Enterprise investment in AI is surging in 2026, with Gartner calling it an “inflection year” for aligning AI projects with business goals, according to technologyreview.com. Tech teams—including engineers and developers—have increasingly adopted agentic AI over the past 18 months to automate and coordinate workflows. This trend comes as IT infrastructure costs are projected to grow two to three times by 2030, while budgets remain flat, per McKinsey data cited in the report.
The report highlights that agentic AI’s promise extends beyond task automation to managing entire workflows that integrate human and machine efforts. However, confidence in delegating tasks to AI agents depends on their ability to perform reliably, safely, and securely. Technology experts surveyed show high confidence in using agentic AI for AI, data, and cloud-related tasks, but readiness declines when business context is insufficiently provided to the systems.
This shift toward agentic AI reflects growing pressure on organizations to demonstrate measurable financial returns from AI investments. The tech function is a prime area for AI agents given its rising costs and unchanged budgets. The findings underscore a broader industry movement to embed AI deeply into operational workflows, aiming to optimize efficiency and cost-effectiveness. McKinsey’s projection of escalating IT costs adds urgency to adopting AI-driven solutions that can manage complex infrastructure demands.
The report from technologyreview.com underscores that successful deployment of agentic AI hinges on supplying adequate business context to these systems. As organizations navigate this transition, the next critical milestone will be how effectively AI agents can integrate strategic business objectives while maintaining operational safety and reliability.