Cross-Functional Collaboration: The Missing Piece in AI Execution
You can have the best AI models in the world , but without cross-functional collaboration, they won’t scale.
AI success doesn’t hinge on technical horsepower alone. It hinges on your organization’s ability to get product managers, data scientists, engineers, and operators working together toward a shared outcome.
Yet, in most mid-to-large enterprises, these functions operate in parallel lanes, rarely overlapping in a meaningful way. And that’s exactly why so many AI projects stall after the pilot.
A recent HBR article noted that only 30% of AI pilots successfully transition into production, and the primary blocker is not data , it’s team alignment.
Let’s fix that.
Beyond Pilots: The Framework for Scaling AI Company-Wide
AI pilots are everywhere, and that’s the problem.
In 2024 alone, over 70% of Fortune 1000 companies ran at least one AI pilot. But fewer than 25% of those pilots scaled across the enterprise. Most stall. Why? Because companies treat pilots as proofs of concept, not as stepping stones to capability.
What Boards Need to Know About AI Governance
In 2025, boards face a new type of fiduciary duty: understanding and governing artificial intelligence.
AI is no longer confined to R&D or innovation teams. It’s shaping decisions in operations, finance, marketing, HR, and customer experience. And as adoption rises, so do questions of risk, transparency, and accountability, areas where board oversight must mature.
Designing an Organization That Is Built for AI Execution
AI isn’t just a software upgrade. It’s an operating model reset.
Many organizations believe they can “layer” AI on top of existing structures and still achieve exponential outcomes. But AI isn’t wallpaper—it’s architecture. And if your architecture is misaligned, you’ll stall out quickly.
The Role of AI in Shaping the Future of Customer Experience
You can have the best AI models in the world , but without cross-functional collaboration, they won’t scale.
AI success doesn’t hinge on technical horsepower alone. It hinges on your organization’s ability to get product managers, data scientists, engineers, and operators working together toward a shared outcome.
Yet, in most mid-to-large enterprises, these functions operate in parallel lanes, rarely overlapping in a meaningful way. And that’s exactly why so many AI projects stall after the pilot.
A recent HBR article noted that only 30% of AI pilots successfully transition into production, and the primary blocker is not data , it’s team alignment.
Let’s fix that.
The AI Adoption Roadmap: How to Structure Your Org for Long-Term Success
AI is no longer a future initiative—it’s a present imperative. But most companies still approach it with the wrong frame: as a tech deployment, rather than an organizational transformation.
AI and Organizational Agility: Enhancing Adaptability in a Rapidly Changing Market
There’s a major misunderstanding among executives about what it means to “do more with AI.”
The conversation too often focuses on automation, cost reduction, or headcount efficiency. But the true value of AI isn’t subtraction , it’s amplification.
AI-enhanced talent , humans empowered with AI capabilities , is the growth engine most CEOs overlook.
According to a recent study by Chicago Booth, companies that invest in AI-assisted work environments see productivity growth of up to 35%, especially in knowledge-intensive roles. Yet, fewer than 40% of companies are redesigning jobs to leverage this.
Let’s break down what AI-enhanced talent looks like , and how to build it.
How to Align Your Leadership Team Around an AI-Ready Mindset
In most companies today, AI isn’t failing because of the technology—it’s failing because leadership isn’t aligned on what it means, why it matters, and how fast to move.
If you’re seeing inconsistent priorities, stalled pilots, or fragmented messaging across departments, you’re not dealing with an AI issue. You’re dealing with a leadership mindset gap.
AI for Talent Management: How to Optimize Hiring and Employee Development
You can have the best AI models in the world , but without cross-functional collaboration, they won’t scale.
AI success doesn’t hinge on technical horsepower alone. It hinges on your organization’s ability to get product managers, data scientists, engineers, and operators working together toward a shared outcome.
Yet, in most mid-to-large enterprises, these functions operate in parallel lanes, rarely overlapping in a meaningful way. And that’s exactly why so many AI projects stall after the pilot.
A recent HBR article noted that only 30% of AI pilots successfully transition into production, and the primary blocker is not data , it’s team alignment.
Let’s fix that.
Why AI Starts with the CEO: Crafting a Vision That Inspires Cultural Change
Every AI transformation starts with a single point of leverage—the CEO’s mindset.
Too often, companies treat AI as a technology initiative. But in every successful transformation I’ve advised, the shift began with a clear, bold CEO vision. Not a technical roadmap, but a cultural one.
Data-Driven Innovation: Using AI to Create New Business Opportunities
There’s a major misunderstanding among executives about what it means to “do more with AI.”
The conversation too often focuses on automation, cost reduction, or headcount efficiency. But the true value of AI isn’t subtraction , it’s amplification.
AI-enhanced talent , humans empowered with AI capabilities , is the growth engine most CEOs overlook.
According to a recent study by Chicago Booth, companies that invest in AI-assisted work environments see productivity growth of up to 35%, especially in knowledge-intensive roles. Yet, fewer than 40% of companies are redesigning jobs to leverage this.
Let’s break down what AI-enhanced talent looks like , and how to build it.
From Resistance to Readiness: Leading Culture Change in the AI Era
When leaders encounter pushback from teams during AI adoption, the reflex is often to double down on tools, training, or consultants. But true AI transformation doesn’t start in IT. It starts in culture, where resistance is not just expected, it’s essential.
AI-First Organizations: Building the Culture to Embrace Innovation
You can have the best AI models in the world , but without cross-functional collaboration, they won’t scale.
AI success doesn’t hinge on technical horsepower alone. It hinges on your organization’s ability to get product managers, data scientists, engineers, and operators working together toward a shared outcome.
Yet, in most mid-to-large enterprises, these functions operate in parallel lanes, rarely overlapping in a meaningful way. And that’s exactly why so many AI projects stall after the pilot.
A recent HBR article noted that only 30% of AI pilots successfully transition into production, and the primary blocker is not data , it’s team alignment.
Let’s fix that.
5 Signs Your Organization Is Culturally Ready for AI
5 Signs Your Organization Is Culturally Ready for AI
Scaling AI in Customer Service: Enhancing Efficiency and Satisfaction
You can have the best AI models in the world , but without cross-functional collaboration, they won’t scale.
AI success doesn’t hinge on technical horsepower alone. It hinges on your organization’s ability to get product managers, data scientists, engineers, and operators working together toward a shared outcome.
Yet, in most mid-to-large enterprises, these functions operate in parallel lanes, rarely overlapping in a meaningful way. And that’s exactly why so many AI projects stall after the pilot.
A recent HBR article noted that only 30% of AI pilots successfully transition into production, and the primary blocker is not data , it’s team alignment.
Let’s fix that.
From Data to Insights: How AI Turns Raw Data Into Actionable Knowledge
You can have the best AI models in the world , but without cross-functional collaboration, they won’t scale.
AI success doesn’t hinge on technical horsepower alone. It hinges on your organization’s ability to get product managers, data scientists, engineers, and operators working together toward a shared outcome.
Yet, in most mid-to-large enterprises, these functions operate in parallel lanes, rarely overlapping in a meaningful way. And that’s exactly why so many AI projects stall after the pilot.
A recent HBR article noted that only 30% of AI pilots successfully transition into production, and the primary blocker is not data , it’s team alignment.
Let’s fix that.
AI-Powered Decision-Making: How to Enhance Business Intelligence
You can have the best AI models in the world , but without cross-functional collaboration, they won’t scale.
AI success doesn’t hinge on technical horsepower alone. It hinges on your organization’s ability to get product managers, data scientists, engineers, and operators working together toward a shared outcome.
Yet, in most mid-to-large enterprises, these functions operate in parallel lanes, rarely overlapping in a meaningful way. And that’s exactly why so many AI projects stall after the pilot.
A recent HBR article noted that only 30% of AI pilots successfully transition into production, and the primary blocker is not data , it’s team alignment.
Let’s fix that.
Embracing AI in Marketing: How to Drive Revenue Growth with AI
You can have the best AI models in the world , but without cross-functional collaboration, they won’t scale.
AI success doesn’t hinge on technical horsepower alone. It hinges on your organization’s ability to get product managers, data scientists, engineers, and operators working together toward a shared outcome.
Yet, in most mid-to-large enterprises, these functions operate in parallel lanes, rarely overlapping in a meaningful way. And that’s exactly why so many AI projects stall after the pilot.
A recent HBR article noted that only 30% of AI pilots successfully transition into production, and the primary blocker is not data , it’s team alignment.
Let’s fix that.
Scaling AI: A CEO’s Guide to Growing AI Across the Organization
You can have the best AI models in the world , but without cross-functional collaboration, they won’t scale.
AI success doesn’t hinge on technical horsepower alone. It hinges on your organization’s ability to get product managers, data scientists, engineers, and operators working together toward a shared outcome.
Yet, in most mid-to-large enterprises, these functions operate in parallel lanes, rarely overlapping in a meaningful way. And that’s exactly why so many AI projects stall after the pilot.
A recent HBR article noted that only 30% of AI pilots successfully transition into production, and the primary blocker is not data , it’s team alignment.
Let’s fix that.
AI Vision for CEOs: Crafting a Roadmap for Transformative Leadership
You can have the best AI models in the world , but without cross-functional collaboration, they won’t scale.
AI success doesn’t hinge on technical horsepower alone. It hinges on your organization’s ability to get product managers, data scientists, engineers, and operators working together toward a shared outcome.
Yet, in most mid-to-large enterprises, these functions operate in parallel lanes, rarely overlapping in a meaningful way. And that’s exactly why so many AI projects stall after the pilot.
A recent HBR article noted that only 30% of AI pilots successfully transition into production, and the primary blocker is not data , it’s team alignment.
Let’s fix that.
AI-Enhanced Customer Retention: Using AI to Build Long-Lasting Relationships
You can have the best AI models in the world , but without cross-functional collaboration, they won’t scale.
AI success doesn’t hinge on technical horsepower alone. It hinges on your organization’s ability to get product managers, data scientists, engineers, and operators working together toward a shared outcome.
Yet, in most mid-to-large enterprises, these functions operate in parallel lanes, rarely overlapping in a meaningful way. And that’s exactly why so many AI projects stall after the pilot.
A recent HBR article noted that only 30% of AI pilots successfully transition into production, and the primary blocker is not data , it’s team alignment.
Let’s fix that.
Building AI-Ready Teams: Strategies to Empower Your Workforce
You can have the best AI models in the world , but without cross-functional collaboration, they won’t scale.
AI success doesn’t hinge on technical horsepower alone. It hinges on your organization’s ability to get product managers, data scientists, engineers, and operators working together toward a shared outcome.
Yet, in most mid-to-large enterprises, these functions operate in parallel lanes, rarely overlapping in a meaningful way. And that’s exactly why so many AI projects stall after the pilot.
A recent HBR article noted that only 30% of AI pilots successfully transition into production, and the primary blocker is not data , it’s team alignment.
Let’s fix that.
Leading with AI: How to Inspire Innovation Through AI-Driven Leadership
You can have the best AI models in the world , but without cross-functional collaboration, they won’t scale.
AI success doesn’t hinge on technical horsepower alone. It hinges on your organization’s ability to get product managers, data scientists, engineers, and operators working together toward a shared outcome.
Yet, in most mid-to-large enterprises, these functions operate in parallel lanes, rarely overlapping in a meaningful way. And that’s exactly why so many AI projects stall after the pilot.
A recent HBR article noted that only 30% of AI pilots successfully transition into production, and the primary blocker is not data , it’s team alignment.
Let’s fix that.
Aligning Leadership for AI? Start with the Hard Conversations
You can have the best AI models in the world , but without cross-functional collaboration, they won’t scale.
AI success doesn’t hinge on technical horsepower alone. It hinges on your organization’s ability to get product managers, data scientists, engineers, and operators working together toward a shared outcome.
Yet, in most mid-to-large enterprises, these functions operate in parallel lanes, rarely overlapping in a meaningful way. And that’s exactly why so many AI projects stall after the pilot.
A recent HBR article noted that only 30% of AI pilots successfully transition into production, and the primary blocker is not data , it’s team alignment.
Let’s fix that.
Is Your Org AI-Ready, or Just AI-Hoping?
You can have the best AI models in the world , but without cross-functional collaboration, they won’t scale.
AI success doesn’t hinge on technical horsepower alone. It hinges on your organization’s ability to get product managers, data scientists, engineers, and operators working together toward a shared outcome.
Yet, in most mid-to-large enterprises, these functions operate in parallel lanes, rarely overlapping in a meaningful way. And that’s exactly why so many AI projects stall after the pilot.
A recent HBR article noted that only 30% of AI pilots successfully transition into production, and the primary blocker is not data , it’s team alignment.
Let’s fix that.
Building an AI-First Culture That Actually Sticks
You can have the best AI models in the world , but without cross-functional collaboration, they won’t scale.
AI success doesn’t hinge on technical horsepower alone. It hinges on your organization’s ability to get product managers, data scientists, engineers, and operators working together toward a shared outcome.
Yet, in most mid-to-large enterprises, these functions operate in parallel lanes, rarely overlapping in a meaningful way. And that’s exactly why so many AI projects stall after the pilot.
A recent HBR article noted that only 30% of AI pilots successfully transition into production, and the primary blocker is not data , it’s team alignment.
Let’s fix that.
Culture Eats AI for Breakfast, Unless You Lead It
You can have the best AI models in the world , but without cross-functional collaboration, they won’t scale.
AI success doesn’t hinge on technical horsepower alone. It hinges on your organization’s ability to get product managers, data scientists, engineers, and operators working together toward a shared outcome.
Yet, in most mid-to-large enterprises, these functions operate in parallel lanes, rarely overlapping in a meaningful way. And that’s exactly why so many AI projects stall after the pilot.
A recent HBR article noted that only 30% of AI pilots successfully transition into production, and the primary blocker is not data , it’s team alignment.
Let’s fix that.
The Executive Guide to Structuring Your AI Transformation
AI pilots are everywhere, and that’s the problem.
In 2024 alone, over 70% of Fortune 1000 companies ran at least one AI pilot. But fewer than 25% of those pilots scaled across the enterprise. Most stall. Why? Because companies treat pilots as proofs of concept, not as stepping stones to capability.
Executive Coaching Offered for Current Vps, Svps, Cxos, & Founders
A 2013 survey conducted by Stanford’s Graduate School of Business found that nearly two-thirds of CEOs and almost half of senior executives do not
Build an AI-First Culture That Fuels Innovation and Execution
You think you are a leader. Or you would like to be one. Most people want to be leaders. A simple search on LinkedIn will show you the number of people
Why Board Directors And CEOs Need An AI And Data Expert To Accelerate Growth and Digital Transformation
Did you know that a staggering 70%[1] of digital transformation efforts fail, even though companies have invested a combined total of more
AI CULTURE TRANSFORMATION
Have you ever been in a situation where no matter how hard you try you do not get to own your career? You try your best but are not sure what is keeping
What Can CEOs Learn from Bob Iger’s Return To Disney
The Walt Disney Co. board’s decision to bring back Bob Iger as a CEO which stunned media observers and Hollywood Sunday evening, came
2023 Business Planning For CEOs
One of the most important parts of CEO coaching is the questions I ask my clients. Sometimes, it is not the answers but the questions we ask that get us to have the right mindset.
4 Tips for Running Your Board Meeting Effectively
Board members and executives never want to leave a meeting feeling like they wasted their time because they didn’t accomplish anything or contribute anything.
How Do CEOs Create a Compelling Vision?
The first responsibility of a CEO, in my opinion, is to own the vision. I use the term “vision” to refer to the company’s mission, vision, values, and overall strategy.
How To Build a Time Audit Report For Your Calendar In Less Five Minutes
Time is a precious commodity, especially for busy CEOs who have multiple responsibilities that require their attention.