AI at Scale: How 2025 Set the Stage for Agent-Driven Enterprise Reinvention in 2026

2026: The Year Agents Move to Professionalized, Orchestrated Systems

While the survey found a reported decline in agent deployment at 26% (down from 42% in Q3), that number is more than double the 11% reported in Q1 and does not reflect the reality KPMG is observing among leading enterprises. In our client work and at KPMG, we see the opposite trend: leaders have moved beyond initial deployments and are professionalizing and preparing to scale agent systems – readying data, investing in infrastructure, and building governance and observability to run multi-agent systems reliably.

“The topline adoption number undersells what’s actually happening among leaders,” Chase continued. “They’re not pulling back, they’re professionalizing their agents and agent systems. We’ve also seen leaders adopt more sophisticated definitions of what constitutes a true agent with higher aspirations of what’s possible as the technology rapidly advances and they see material value from the agents they’ve already deployed.”

Investment and engineering capacity are focused on production-grade, orchestrated agents - systems that can be governed, monitored, secured, and integrated at scale. Leaders are converging on platform standards that consistently manage identity and permissions, data access, tool catalogs, policy enforcement, and observability, so each new agent strengthens the system rather than adding fragility.

That portfolio of work is a recognized challenge, with nearly two-thirds of leaders (65%) citing agentic system complexity as the top barrier for two consecutive quarters.

“Much of this work is happening behind the scenes today but it sets the stage for a very different 2026 because value doesn’t come from launching isolated agents,” said Swami Chandrasekaran, Global Head of KPMG AI and Data Labs. “2026 will be the year we begin to see orchestrated super-agent ecosystems, governed end-to-end by robust control systems that drive measurable outcomes and continuous improvement.”

The Great Skills Reset: Designing the Workforce for Human-Agent Collaboration

As enterprises professionalize and prepare to scale agents, the top-of-mind question for every leader is the size, shape, and skills of their workforce of the future. The differentiator is no longer basic adoption, it’s effective human-agent teaming, grounded in ethical practices and measurable outcomes.

• Entry-level hiring is being reimagined: 64% of organizations have already altered their approach due to AI agents’ influence, up from 18% last quarter, reflecting the need for new competencies in data, automation, and responsible AI.
• Agents as project leads: 44% of leaders expect AI agents to take lead roles in managing specific projects alongside human teams over the next 2 to 3 years.
• Talent premiums are real: 76% of leaders are willing to offer up to 10% higher compensation for candidates with strong AI skills.
• Boards are upskilling rapidly: 40% of leaders say their board members now have substantial AI expertise, a five-fold increase from two quarters ago (8%).
• New roles are emerging: AI prompt engineer, AI performance analyst, and AI trainer/data curator are among the most anticipated roles.

Against this backdrop, we also saw a rise in employee resistance to AI. Leaders will need to communicate transparently and invest in upskilling to prepare teams.

Security Is a First-Order Constraint and the Catalyst for Enterprise Hardening

Cybersecurity is the single greatest barrier to achieving AI strategy goals – 80% of leaders say so, up from 68% in Q1. It is also projected to be the top investment category; half of executives plan to allocate $10-50 million in the coming year to secure agentic architectures, improve data lineage, and harden model governance. Data privacy (77%, up from 53% in Q1) and data quality (65%, up from 37% in Q1) have risen sharply as agent-to-agent workflows and tool integrations expand risk.

Enterprises are responding pragmatically by hardening platforms, controls, and integration:

• 72% plan to deploy agents from trusted technology providers.
• 60% restrict agent access to sensitive data without human oversight; nearly half also employ human-in-the-loop controls across high-risk workflows.
• Beyond speed, leaders are prioritizing security, compliance and auditability (75%) as the most critical requirements for agent deployment.

Leading teams are embedding privacy by design and segmenting sensitive data to trace and remediate issues early and ensuring auditability across agent actions and tool calls. These safeguards are becoming foundational to scaling agents responsibly in 2026.

The Bottom Line

Capital is flowing, ROI confidence is rising, and agents are moving from pilots to professionalized platforms with focus and investment in safeguards.

The KPMG Quarterly Pulse Survey captures perspectives from 130 U.S.-based C-suite and business leaders representing organizations with annual revenue of $1 billion or more. The report was prepared by the KPMG US AI & Digital Innovation group led by Stephen Chase.