ESTIMATED READING TIME: 6 MINUTES

WEDNESDAY, JUNE 10 – Kathryn Kaminsky serves as Chief Commercial Officer at global professional services firm PwC, where she leads the commercial side of the business. She brings decades of experience in business transformation, complex accounting, regulatory and strategic business matters, and tech-led innovation. 

At PwC for over thirty years, her biggest passion is serving clients. She has led engagement teams to help her clients meet their financial reporting, regulatory, and transformation needs. 

Most recently, Kathryn served as the Vice Chair and Co-Leader of what was then Trust Solutions, where she brought together the firm’s combined Audit, Sustainability, Digital Assurance and Tax Reporting capabilities to assist clients in building trust with their stakeholders. In addition, she is a certified public accountant and a member of the American Institute of Certified Public Accountants and the Southern Methodist University Cox Executive Board.

 

What’s the biggest mistake people are making with AI today?

Waiting for certainty about the technology before acting. I’m not someone who only moves forward when the conditions are perfect, and that instinct has served me well. The organizations moving fast aren't the ones with complete clarity, but conviction. They make informed bets, build around assumptions, and adjust as they learn. 

AI is a capability you build over time, and the cost of delay is real. Organizations that postpone its adoption may find it harder to keep pace as capabilities evolve.

 

Mistakes are part of adopting anything new, yet some leaders are quiet on where AI is falling short inside their own organizations. What do we lose when we don't talk about what isn't working?

If we don’t acknowledge when AI falls short, we may not only lose speed, but credibility within our own teams. When leaders only share the wins, others within the organization often mirror that behavior and hide failures. But failure is data. Some of my most important lessons have come from things that didn't go as expected.

Companies that want to gain true insight into the process should create space for honest conversations about what isn't working. I believe in learning from failure, where someone can admit, “This didn't go as planned." Transparency from the top helps set that tone, and when leaders model it, others will likely follow. 

 

According to BetterUp, 40% of employees have received AI workslop. As the leader of PwC’s commercial business, how are you training your teams to lead in this era and use it well, not just for speed?

Speed is a byproduct, not the goal. The world has changed, and at PwC, we're evolving with it. What we're really building is judgment and a different kind of talent model. That means bringing in engineers, data scientists, and new capabilities alongside the expertise we've always had. 

 

Throughout all of this, one thought remains prevalent: the skills that matter most are the deeply human ones like empathy, critical thinking, and the ability to challenge results. You have to examine what AI produces and ask the hard questions. A client we work with put it simply: "You can't blame the AI." And that’s because you still need a human lens. Leading in this era is about pushing back, engaging in dialogue, and understanding that the review is as important as the output. 

 

Every company says they're "investing in AI." Few can articulate what winning actually looks like. How are you defining it at PwC, and what separates the companies pulling ahead from the ones falling behind?

The real issue is not the return on investment of AI, but doing nothing. The companies falling behind are still waiting for a clean business case before they move, but delaying is the real risk. The organizations pulling ahead are asking more incisive questions about what success looks like. Is AI making our work more efficient, strategic, and insightful? Is it more embedded in how the business runs? What is it actually changing? At PwC, that's the bar.

 

What’s something that AI has enabled your team to do that would have been impossible just 5 years ago?

Five years ago, understanding someone's full context, their business, their competitive position, their regulatory environment, what's keeping them up at night, required weeks of research. Now, you can walk in with a level of insight that used to take a team a month to build. It’s a genuine equalizer. It means that someone who is earlier in their career and without the experience of decades of pattern recognition can now show up with a deeper depth of preparation. 

AI helps get you to the table ready, but what hasn't changed is that humans still have to show up and deliver. Preparation opens the door, but judgment and relationships are what move things forward.

 

Tell us about a creative way someone is using AI at PwC that surprised you?

For me, it’s not any single use case, but where the creativity is coming from. People that are using AI aren’t just the technologists or innovation teams. It’s people across the firm who noticed a bottleneck in their own work and figured out how to remove it. I've seen people completely reimagine how they structure client deliverables, run internal reviews, and synthesize complex data before a critical meeting. They didn't wait for a top-down mandate, they experimented. It’s a culture shift where curiosity is the default, not the exception.

 

Are we overestimating what AI can do or underestimating what it will change?

Both, simultaneously. I started my career before we had computers or Excel spreadsheets. At the time, people were convinced that technology would eliminate entire professions, but it didn't. It did, however, change what the work looked like while also expanding our capabilities.

What I've learned from observing multiple waves of technological change is that we almost always overestimate the short-term disruption and underestimate the long-term structural shift. Unlike previous tech cycles where a new tool primarily impacted one business function, AI is touching nearly every corner and role of the organization at once: the Chief Executive Officer, the Chief Human Resources Officer, and the back office. The leaders who build for it now have the real advantage.

 

Looking at the next 12 months, what's one shift leaders should be preparing for today?

Clarity on who owns the transformation. In the past, it was the responsibility of the Chief Information Officer, but AI isn't a technology decision anymore. It's a business, workforce, and growth decision. Everyone is implicated, so the CEO's job right now is to integrate while also taking accountability across the C-suite. The leaders preparing well are creating decision-making models that can move quickly, stay aligned, and keep their people with them through the change.