Foreword

Over the past several months, AI agents have moved from experimental technology to infrastructure that enterprises use in production. Unlike traditional software that waits for human input, agents reason through problems, make decisions, and take action autonomously—handling everything from multi-step coding workflows to cross-functional business processes.

This shift toward automated workflows and multi-step agentic systems fundamentally changes what organizations require from AI: models that are secure when handling proprietary data, compliant with industry regulations, and robust against adversarial attacks like jailbreaks.

In partnership with research firm Material (opens in new tab), we surveyed over 500 technical leaders in the United States across company sizes and industries to understand how organizations are using agents today and where they see opportunity in 2026. What emerged is a clear picture of technology in transition: from task automation to strategic impact, from single-function pilots to cross-functional deployment, and from incremental efficiency to fundamental shifts in how work gets done.

The data shows this shift in concrete terms. According to our research, more than half of organizations (57%) now deploy agents for multi-stage workflows, including 16% that have progressed to cross-functional processes spanning multiple teams. In 2026, 81% plan to tackle more complex use cases—39% developing agents for multi-step processes and 29% deploying them for cross-functional projects.

Given the growth of agentic coding over the past 12 months, it's unsurprising that nearly 90% of organizations surveyed use AI to assist with coding today.

Organizations report AI agents free up more time across the entire development lifecycle—from planning and ideation (58%) to code generation, documentation, testing, and review (all at 59%).

The impact also extends well beyond software development. Beyond engineering, the highest-impact use cases include data analysis and report generation (60%) and internal process automation (48%), with 56% planning to implement agents for research and reporting over the next year. And 80% report these investments are already delivering measurable economic returns—not projected value or pilot results, but actual ROI.

Eight in 10 organizations believe AI agents have already delivered measurable ROI, with another 1 in 10 saying they expect them to deliver more economic impact in the future. The question facing leaders in 2026 isn't whether to adopt AI agents but how to scale them strategically while addressing integration challenges (46%), data quality requirements (42%), and change management needs (39%).

Read on to learn more about how today's leaders are building AI agents in the enterprise.

Survey methodology

In partnership with Material, Anthropic surveyed over 500 technical leaders across company sizes and industries in late 2025 to understand current AI agent adoption patterns and future plans. Respondents included engineering leaders, IT executives, and technical decision-makers from organizations ranging from startups to large enterprises across multiple sectors.