Kore.ai, the global leader in enterprise AI platform and agentic applications, today released the 2026 Kore.ai Agent Productivity Index™, a survey of over 400 IT business leaders on the state of agentic AI in the enterprise. The report shows that 72% of enterprises say their AI agents operate with unmanaged risk, including financial and compliance exposure.
The Agent Productivity Index report found that companies are increasingly granting AI agents authority over data, decisions, and customer interactions, yet most IT leaders cannot fully account for how those agents exercise that authority. The survey further found that AI agents are executing tasks that enterprise leaders do not fully trust, cannot adequately trace, and that are already contributing to revenue loss. The numbers show how far authority has outrun control.
Key Findings
The survey covered IT business leaders at U.S. organizations with 2,000 or more employees. Among the key findings:
- 79% have had to reverse an action taken by an AI agent
- 72% say their agents introduce unmanaged financial or compliance risk.
- 70% have faced a failure their teams could not trace
- 62% have delayed deployments over governance concerns
- 53% are running agents they do not fully trust or understand
- 42% report lost revenue tied to an AI agent failure
These are not trivial tasks, and when one agent fails that failure rarely stays contained. 40% of enterprises saw a single agent failure cascade across multiple systems, turning one bad decision into many. This business exposure is amplified specifically because, in the first half of 2026, AI has been granted authority over work that is consequential for businesses: 41% of agents are running data migrations and system updates, 26% are approving or denying decisions, and 15% are acting on financial transactions. Enterprises have handed agents real authority and, in most cases, cannot fully account for how that authority is used.
This data is supported by leading research organizations. McKinsey reports 62% of organizations are experimenting with or scaling AI agents, but fewer than 10% have scaled them in any single function. Gartner forecasts that, by 2027, 40% of enterprises will demote or decommission autonomous AI agents due to governance failures. Both reports cite rising costs, unclear value, and weak risk controls. Enterprises are deploying agents faster than they are building the foundation architecture and governance frameworks needed to run them safely.
Why Adding Controls Later Does Not Work
The common response to agent risk is to add a guardrail, a monitor, or a policy engine after the agent is completed. These tools are widely deployed, yet the Index shows that problems continue to override the controls.
The reason is structural. A control added after-the-fact governs only the running agent. It cannot influence how the agent was built or how it will be updated and improved over time. Bolting governance onto an agent after it is assembled is not the same as building the agent governed from the start. The value in enterprise AI is moving up the stack, away from the model and toward the harness: a single layer that builds, deploys, manages, and optimizes an agent as one system, with governance defined within, not added afterwards.
“Enterprise AI has shifted from showing that AI works to proving it can be trusted,” said Raj Koneru, CEO and founder of Kore.ai. “Governance has to be built into the agent itself, not added once it is running, because trust comes from visibility, reproducibility, auditability, and control, not from the model getting it right every time. The companies that scale AI will be the ones using AI to build, govern, and improve AI on a single layer. That is the architecture this market is moving to, and it is the one we’ve built.”
The Kore.ai Agent Platform
The Kore.ai Agent Platform, Artemis edition, was built to run the full lifecycle as one system. Its AI agent architect, Arch™, turns plain-language objectives into agents defined in Agent Blueprint Language™ (ABL), a declarative language that validates and governs each agent before it runs. The same foundation deploys those agents, manages them in production with traceability and policy enforcement built into the design, and optimizes them continuously, with Arch reviewing production behavior and proposing improvements for human approval.
Governance, observability, and operational control are enforced before any agent goes live. The platform is model-agnostic and cloud-agnostic, and runs in public cloud, sovereign, private, or on-premises environments with data residency by region. Agents that once took months to build now ship in days, governed from the first build and improving after they go live.
“The market is solving for visibility, but enterprises need accountability. Those are not the same thing. An agent that can be watched but not governed is still a liability. Enterprises do not need better ways to monitor their agents. They need agents built right from the start and governed through production scale,” said Peter Mullen, Chief Marketing Officer, Kore.ai.
The Index points to a single conclusion: Agents deliver the productivity enterprises expect when one layer builds, deploys, manages, and optimizes them as a single system, governed from the first step. Run as four disconnected efforts with governance added at the end, the failures the Index measures become the predictable result.
Download the Kore.ai AI Agent Productivity Index report.
Methodology
The Kore.ai Agent Productivity Index is based on a survey conducted by Propeller Insights, commissioned by Kore.ai, of over 400 IT business leaders aged 34 to 50 at U.S. organizations with 2,000 or more employees, fielded in May 2026. Responses were representative of the U.S. population for age, gender, region, and ethnicity. The maximum margin of sampling error was plus or minus 3.0 percentage points at a 95% confidence level. Kore.ai intends to publish the Index annually.
About Kore.ai
Kore.ai is a global leader in enterprise AI, helping organizations transform customer experiences and workplace productivity through trusted, scalable AI. The Kore.ai Agent platform and prebuilt agentic solutions enable enterprises to design, deploy, govern, and optimize multi-agent systems across customer service, workplace productivity, and industry-specific use cases. Its breakthrough innovations include the Agent Blueprint Language (ABL), Arch AI, and a dual-brain architecture enabling organizations to scale AI with confidence and control. Built on an open, model-agnostic architecture, the platform gives enterprises the freedom to choose their preferred AI models, cloud infrastructure, and enterprise systems. Trusted by more than 500 Global 2000 organizations, Kore.ai maintains a strong AI patent portfolio and is consistently recognized by leading industry analysts for innovation and market leadership. Headquartered in Silicon Valley, Kore.ai serves customers worldwide through a global network of offices and partners. To learn more, visit www.kore.ai.
View source version on businesswire.com: https://www.businesswire.com/news/home/20260617610324/en/
Media gallery
