Nearly a third of organizations have decided against buying software because they can build it themselves with agentic coding tools, according to a McKinsey report on the state of AI in 2026. The shift signals a broader change in how enterprises approach technology: instead of defaulting to external vendors, they're asking what their own teams can build.
The report, based on a global survey, found that 32 percent of respondents said their organizations had forgone at least one software purchase because internal development with AI coding tools was feasible. Technology companies lead the trend at 41 percent, followed by healthcare payers and providers at 39 percent, and professional services and energy and materials at 38 percent. Financial institutions register 36 percent, media and telecom at 34 percent, and pharmaceuticals at 33 percent. Insurance (19 percent) and the public sector (17 percent) lag behind.
McKinsey Senior Partner Lieven Van der Veken said the change reflects growing confidence in internal tech teams. "Until recently, many leaders assumed that AI was beyond the capabilities of their own technology teams, and that moving quickly meant securing the right external partnership," he said. "Now, the tone is changing. Leaders are asking what their organisations need to build AI tools themselves. The rise of software coding agents and in-house development is one clear sign of this broader shift."
AI adoption is scaling across enterprises
The report also tracks broader AI adoption. Nearly nine in ten respondents report regular use of AI in at least one business function. Enterprise-wide scaling grew from 38 percent to 44 percent over the past year, and organizations deploying AI across three or more functions rose from 51 percent to 56 percent.
Larger enterprises are moving faster. Fifty-four percent of respondents from organizations generating at least USD 1 billion in annual revenue report scaling AI enterprise-wide, compared to one-third of smaller organizations. The gap is wider with agentic AI: larger enterprises scaling agents in one or more functions jumped from 27 percent to 40 percent, while smaller organizations stayed flat at 22 percent.
Van der Veken cautioned against reading the trend as a rejection of external partnerships. "This, of course, does not mean companies should build everything themselves or turn away from forging partnerships," he said. "It means that leading organisations are engaging partners from a position of agency." He added that the fastest-moving organizations are deliberate about where to buy, where to build, and where to develop internal capability to integrate and scale what works.
For IT and development professionals, the shift means in-house teams are becoming strategic assets rather than cost centers. Building software with agentic tools requires new skills - prompt design, AI-assisted code review, and integration of AI agents into existing workflows. Professionals who develop these capabilities position themselves for roles with more ownership over product decisions, as their organizations increasingly rely on internal builds over vendor purchases. For those looking to build these skills, an AI Learning Path for Software Developers covers the practical application of AI tools in development work.
Why this matters for IT and development professionals
The report's findings suggest that software development teams will be asked to do more than write code. They'll be expected to evaluate whether internal builds make sense, prototype quickly with AI tools, and maintain the resulting systems. That's a broader mandate than most development teams have today.
The skills gap is real. Teams that can effectively use agentic coding tools will deliver software faster and at lower cost than those that can't. The report's data on enterprise scaling - 44 percent of organizations now deploy AI across the business - means the demand for these skills is already here. For professionals in AI for IT & Development, the opportunity is to move beyond using AI as a coding assistant and toward owning the build-versus-buy decisions that are increasingly landing on their desks.
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