Organizations are moving beyond chatbots to AI agents capable of autonomous multi-step workflows. McKinsey’s 2025 survey found that 23% of respondents report their organizations are scaling agentic AI systems—systems based on foundation models capable of acting in the real world, planning and executing multiple steps in a workflow.
What Happened
The transition from conversational AI to agentic AI represents a fundamental shift in how enterprises deploy the technology. Rather than responding to queries, agentic systems can execute tasks autonomously within defined parameters. In 2026, these systems will become embedded in enterprise operations, though organizations are prioritizing controlled autonomy with human oversight.
Key Data
Scaling agentic AI: 23% of enterprises
AI high performers: More than three times more likely to pursue transformative business change
Management practices: Agile product delivery, talent strategies, and technology infrastructure correlate positively with AI value creation
Expert Analysis
“In 2026, agentic AI systems, capable of autonomously executing multi-step tasks and workflows, will become embedded in enterprise operations. However, organizations are prioritizing controlled autonomy, ensuring AI agents operate within predefined business rules, approval chains, and auditability requirements.”
— Dan Herbatschek, CEO, Ramsey Theory Group
“2025 was the year of experimentation. Looking ahead to 2026, curiosity will give way to commitment as enterprises start to rely on AI agents as business-critical tools.”
— Solutions Review, AI and Enterprise Technology Predictions
What’s Next
The psychological shift from testing agents to trusting them will widen between successful organizations and those that struggle. Companies that invest upfront in controls and guardrails will unlock productivity gains; those rushing to deploy without oversight will face failures.
Frequently Asked Questions
What is agentic AI?
AI systems capable of autonomously planning and executing multi-step workflows, rather than simply responding to individual queries.
About the Author
Sarah Kim covers enterprise software and previously worked as a software engineer at major technology companies.
About The Author
