Originally aired February 25, 2026 on Extropy On AIr.
Digital transformations fail when leaders treat them as projects instead of system design. Entropy, the natural drift toward disorder, never stops, so organizations need a counterforce: extropy, or intentional order. In this episode, Kevin Zirkle and Mike Jasper explain why common transformation language falls short, why scale breeds complexity, and how leaders can build coherence that compounds over time.
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Key takeaways
- Left alone, organizations decay. Leaders are architects of order, not just operators.
- Words like transformation, automation and optimization focus on outputs, not structure, and make change feel episodic.
- Entropy doesn’t care about your go-live date. Without sustainment, organizations end up reinvesting in transformation every few years.
- AI isn’t neutral. It amplifies whatever structure already exists, good or bad.
- Measure coherence, not deployment, and keep applying energy to maintain it. That is how leadership works.
What do entropy and extropy mean for organizations?
Entropy comes from thermodynamics. It describes the natural tendency of systems to move toward disorder unless energy is applied to maintain their structure. Mike, who started as a science major before moving into business and IT, says organizations behave the same way. Strategies shift, processes diverge, metrics multiply and technology stacks expand. If no one is intentionally reinforcing coherence, fragmentation becomes the default.
Extropy is the counterforce: intentional order and design coherence within all that complexity. Kevin’s takeaway is that this reframes leadership. If entropy is natural decay, then leaders are architects of order, and transformation is about continuously resisting entropy, not just implementing change.
Why does traditional transformation language fall short?
Mike points out that the usual words are output focused, not structural. When an executive says digital transformation, nine times out of ten they mean a system implementation. Automation usually means labor efficiency, and optimization usually means cost compression.
That project mindset makes change episodic: select a tool, implement it, stabilize it and declare victory at go-live. But entropy is constant. Organizations end up reinvesting in transformation every few years, not because the tools failed, but because no one sustained the changes and people slipped back into old ways.
How does AI affect organizational entropy?
Complexity doesn’t grow in a straight line. Global operations, acquisitions and hybrid workforces all compound it, and layering AI on top of legacy systems adds more. Mike’s view is that AI amplifies whatever structure already exists. Weak data governance gives you bad results, and a fragmented process architecture gives you fragmented AI. Clean data and well-designed processes are not a one-time fix. They need constant attention.
Why does scale create disorder instead of advantage?
Growth multiplies interaction points: system to system, person to person, and system to person. Every new system, like a contract management tool that feeds finance, adds data points that need realignment. If growth is treated as financial consolidation rather than a push for coherence, entropy creeps in.
That is why some companies feel slower at $5 billion in revenue than they did at $500 million. They didn’t lose talent. Complexity overwhelmed coherence. Startups feel naturally coherent because decision paths are short and accountability is clear. Mature enterprises have to engineer that on purpose.
What does an extropic organization look like?
An extropic organization strengthens relationships over time: between systems, between people, and between people and technology. It improves how tasks connect, not just the tasks themselves. Better data leads to better decisions, better decisions simplify processes, simpler processes make outcomes more predictable, and predictability lets leaders be more strategic.
Kevin calls this coherence velocity: how fast an organization can absorb change without destabilizing itself. In a high entropy organization, every change ripples into fire drills, exceptions, workarounds and spreadsheets. In an extropic one, change fits in smoothly because there is an architecture built to absorb it.
How can CFOs and transformation leaders apply this lens?
- Redefine success. Stop treating deployment as the finish line. Ask whether the initiative reduced friction, clarified accountability and improved system integrity.
- Elevate architectural ownership. Someone needs to own the system design beyond individual projects and beyond go-live, not just a power user or admin.
- Add coherence reviews to governance. Evaluate every new initiative for its impact on the organization and its processes, not just ROI.
- Build diagnostic maturity. Entropy leaves signals before failure, like shadow reporting, conflicting KPIs, spikes in manual exceptions and reliance on tribal knowledge.
The good news, as Mike puts it, is that if failure is predictable, prevention is possible. Set success criteria at the start, measure against them, and plan to come back and keep optimizing instead of calling it done. Kevin sums it up: define decision architecture before workflows, governance before automation, and accountability before analytics.
In their words
Entropy doesn’t really care about your Go Live date, does it?
Kevin Zirkle, Extropy Advisors
Leaders need to continuously apply energy to maintain that coherence. And that’s not a flaw of the process. That’s how leadership works.
Mike Jasper, Extropy Advisors
About the speakers
Kevin Zirkle is Director of Business Development at Extropy Advisors, where he works across Extropy’s partner ecosystem, matching organizations with the right technology and the right people to move transformation from the whiteboard into production.
Mike Jasper is VP of Finance Transformation at Extropy Advisors, where he leads digital transformation and client success, working hands-on with clients to set success criteria, optimize their people, process and technology, and measure the results.
FAQ
What is the difference between entropy and extropy in business?
Entropy is the natural tendency of an organization to drift toward disorder as strategies shift, processes diverge, metrics multiply and technology stacks grow. Extropy is the counterforce: intentional order and design coherence that strengthen the connections between systems, people and technology over time.
Why do digital transformations fail even when the tools work?
Transformation is often treated as a one-time project that ends at go-live. Entropy is constant, so without sustained ownership and reinforcement, people revert to old ways, processes drift and organizations end up reinvesting in transformation every few years. The tools did not fail. The structural coherence was never maintained.
How can a CFO apply the entropy and extropy lens?
Redefine success around coherence, not deployment: did the initiative reduce friction, clarify accountability and improve system integrity? Give someone ownership of system design beyond individual projects, add coherence reviews to governance alongside ROI, and build diagnostic maturity to catch warning signs like shadow reporting and conflicting KPIs early.
Keep exploring
- More episodes of Extropy On AIr
- Previous in the entropy series: The Hidden Cost of Organizational Entropy
- Next in the entropy series: The Digital Transformation Myth: Technology Comes Last
- Next episode with show notes: Execution Beats Experimentation: Agentic AI in AP
- Why Extropy
Ready to design for coherence instead of chasing the next tool? Book a discovery call with our team.
