Driving Change in the Age of AI: Insights from Michael Ruckman Shared on the Escaping the Drift Podcast

In a recent episode of the Escaping the Drift podcast, host John Gafford sat down with Michael Ruckman, founder and CEO of Senteo, to explore how artificial intelligence is reshaping business—and why organizational transformation must keep pace. Ruckman, an international consultant who has worked in more than 40 countries and speaks four languages, argues that the real challenge of AI isn’t the technology itself, but the speed at which companies can adapt to their customers’ changing needs and behaviors.

Transformation, Innovation, and the Human Factor

Ruckman draws on Geoffrey Moore’s “Law of Diffusion of Innovation” to explain why transformation is so hard. Only 2.5% of people are true innovators, with another 13.5% as early adopters. The rest fall into early majority, late majority, and laggards. People can be innovators in one aspect of life and conservative in another—so leaders can’t simply “find the innovators” and expect them to drive change everywhere.

“Most decisions are made in the primitive or emotional reasoning state, not rationally,” Ruckman explained. “Humans don’t love change—we like things to be predictable and stable. Companies that forget this will struggle when implementing new technologies.”

He notes that traditional change-management models, like John Kotter’s eight steps, still have value. But success often comes from creating an environment where small, unnoticed pilot projects can grow organically—the “old potato” effect, as Ruckman calls it. Small initiatives sprout, successful ones are quietly nurtured until they are undeniable, and resistance fades.

His work in Russia offers an example. Asked to modernize a bank’s CRM system, he discovered 16 different databases and 42 separate user interfaces—hardly a single system at all. Executives balked at the $35 million cost to integrate everything. So Ruckman took a small team of eight people, a $50,000 seed budget, and a free one-year software license. Within three months, the team proved enough value to self-finance the next phase. Over five years, they invested more than $50 million—but were in the red only for that first $50,000. It was a textbook “old potato” project: quiet pilots, quick wins, organic growth.

Leading in the AI Era

Leadership, Ruckman argues, must evolve beyond simple authority. Many so-called leaders are in fact managers who govern by power and policy rather than inspiration. AI-driven transformation requires what he calls a “full range of abilities”—from directive action in a crisis to the ability to mentor and inspire.

“Unfortunately, the majority of people in leadership positions are not leaders,” he said. “They may be good managers, but they’re managing with power and authority. They’re not managing with example, guidance, or mentoring.”

True leaders must be able to shift styles depending on the situation, a concept known as situational leadership. When there is a fire, a leader must be directive—“get the hose, go over there.” But in ordinary times, the same person must coach and inspire. Without that flexibility, organizations can’t adapt to the fast-moving AI landscape.

Ruckman recalls working with a Ukrainian bank where the CEO explicitly told the management team: if Michael says we’re doing something, it’s already approved. “After the first three months,” Ruckman said, “no one questioned it. We were able to drive massive change because the CEO set the tone for trust and empowerment.”

He contrasts this with another project where the CEO tried to outsource the change-leader role to him without providing visible support. “You render me useless in that role,” Ruckman warned. The project stalled—proof that without committed leadership, even the best strategies fail.

Rethinking Management Models

One of the biggest obstacles to AI adoption, Ruckman says, is that most companies still rely on classical management theory from over a century ago. Those principles were designed for industrial-era stability, not for today’s environment where customer preferences can shift in six to twelve months.

He cites the “three fathers of management theory”—from top-down control models to Frederick Taylor’s process-driven efficiency and Henri Fayol’s early (and modest) nod to team spirit. Those ideas worked for assembly lines, but in an era of rapid technological change they create rigidity instead of resilience.

Organizational models must be restructured to support speed and flexibility. Corporate culture must move from hierarchical or purely product-centric models toward networks of teams and relationship-centric structures. Ruckman contrasts Microsoft’s adapted hierarchy—where competition can slow collaboration—with Facebook’s network of teams built for cooperation.

In most companies, he observes, “I see massive duplication of effort. Teams doing the same thing, competing instead of collaborating. Designed for conflict, not cooperation. If you want to go fast, you go alone. If you want to go far, you go together.”

Management in the AI Age

For managers, the AI era demands a new mindset. Traditional metrics—units sold, cost per transaction—are insufficient. Companies must measure the quality of relationships with their customers and employees. That means empowering teams to experiment, fail quickly, and learn.

Ruckman warns against what he calls the “we punish initiative” culture, borrowing a phrase from the old Soviet Union. When employees fear reprisal for mistakes, they avoid suggesting improvements. In an AI-driven economy, where technologies and customer expectations evolve constantly, that fear is deadly.

Management must create an environment where experimentation is not only tolerated but celebrated. Small pilots should be encouraged and quietly nurtured until they demonstrate undeniable value. This is how companies can match the speed of AI innovation without losing the human element.

AI as a Tool for Better Customer Relationships

Too many companies see AI primarily as a cost-cutting tool—replacing call centers or low-level jobs. But that, Ruckman warns, is a mistake.

“Companies are making the same mistake they made with digital transformation,” he said. “They ask, ‘How do I use AI to reduce costs?’ What they should be asking is, ‘How do I use AI to improve customer contacts, experiences, and relationships?’”

He points to examples like Amazon and Meta, where it is now nearly impossible to reach a human being. While AI chatbots may seem efficient, they fail to deliver the empathy customers need when something goes wrong. An empathetic human who can say, “That happened to me once—let me see what I can do,” remains irreplaceable.

Ruckman’s own experience illustrates the danger: an unresolved $561 dispute with ADT despite being a loyal customer. The company’s rigid processes risk losing a long-term relationship over a trivial sum—precisely because performance metrics don’t measure the quality of customer relationships.

John Gafford added another perspective: in hospitality companies like Ritz-Carlton, any employee can spend up to $2,000 to resolve a guest’s problem immediately. This policy reflects an understanding that long-term loyalty outweighs short-term savings. Most businesses, however, have yet to embrace such relationship-centric thinking.

Four Components of Successful Adaptation

In Ruckman’s view, every major challenge in adopting AI or leveraging its benefits comes down to one core problem: the inability to guide change at the speed of shifting customer needs and AI’s rapid development. He identifies four critical components:

1. Organizational Models – Structures for decision-making, resource allocation, and performance measurement must be redesigned for agility.
2. Corporate Culture – Move from authoritarian or product-centric approaches to relationship-centric networks of teams.
3. Leadership Approach – Replace power-based management with leaders who inspire, mentor, and know when to be directive.
4. Approach to Change – Stop over-managing change; instead, create an environment where innovation can emerge organically.

The Human Advantage in an AI World

Ruckman is clear: AI can process data and recognize patterns in seconds—tasks that once took teams of data scientists months. But it cannot yet replicate the emotional reasoning that drives human decision-making. Both Michael and John agreed that the most valuable skill for the next generation will be the ability to connect one-on-one with another human being and make them feel seen and heard.

John even notes a personal example: after two seven-figure deals went sour, his wife had warned him not to trust those partners—purely on instinct. “Now,” he jokes, “nobody gets to work with me unless my wife meets them first.” It’s a reminder that human intuition and empathy still outperform machines when relationships are at stake.

Conclusion

Artificial intelligence is accelerating faster than most companies can adapt. Yet the technology itself is not the greatest challenge. The real test lies in transforming leadership, management, culture, and organizational models to keep pace with rapidly changing customers. As Ruckman puts it, companies must stop treating AI as a simple cost-cutting tool and instead use it to deepen relationships and create genuine value.

In an age when machines can automate tasks in seconds, empathy, trust, and human connection remain the ultimate competitive advantage. Leaders who inspire, managers who nurture experimentation, and organizations that embrace relationship-centric models will be the ones that not only survive the AI revolution—but thrive because of it.