Is it time to replace your Org Chart with a Work Chart in the age of AI

Two people standing in front of a whiteboard discussing strategy

The Foundation: Purpose, People, Performance

We have always maintained that one starts with Purpose, ends with Performance and in the middle ask who and how – People – we get things done.

In our rapidly evolving AI era, we must also integrate Technology into this framework.

While there will be temptation to either overestimate or underestimate AI’s role in the near future, a considered, human-centric approach will help us limit missteps, risks, and failures.

Rethinking Labour in the Intelligence Age

Historic perspectives on labor must now be challenged. We need to move beyond reducing human contribution to:

  • Hours worked
  • Physical presence
  • Quantitative outputs

These archaic metrics, developed for the industrial revolution, no longer suit the information and intelligence age.

Contribution to purpose—what we call performance—may no longer require employees to be exclusive, full-time, or always present. Perhaps even the term “employee” may soon become contentious.

Similarly, the rigorous responsibilities placed on employers, along with their associated liabilities, may need review. Governments, labor laws, unions, and current taxation structures must all adapt to this transformative environment.

Change must happen simultaneously across all three areas: employees, employers, and statutory frameworks.

From Organisation Charts to Work Charts

We have long held that viewing organisations through the lens of teams is optimal. But how do we navigate the new concept of AI agents as human replacements? How do we move from traditional Organisation Charts to Work Charts?

The Traditional Challenge

Setting aside debates about legacy hierarchical issues and authority biases in traditional organisation charts, graphically accounting for people and teams remains useful.

The AI-Driven Alternative

AI advocates suggest replacing traditional charts with an outcome-driven model that maps:

  • Workflow expertise
  • Collaboration patterns
  • How work gets done (rather than who reports to whom)

In this model, teams—composed of both human and AI agents—form and dissolve around critical projects and evolving priorities.

Drawing the Line: Human vs. AI

While we support this perspective, a hard line must be drawn on the immutable difference between human beings and AI agents for what seem obvious reasons, despite the increasing temptation to blur this distinction.

The intrinsic sanctity of human beings includes their:

  • Unique strengths (their imago dei)
  • Sense of and need for purpose
  • Desire to contribute and belong
  • Critical need to leave a legacy

These qualities cannot compare to anything artificially created, regardless of how efficient or effective.

The Benefits and Risks

Potential Gains

Agility, fluidity, scale, and leverage can all be gained from Work Chart approaches, as evidenced by Microsoft’s “Frontier Firm” ideology—as long as we remain firmly grounded.

Real-world example: Shopify announced in April 2025 that no new hires would be approved unless AI demonstrably cannot do the job, signaling a future where integrating AI into every workflow becomes the default.

Critical Missteps

However, missteps are equally important to consider. Today’s CBA U-turn on AI job cuts illustrates this—they reversed their decision to cut 45 call centre jobs after realising it was premature and ill-conceived.

Our Recommendation

While we advocate that organisations commence reimagining their:

Purpose – Staying relevant in this rapidly changing environment

Performance – Maximising efficiency, effectiveness, scale, intelligence, and expertise through technology

People – They must hold fast to what matters most: the human being.


Summary Table: Org Chart vs. Work Chart (with AI)

Dimension Org Chart (Traditional) Work Chart (AI-enhanced)
Structure Hierarchical Dynamic, cross-functional
Reporting Relationships Static lines of authority Temporary teams, formed by workflow
AI Integration Minimal (automation only) Embedded AI as collaborators
Adaptability Low (slow updates) High (real-time, scenario-based)
Decision-Making Centralised Distributed, both human and AI-driven
Visibility Titles, roles, departments Actual work, projects, skills, outcomes
Example Software ChartHop, Workable, Pingboard Functionly, Agentnoon, Peoplebox

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