perspective, however, enterprises still have several problems that they’re sharing with us. For example:<\/p>\n\n\n\n For founders asking if they should pivot to agentic AI:<\/p>\n\n\n\n Building AI products requires massive<\/em> computing power\u2014both to train models and to run them in production. Unlike a typical software startup, an AI startup might need clusters of GPUs. Shortages of that computing power have made capacity scarce and pricey. Many founders shared stories of how they start by prototyping with a powerful hosted model like GPT-4o, and before they know it, the API bill becomes their biggest expense. Ouch.<\/p>\n\n\n\n While GPU hours are cheaper than two years ago, it’s important to keep a pulse on the model releases. Once you’ve proven value and retention, explore downgrading to cheaper models (for example, drop from a GPT-4o to a Phi-4). Depending on your use case, some optimize their models for efficiency, even if it sacrifices a bit of accuracy\u2014a slightly less complex model might cut cloud costs by five times.<\/p>\n\n\n\n Many AI teams are also exploring other ways to reduce costs such as prompt caching, batch processing, and other creative approaches. We’re also seeing creative hybrid strategies that involve orchestrating across multiple models to utilize cheaper models for most traffic and use premium models for only the tasks where quality truly matters.<\/p>\n\n\n\n Pro tip: For startup founders, the generative boom holds an unpleasant truth: compute expenses can outstrip revenue and threaten your startup\u2019s survival if left unchecked. So make sure you start thinking through your cost-control playbook. <\/p>\n<\/blockquote>\n\n\n\n Since Andrej Karpathy\u2019s February tweet<\/strong><\/a>, investors can\u2019t stop asking about \u201cvibe coding\u201d\u2014the prompt\u2011driven, chat\u2011with\u2011your\u2011IDE (Integrated Development Environment) workflow that lets non\u2011technical founders ship production apps in days. This boom has led to thousands of AI startups springing up, many with overlapping ideas. And that brings up its own challenge: how do you stand out?<\/p>\n\n\n\n If the technical barriers to building AI applications are falling, it’s more important than ever to focus on building a defensible company. Differentiation is more critical to your startup\u2019s survival than ever. And to differentiate in a crowded market, you need to be thinking long and hard about your \u201cmoat.\u201d<\/p>\n\n\n\n Need some inspiration? Here are a few examples:<\/p>\n\n\n\n The big takeaway here is embrace the new \u201cvibe coding\u201d world but plan for defensibility. Leverage AI doors to move fast\u2014but don\u2019t skip the strategy. Ask yourself at every step: \u201cIf it\u2019s this easy for me, couldn\u2019t someone else do the same thing? How will I stay ahead?”<\/p>\n\n\n\n AI job postings grew 38% between 2020 and 2024 and are still climbing.\u00b9 But every founder we met said the same thing: \u201cI can find prompt engineers but I cannot find skilled AI engineers.\u201d <\/p>\n\n\n\n Behind every AI product is human talent\u2014data scientists, machine learning engineers, research scientists, and the like. Hiring these specialists is a major challenge, especially for early-stage startups. There\u2019s fierce competition for anyone with machine learning (ML) and AI skills, as tech giants and well-funded later-stage startups can offer hefty salaries and stock packages. Moreover, new sub-domains like AI safety, LLMOps (large language model operations) and MLOps (machine learning operations), and data engineering for AI require experience that few people have.<\/p>\n\n\n\n Founders shared stories about how long it took to fill key positions. In some cases, critical roles stay open for more than six months because the talent pool is so limited. The strategies we discussed included:<\/p>\n\n\n\n Yes, we all live on Microsoft Teams<\/a> meetings, Viva Connect communities, Loop pages, and email threads, but every pivotal insight in this post originated from a hallway track conversation: seeing a founder\u2019s whiteboard or back-of-the-napkin sketch, overhearing a complaint about data lineage, sharing cloud bill horror stories over dinner, discussing the differences between Model Context Protocol (MCP) and Agent2Agent<\/a> (A2A). The list goes on and on, but they all came through in-person conversations.<\/p>\n\n\n\n That\u2019s why our next big stop is<\/strong> Microsoft Build<\/a> (May 19 through 22, 2025, in Seattle, WA)<\/strong>\u2014the perfect chance to pressure\u2011test these ideas with more than 5,000 builders, swap notes on Copilot roadmaps, and maybe settle the \u201cvibe\u2011coding vesus real\u2011coding\u201d debate once and for all.<\/p>\n\n\n\n I\u2019m looking forward to engaging in even more of these conversations\u2014and testing these insights\u2014at Microsoft Build 2025, our annual developer conference where developers, founders, and tech enthusiasts<\/a> gather to learn about the latest innovations and updates from Microsoft. I look forward to asking those same questions of enterprise customers and founders in attendance.<\/p>\n\n\n\n And I also look forward to catching up with our Pegasus startups<\/a> in attendance including Bria<\/a>, Coactive<\/a>, D-iD<\/a>, Dataloop<\/a>, Factory AI<\/a>, Faros AI<\/a>, Galileo AI<\/a>, Howso<\/a>, Kubiya AI<\/a>, Moderne AI<\/a>, Nimble<\/a>, and Qodo<\/a>.<\/p>\n\n\n\n We\u2019ll be on the expo floor trading stories, showcasing some of our top AI startup solutions that will revolutionize the way you build AI applications, and hunting for the next hallway inflection. If any of the lessons above resonated with you, find Microsoft for Startups<\/a><\/strong> while you\u2019re there and tell us more about what you’re building.<\/strong><\/p>\n\n\n\n <\/p>\n\n\n\n\n
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1. Beyond agents: A lot of AI problems remain unresolved <\/strong><\/h2>\n\n\n\n
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2. The increasing need for a cost control playbook (such as controlling compute costs)<\/strong><\/h2>\n\n\n\n
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3. \u201cVibe coding\u201d lowers the barrier on building software\u2014but raises the bar on moats<\/strong><\/h2>\n\n\n\n
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4. The AI talent wars <\/strong><\/h2>\n\n\n\n
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5. Face\u2011to\u2011face still wins in an LLM world<\/strong><\/h2>\n\n\n\n