Session 1 — Why AI Agents Struggle to Deliver Enterprise Value
Are you a CEO, CIO, COO or transformation leader responsible for demonstrating the return from enterprise AI?
Session 1 of 4 in The Agentic Enterprise, a WORK-SELF webinar series on turning agentic deployments into measurable ROI.
Thursday, 22 October 2026 | 2:00 PM BST | 9:00 AM EDT | 30 minutes
AI agents can complete tasks faster, but that does not necessarily mean enterprises are completing more work. Employee rework, reviews, handoffs and exceptions can absorb the productivity gains that automation appears to create.
McKinsey’s 2026 research finds that 80% of respondents report improvements in individual productivity from AI, while only 37% report a positive impact on organisational EBIT.
Where is the value being lost?
This session examines why agent productivity does not automatically translate into enterprise ROI, how leaders can identify the right workflows for agentic deployment, and what needs to be measured to demonstrate business value.
The Missing Layer in Enterprise AI
AI agents can access enterprise applications, retrieve information and execute tasks. But access to systems does not tell an agent who owns the work, what decisions it is authorised to make, when human judgement is required or who remains accountable for the outcome.
This is where Human Context becomes essential. It brings together governed information about employee responsibilities, decision authority, review requirements, escalation rules and the operating conditions that determine how people and AI agents work together.
As enterprises scale agentic workflows, Human Context Infrastructure is emerging as a distinct layer of enterprise technology, connecting existing systems, employees and AI agents through governed, identity-aware operating data.
WORK-SELF is developing this infrastructure through Maya Enterprise, providing approved AI agents with Human Context at runtime so they can operate within established enterprise responsibilities, governance and accountability structures.
What we’ll cover
Where AI productivity gains get lost before they reach operating performance
How employee rework, reviews, handoffs and exceptions affect realised value
How to identify workflows with a clear, measurable baseline
Why Human Context matters for employee and agent coordination
What leaders should measure to connect agentic deployment with enterprise ROI
Your free personal takeaway
A short self-assessment of agentic AI impact within your own function or use case, helping you identify where human involvement, rework and coordination affect the value being delivered.
About the speakers
Wolf Magdelinic
Founder and CEO, WORK-SELF
Wolf has more than 20 years of experience building AI-assisted workflow automation and enterprise technology. He founded and exited Overbond AI, led an applied machine learning research lab involving more than 30 PhD researchers, and is the inventor of a granted US AI patent.
Previously at PwC, Deloitte and CIBC, he holds an Electrical Engineering degree from the University of Toronto and an MBA from Ivey Business School. His work has been featured in The Economist, Reuters, Bloomberg, Forbes and the Financial Times.
Wolf leads the development of WORK-SELF’s Human Context Infrastructure and is co-authoring The Human Feedback Loop: Agentic Enterprise Transformation with Prof. John O’Dwyer.
Prof. John O’Dwyer, PhD, MBA, FCA, CMC, ICD.D
Adjunct Professor and Executive-in-Residence, Rotman School of Management, University of Toronto
John has taught in Rotman’s Executive Education programmes since 2002 and brings over 30 years of experience in strategy, leadership and organisational transformation.
As a Partner at Strategic Advisory International, he advises boards and executive teams on strategy execution, operating model design and organisational performance. At WORK-SELF, he contributes expertise in executive alignment, decision rights and governance to support enterprise AI transformation.
John has authored multiple books and is co-authoring The Human Feedback Loop: Agentic Enterprise Transformation with Wolf Magdelinic.
Rotman Faculty Profile | LinkedIn
Who it’s for
CIOs, CAIOs, COOs, CEOs, transformation leaders and executives responsible for AI value realisation, operational performance and enterprise transformation.
About WORK-SELF
WORK-SELF builds Human Context Infrastructure for the agentic enterprise.
Maya Enterprise (a WORK-SELF offering) brings authorised employee, role, task, policy and workflow information into a governed Human Context layer.
Through employee-specific Work Contracts, permissioned Context Capsules and Model Context Protocol (MCP) interoperability, Maya provides approved AI agents with the context required to respect decision authority, human oversight, escalation rules and accountability.
Operating alongside existing enterprise applications and AI systems, Maya helps organisations coordinate human and agent workflows, reduce employee rework and measure the value of completed work.
Part of The Agentic Enterprise, a four-part WORK-SELF webinar series.