Please Note: This is a summary of an article originally posted on Training Industry on September 14, 2026. Click here for the original article and links. The Australian L&D Network has no affiliation with Training Industry.
Durocher argues that many organisations know they need AI but haven’t worked out why. He cites McKinsey data showing most companies use AI somewhere, yet few see enterprise-level financial impact. At Calix, staff built around 700 agents, but only about 40 reached production, and those solved real problems within a workflow. He contrasts “little AI” (incremental task fixes, small returns) with “big AI” (redesigning cross-functional workflows), and says L&D is well placed to enable the latter through four questions:
- Where should AI change the work? Agents deliver value when whole workflows are redesigned, not when bots are bolted onto existing tools. Few people understand workflows end-to-end and the technology. L&D should build that cross-functional capability in leaders.
- Who owns outcomes and accountability? HBR research suggests framing agents as “AI employees” leads managers to take less responsibility and miss more errors. Each workflow needs a named outcome owner who knows what they’re accountable for, what the agent can do autonomously, and when to step in. L&D should develop transformation leaders who can hold that accountability across functions.
- How will we measure real impact? Usage and login figures aren’t enough. He recommends workflow metrics (cycle time, throughput, errors, escalations), role metrics (capacity shifts, cross-functional ownership) and business outcomes (time-recovery value, cost or margin gains). Calix saw a 20% productivity lift from a triage agent. Measurement design is itself a skill L&D should teach.
- How will we build trust and fluency at scale? Calix treats agents as systems with clear guardrails: each has an identity, a narrow scope, and logged, reversible actions. L&D should teach people to supervise agents, know when to question outputs and escalate, and understand their own accountability. Role descriptions and performance expectations need updating too.
Takeaway: There’s no playbook yet, which is where L&D can lead. Focus on workflow-level redesign, accountability, outcome measurement and supervision skills, not tool training.
How do you train people to supervise agents when there’s no playbook yet? What does good oversight look like, and how would you assess it?
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