Change Management in the Age of AI

In an era where artificial intelligence promises transformation but often stumbles in execution, Dr. Shannon Gregg’s (President of Cloud Adoption Solutions) session at Innovation Summit 2025 delivered a refreshingly candid—and often humorous—look at what truly drives successful AI adoption: people. 

In her deep-dive on change management, Gregg challenged organizations to look beyond the tech itself and into the psychology, fears, and behaviors of the humans expected to use it.

A few of the standout takeaways:

1. AI Fails Without Human Trust: A staggering 75% of corporate AI initiatives fail—not due to technical issues, but because of poor user adoption. Gregg emphasized that fear and uncertainty are amplified with AI rollouts, making trust-building and communication vital parts of any change strategy.
   
2. Perceived Usefulness & Ease of Use Matter More Than Hype: Drawing from the Technology Acceptance Model, Gregg pointed out that unless users see direct, personal value in a tool—and find it intuitive—they simply won’t use it. Adoption doesn’t come from flashy features; it comes from meaningful utility.
   
3. Quick Wins Drive Cultural Momentum: To combat resistance, organizations should showcase early, tangible results—like faster deal closures or improved lead conversion—as “quick wins.” These act as internal PR moments that generate buy-in and enthusiasm from skeptical users.
   
4. Tailored Learning Is the Game-Changer: With four generations in the workforce and wildly different learning styles, one-size-fits-all training doesn’t cut it. Whether it’s podcasts, interactive videos, or real-time mentoring, change management must meet learners where they are—and keep it interesting.

The Human Side of AI Adoption

Dr. Gregg opened with a dose of reality: despite AI’s promise, it regularly fails in practice. According to research cited from Fortune, 75% of corporate AI initiatives never achieve their intended outcomes. Why? Because adoption is often treated as a technical rollout rather than a behavioral transformation.

Her research, including studies from fields as diverse as healthcare and enterprise IT, revealed that people—not platforms—are the main variable in AI success. Fear of job loss, confusion over purpose, and change fatigue all hinder adoption. These emotions are rarely addressed in implementation plans, but they determine whether users embrace or reject a new tool.

Understanding the Stages of Organizational Readiness

To frame the journey, Gregg introduced three stages of organizational AI maturity:

1. Build: Laying foundational knowledge and testing narrow use cases.
2. Expand: Scaling solutions across departments or functions.
3. Strengthen: Institutionalizing AI through governance, training, and optimization.

Understanding where your team or department falls on this maturity curve is crucial. Applying “strengthen” tactics too early, or “build” tactics too late, can lead to confusion and wasted effort.

Applying the Technology Acceptance Model (TAM)

The Technology Acceptance Model (TAM) was used as a foundational framework. It emphasizes that users adopt technology based on:

• Perceived Usefulness: “What’s in it for me?”
• Perceived Ease of Use: “Can I figure this out without a manual?”
• Intention to Use: “Will I keep coming back to it after the first try?”

These insights highlight why long training videos and dense change documentation often fail. People need intuitive, beneficial tools—and reinforcement over time.

Change Management Requires More Than Training

Gregg emphasized that one-off training sessions won’t cut it. Like joining a gym in January, initial enthusiasm fades unless daily habits are formed. Without repeated exposure, reinforcement, and relevance, employees quickly disengage. Worse, disengaged users influence others, breeding widespread resistance.

To combat this, she advocated for:

• Quick wins that demonstrate immediate value,
• Multi-modal learning (e.g., videos, podcasts, checklists),
• Frequent communication of vision and benefits,
• Championing early adopters as peer influencers.

Research-Backed Insights on AI Adoption

Gregg walked through three of the most recent academic studies on AI-enabled CRM systems. Despite different sectors and methodologies, all pointed to the same conclusion: the success of AI initiatives hinges on people.

One standout finding was that top management support was the strongest predictor of adoption success. Leaders who actively endorse, engage with, and advocate for AI set the tone for the rest of the organization. Conversely, disengaged leaders send a clear (if unintentional) message: “This doesn’t matter.”

Another common thread: the importance of perceived strategic advantage. AI for the sake of AI doesn’t resonate. But when AI tools are tied directly to organizational goals, like improving sales close rates or reducing service response times, users are more likely to engage.

Tailoring Learning for Multi-Generational Teams

A major theme in the talk was the diversity of learning preferences in today’s workforce. With four generations working side by side, the same training approach won’t work for everyone. Some prefer podcasts, others need hands-on tutorials, while many just want a quick how-to video they can revisit as needed.

Gregg encouraged leaders to meet users where they are, offering content in multiple formats and using familiar platforms. Just like the intuitive Whova app used at the conference, AI tools should feel obvious, not overwhelming.

The Diffusion of Innovation: Focus on the Majority

Referencing Everett Rogers’ Diffusion of Innovations theory, Gregg reminded attendees that change is driven not by the loudest voices (the innovators), but by the majority in the middle—the 68% who wait until a solution proves safe and effective.

To win them over, you need:

• Credible early adopters who share success stories,
• Clear communication about purpose and benefits,
• Ongoing reinforcement and support,
• Space to express concerns without judgment.

Gregg even suggested deputizing early adopters to act as peer mentors. These users are often the first to speak up in meetings and the most influential in shaping team sentiment.

Change Is Hard. Irrelevance Is Harder

Dr. Gregg closed with a powerful reminder: while change is uncomfortable, the alternative is stagnation. AI is evolving rapidly, and companies that fail to help their people evolve alongside it will fall behind.

Adoption won’t happen by accident. It requires empathy, structure, creativity, and above all, human-centered design. By grounding change management in proven frameworks and adapting to the emotional reality of AI-driven transformation, organizations can turn disruption into competitive advantage.