Agent confidence on the technical frontier

The tech function is at the forefront of AI adoption, with Gartner calling 2026 an "inflection year" for aligning AI projects with strategic business objectives. Microsoft Azure Platform is leading the charge, with Jeremy Winter, corporate vice president and chief product officer, emphasizing the importance of agents operating within existing operational boundaries. As a result, tech teams are increasingly confident in using agentic AI for tasks such as generating reports, boilerplate code, and data quality monitoring. In fact, a survey of 300 global technology experts found that confidence in agents is surging for measurable tasks and growing in areas of complex judgment. The report ranks 101 tasks across AI, data, and cloud workflows based on respondents' confidence in agents acting on their behalf.

The growing reliance on agentic AI in tech functions highlights the broader trend of AI adoption in enterprise settings. As McKinsey projects IT infrastructure costs to grow two to three times by 2030, companies are seeking ways to automate tasks and reduce costs. The use of agents in data workflows, in particular, is a breakthrough domain, where teams trust them to make decisions based on reliable foundations. This trend is closely tied to the increasing importance of systems thinking, as emphasized by Amanda Silver, corporate vice president of Microsoft 365 Core and Work IQ, and Kim Manis, corporate vice president of Product for Microsoft Fabric. By keeping humans in the loop and leveraging domain experts, companies can ensure that agents deliver trusted outcomes.

The implications of this trend are significant, with risks associated with automated decision-making and the need for human oversight. As agents become more prevalent, companies must ensure that they are designed to operate within existing operational boundaries and governance models. The report highlights the importance of business context in agent development, particularly for complex tasks that require advanced reasoning capabilities. Companies must also address the challenge of providing high-quality data to agents, which is a key factor in their success. As the use of agentic AI continues to grow, it will be essential to monitor these developments and adapt to the changing landscape.