Their approach centres on treating agents as part of the operating model — with clear ownership, defined standards, and measurable outcomes.
Start with operating model clarity
Before building agents, Levi and Lachlan start with organisational clarity rather than use cases.
They focus on a small set of foundational questions:
Without this alignment, they consistently see fragmented pilots, unclear ownership, and no clear path to scale.
The bottleneck has shifted
From their perspective, the issue is no longer whether agents work.
Most large enterprises have already run multiple POCs, and real ROI is being achieved. The bottleneck has shifted to how organisations move from proof-of-concept into enterprise rollout and how ROI is tracked over time.
Agents can generate outputs easily. What determines success is whether accuracy standards are clearly defined and whether agents are integrated into real workflows. Without that, pilots may look successful in isolation but fail once exposed to day-to-day operations.
Patterns in organisations seeing sustained value
The organisations now seeing sustained value tend to follow a consistent set of patterns.
They:
In practice, agents often force teams back to first principles — a step many organisations had previously skipped.
Agents as workforce, not software
Levi and Lachlan explicitly frame agents as part of the workforce, but they manage them differently from human roles.
That means defining:
This leads to a combined digital and workforce strategy, where operating models are redesigned around collaboration between humans and agents rather than simply deploying new software.
Platform over point solutions
To address concerns around vendor lock-in and tool sprawl, the approach prioritises a horizontal platform model.
The intent is to:
This reduces fragmentation and shortens the time it takes to move from build to production.
Technology is ready — adoption is the constraint
Levi is clear that, in most cases, the technology is already sufficient. What matters is whether it is actually used.
Their focus is on:
Internally and with clients, adoption is reinforced through visible leadership use and hands-on training where leaders build simple agents themselves.
Where the strongest ROI is showing up
Rather than prioritising surface-level automation, the strongest and most defensible ROI is showing up in back-office and knowledge-heavy functions, including:
These areas tend to have clearer baselines, structured data, and processes that benefit most from standardisation and agent-driven automation.
Governance in production
Beyond formal governance frameworks, the emphasis is on what happens in production.
That includes:
Trust is built through visibility into how agents behave in the real world, not just through policy documents.
Looking ahead
Looking ahead, Levi and Lachlan expect pressure on ROI to intensify, with boards demanding clear returns rather than experimentation. They also expect non-technical teams to become heavy users of agents.
As a result, the performance gap between early adopters and laggards is likely to widen. They also anticipate more agent-to-agent interactions in areas such as procurement, invoicing, and parts of sales and contracting.
Taken together, these practices show how KPMG is turning AI agents from interesting prototypes into a repeatable, enterprise-grade operating model.