Skan AI publishes Agentic Process Automation Manifesto
Manifesto outlines six principles for building AI agents in the enterprise
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Skan AI has released its Agentic Process Automation Manifesto, a set of six principles for building artificial intelligence (AI) agents in the enterprise.
The concepts are drawn from more than fifty real-world deployments at some of the globe’s largest enterprises in banking, healthcare, insurance, and services, according to the announcement.
The manifesto seeks to address a number of common agentic AI failures and reflect a new era of enterprise AI.
The PEX Report 2025/26, based on the findings of a global survey of more than 200 professionals, found that 40 percent of businesses are currently using AI agents/agentic AI. Meanwhile, more than half (59 percent) are planning to invest in agentic AI/AI agents in the next 12 months
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Learn MoreShaping agentic process automation
Enterprise operational knowledge remains largely undocumented, residing in individual expertise, and informal practices, stated a press release.
By systematically capturing work patterns and encoding them into intelligent automation, organizations can accelerate processing, ensure regulatory compliance, and enhance customer experience while maintaining complete control over data privacy and operational risk.
This digital footprint becomes a living blueprint that AI agents follow to execute complex, multi-step processes from start to finish, providing full context about variations, compliance requirements, and the inevitable exceptions that break traditional automation.
This approach transforms automation from a tool that handles simple, repetitive tasks into a capability that manages complex, variable workflows requiring judgment and context.
“Every large enterprise wants AI that can reason and act. The blocker is that agents lack an accurate picture of how work is actually performed,” said Manish Garg, co-founder and chief product officer of Skan AI. “The missing piece is the living system of record of process execution.”
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Six principles for a new standard of enterprise AI
The six principles featured in Skan AI’s Agentic Process Automation Manifesto are:
- Telemetry over assumptions. Train and govern agents based on real human–system interactions such as clicks, keystrokes, and decisions across approved applications. Use actual behavior, not assumptions.
- Execution over analytics. Insights must power end-to-end execution. Agents should plan, act, and validate outcomes across both UIs and APIs, closing the loop from knowing to doing.
- Transparent governance. Policy-as-code, case memory, and step-level evidence ensure every action is explainable and reversible. Approvals, audit trails, and rollback are built-in, not bolted on.
- Open architecture. Integrate seamlessly with existing systems, models, and controls, no rip-and-replace required. Model-agnostic, connector-rich, and standards-aligned, agents operate wherever the work lives.
- Outcome-driven metrics. Success is measured by business outcomes and not by bot counts. Metrics like cycle time, first-pass yield, exception rate, compliance adherence, and cost-to-serve are tied directly to each case.
- Human-AI collaboration. Humans and agents operate as one team with defined roles, escalation paths, and human-in-the-loop checkpoints. Expert interventions are captured and reused, increasing reliability over time.
“You cannot improve what you do not capture,” commented Cijo Joseph, chief technology and digital officer at Mitie. “When operational telemetry informs agents and controls are built in from the start, you see faster resolution times and more consistent compliance. These principles reflect what it takes to deliver durable outcomes in complex organizations.”
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