Earl Fitzhugh

I recently joined Alex Shevelenko, CEO of RELAYTO AI, on the podcast to discuss how leaders can navigate the intersection of AI and shifting business landscapes. We discussed the challenges CEOs face with two jobs: running the current business model and designing the next one. If you aren’t auditing your business model with the same rigor as your financial statements, you’re at risk. And the biggest hurdle to innovation isn't technical; it's a culture that fears failure. To succeed with AI, organizations must move away from "gut feelings" and toward a structured, mathematical process of experimentation. Listen to the full episode here: https://lnkd.in/gBfTNRY3 #AI #BusinessModels #Innovation The Wharton School #Amazon #Leadership #FutureOfWork

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What does it take to truly lead transformation with AI? It starts with an AI Executive Voice. I recently had the privilege of joining a virtual talk show with WLDA to explore this topic: "AI Executive Voice: Leading Transformation Through Influence and Insight." Our discussion focused on four key pillars for modern leadership: - Establishing AI as a Strategic Vision - Ensuring Responsible AI Innovation - Defining the necessary Executive Voice - Employing practical Frameworks/Models to Drive Impact This conversation emphasized that leadership today isn't just about deploying technology; it's about influence and insight—guiding the organization to view AI not merely as a tool, but as a strategic asset. Thank you to Priya Reddy, a Board Advisor and Professor at Carnegie Mellon University for hosting, and to the executives and community at World Leaders in Data and AI [WLDA] for their great interest and engaging questions. #AILeadership #DigitalStrategy #Influence #ExecutiveVoice #WLDA

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Big news: we're joining forces with the data science experts at MIT to launch a predictive Business Spend Index, utilizing our $8 trillion in spend data to help business leaders bolster resiliency, optimize savings, and drive growth.   https://bit.ly/4gS7pgW

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It was a pleasure to join Sridhar Ramaswamy of Snowflake and Jake Loosararian of Gecko Robotics, along with moderator Carolin Roth, for the CNBC CEO Council Leadership Insights panel in Davos. We had a fascinating discussion on whether 2026 will be the year companies see real returns on their AI investments. The hype around AI is rapidly giving way to a focus on tangible results. The question is no longer if AI can deliver value, but how to achieve it consistently. While the potential is immense, I believe successful AI implementation hinges on a few critical factors: • 𝗦𝘁𝗿𝗮𝘁𝗲𝗴𝗶𝗰 𝗙𝗼𝘂𝗻𝗱𝗮𝘁𝗶𝗼𝗻: True ROI from AI doesn't come from isolated experiments. It requires a clear strategy that aligns technology with core business objectives. You must start with the problem you want to solve, not with the technology. • 𝗗𝗮𝘁𝗮 𝗜𝗻𝘁𝗲𝗴𝗿𝗶𝘁𝘆: The quality of your AI is dictated by the quality of your data. Without clean, well-structured, and relevant data, even the most advanced models will fail to deliver meaningful outcomes. • 𝗠𝗲𝗮𝘀𝘂𝗿𝗮𝗯𝗹𝗲 𝗜𝗺𝗽𝗮𝗰𝘁: To justify investment, we must move beyond vanity metrics. Success needs to be defined by measurable improvements in efficiency, revenue growth, customer satisfaction, or other key performance indicators. The conversation is shifting from potential to proof. Organizations that ground their AI initiatives in solid data, strategic planning, and a relentless focus on measurable business impact will be the ones that realize a true return in 2026 and beyond. You can watch the full panel discussion here: https://cnb.cx/49UZsWB #WEF26 #AI #DigitalTransformation #Leadership

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Remote energy sites often face long lead times and high risk when critical parts take months to arrive. In this blog post, Slalom experts Josh Hirshman and Karn Gupta explain how additive manufacturing (AM) at the edge is changing the equation—bringing 3D printing closer to operations, reducing reliance on global logistics, and strengthening supply-chain resilience. Read how resource-industry leaders are using AM to stay ahead: https://lnkd.in/eWwgH-dh #ImWithSlalom

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🛑 I didn’t expect this answer to stop the room at Davos. With the Super Bowl coming up, it’s hard not to notice how much leadership looks like team sport. At Davos, I was on a panel about what makes boards actually work at scale. Having served on public company boards, including Altair (NASDAQ: ALTR), recently acquired by Siemens for nearly $11B, the discussion felt especially relevant. Then someone asked how we scale AI and blockchain responsibly. 🎤 My answer: If your system can’t survive different perspectives, it probably can’t survive scale. And today, one of the most consistently missing perspectives in those rooms is women. Read more in Forbes https://lnkd.in/dan4QrE3 Dr Anino Emuwa from 100 Davos Women said, “Leadership in the age of AI is about shaping how that power is exercised responsibly. Women must also lead in these spaces, because inclusive leadership drives better innovation, stronger economies, and fairer outcomes for everyone.” Why that matters: 1. Scaling AI and blockchain is a governance challenge, not just a technical one. Davos is where decisions about global AI and blockchain infrastructure are shaped. When only a narrow set of perspectives is present, blind spots compound as systems grow. Check out what Ayumi Moore Aoki has to say about AI and Inclusion! 2. Homogeneous leadership creates fragile systems. Data shows that incomplete leadership increases economic risk, from regulatory exposure to value leakage. Strategies that can’t withstand challenge won’t withstand real-world complexity. Check out @joinmiaworld Melissa Tony Stires quote ! 3. The leadership required for resilient AI already exists. Women are already governing, designing, and deploying AI and blockchain systems at scale. The issue isn’t readiness. It’s whether institutions formally empower that leadership where accountability is set. Amii Barnard-Bahn, JD, PCC makes some great points around this area. Check out the full article in Forbes The Female Quotient WOMEN IN TECH ® Global Unstoppable Women of Web3 World Leaders in Data and AI [WLDA] WORLD WOMAN FOUNDATION

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Grateful for the candid, forward-looking discussions with the Microsoft AI and Agentic leadership team in Seattle ... and for the exceptional AI talent across Alvarez & Marsal. Conversations reinforced again in Davos that made one thing clear: AI’s next chapter is about scale, trust, and outcomes—not experimentation. What’s changing fast: • AI is moving from tools to agentic systems Not copilots—but systems that reason, act, and run real workflows. The winners will be those who govern, observe, and trust agents to operate at enterprise scale. • Centers of Excellence must enable, not constrain. COEs can’t become control towers. The goal is safe playgrounds with smart guardrails—where innovation accelerates instead of stalls. • ROI comes from outcomes, not usage Adoption metrics don’t move the needle. Revenue, speed, quality, and client impact do. AI only matters when it changes results. • Explainability is the currency of trust If leaders can’t explain why the numbers changed, AI adoption stops cold. Observability, variance analysis, and human-in-the-loop design are non-negotiable. • Responsible AI is how you scale—fast. similar to my discussions in Davos, trust, security, and accountability aren’t brakes. They’re what allow AI to move from pilots to production without friction. • Competitive advantage lives in institutional knowledge The frontier isn’t generic models—it’s encoding judgment, experience, and IP into AI systems people trust to run real work. 🚀 If you’re a leader looking to move AI beyond pilots and proofs of concept—and into measurable, durable impact—let’s talk. The next wave is already here. With appreciation to the Alvarez & Marsal team who made this such a strong discussion: Matthew Frank, Richard Chen, Rafael Souza, Joe DeTullio, Dhiren Rawal, James Chalmers, Luke Cornetta, Pranav Gupta, Joel (Joey) Baruch, John Held, Avishek Nandi, Janine Knox, and Austen Myers Huge thanks to the Microsoft team for the leadership, rigor, and partnership—and to the A&M AI community, always a privilege to build with this level of talent: Julian Fang, Danielle Prendergast, Meagan Smith, Mike Bria, Samantha Janiec, Daisy Sarne

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