From Hype to Muscle
AI has quickly become the most over-hyped—and under-delivering—technology of our era. Gartner’s 2025 survey found that
85% of executives expect AI to deliver significant business value within three years, but fewer than
15% feel their organizations are prepared to adopt it at scale (gartner.com). The gap isn’t enthusiasm—it’s
capability.
Organizations rush to install AI like a software upgrade, forgetting that adoption isn’t about enthusiasm for new tools. It’s about whether the
organization has the muscle to use them repeatedly and sustainably.
Why Capability Beats Pilot Success
MIT’s 2025 research made headlines by finding that
95% of AI pilots fail to deliver measurable ROI (fortune.com). But here’s the nuance: success isn’t defined by whether a pilot works—it’s defined by whether the organization can integrate AI into how it
learns, works, and evolves.
That’s the difference between a project that gets “checked off” and a capability that becomes
organizational muscle.
The Meaningful Change Framework™ Applied to AI
This is why the
Meaningful Change Framework™ embeds capability building into every phase of adoption. Each stage is not just about delivering outcomes—it’s about strengthening the ability to deliver
future outcomes.
- Strategic Framing, Not Just Plans
Leaders must frame AI as a capability-building investment, not a short-term project. Harvard Business Review notes that leaders who articulate AI as “strategic augmentation” rather than “replacement” increase adoption readiness by 40% (hbr.org). - Alignment Methods, Not Just Meetings
Misalignment kills adoption. Our
Layered Alignment™ method ensures leaders create coherence across individuals, teams, functions, and leadership levels. This lowers resistance and accelerates trust. - Design Thinking, Not Just Design Docs
McKinsey’s research shows that organizations using iterative, human-centered design in AI rollouts achieve adoption rates 1.5x higher than those using top-down directives (mckinsey.com). - Adaptive Leadership, Not Just Project Management
Leaders must practice adaptive sensing—listening to feedback loops, surfacing disconnections, and adjusting in-flight. It’s about steering while moving. - Reinvention Capability, Not Just Sustainment
The ultimate goal is repeatable reinvention. A culture that doesn’t punish iteration becomes one that leads disruption, rather than surviving it.
Case Example
One client in the healthcare space adopted AI scheduling to optimize provider availability. The pilot worked, technically—but adoption stalled. Why? Leaders hadn’t built alignment across physicians, administrators, and staff. Each group defined “success” differently: efficiency, equity, or patient experience.
Once we applied the
Meaningful Change Framework™, leaders reframed the work as
capability building:
- Strategic framing connected the AI to patient outcomes, not just cost savings.
- Alignment tools resolved role confusion between administrators and clinical leaders.
- Adaptive leadership ensured leaders tested, sensed, and adjusted weekly.
The result? A 25% improvement in schedule efficiency sustained over 18 months—and a workforce more open to the
next AI innovation.
Why Muscle Matters
Capability building isn’t optional. Gartner predicts that by 2027,
organizations with strong change capability will achieve 60% faster AI adoption cycles than competitors (gartner.com).
That’s the future: the ability to
change repeatedly and well becomes the true competitive advantage.
Reflection Questions
- Are you treating AI like a project—or as organizational muscle?
- Which of the five capability phases is your weakest today?
- What would it look like to invest in that muscle now, before AI scales further?
