How Data Leaders Are Adapting to Change

Miss these leadership shifts and you risk irrelevance: (Others are already adapting) Even top leaders feel the pressure today. AI, hybrid work, global shifts...all colliding fast. Leading the old way? You’re already falling behind. Here's how not to: 1/ The Agile Tenacity Test ↳ Agility isn’t optional anymore. ↳ Agile leaders recovered 30% faster (McKinsey). ↳ Run quarterly “assumption checks” w/ your team. ↳ Challenge every strategy, no sacred cows allowed. 2/ The Data Blind Spot ↳ Gut calls alone won’t cut it now. ↳ AI-driven leaders saw 22% higher profits (Gartner). ↳ Start a weekly “data vs gut” review session. ↳ Study where instinct and data clash, and why. 3/ The Psychological Safety Gap ↳ Fear kills innovation at its roots. ↳ Pfizer cut discovery times by 50% (Horton). ↳ Launch a “Failure File” to capture smart risks. ↳ Review those risks and lessons every quarter. 4/ The Empathy Deficit ↳ 68% now value well-being over pay (Gallup). ↳ Adobe’s EQ tool boosted leaders 37% (Horton). ↳ Schedule monthly personal check-ins, no work talk. ↳ Ask about wins, life, and what support they need. 5/ The Purpose Problem ↳ Leaders need more than profits now. ↳ Patagonia tied bonus & purpose, trust up 33%. ↳ Add a purpose metric to your dashboards now. ↳ Review purpose with the same focus as profit. 6/ The Hybrid Reality Reckoning ↳ Hybrid isn’t a perk, it’s the norm. ↳ GitLab boosted innovation 19% (Horton). ↳ Cancel one recurring meeting this month. ↳ Try async updates and ask what worked better. 7/ The AI Co-Pilot Era ↳ Leaders fighting AI will lose fast. ↳ Unilever cut decisions 28% with AI help (DDI). ↳ Assign an “AI Spotter” at key meetings. ↳ Their job: find where AI can assist, every time. The future rewards leaders who rethink it all. Stay curious. Stay human. Stay bold every day. ♻️ Share to help others adapt to the shifts. 🔔 Follow me (Nadeem) for more like this.

Shifting from leading data teams to driving business decisions was a journey that reshaped my perspective profoundly. This table captures 5 critical changes in mindset between a data leader and a business operator. 1) Insights driving Action vs Action driving Insights: While insights can be always tapped from data, I found that taking action and then interrogating the data was a lot more powerful in identifying meaningful signals. In retrospect, this seems obvious—the more we explore the search space, the more data reveals. Yet many data, even business team keep searching for insights in stagnant data pools. 2) Composing vs Decomposing: Early in my data career, I thrived on slicing and dicing datasets to uncover useful nuggets and patterns. However, as an operator, the greater value is in synthesizing information and crafting cohesive narratives. Organizations are often inundated with fragmented analyses. The real power lies in connecting these disparate insights into a coherent storyline. 3) Timing of Decisions: As a data leader, I was seeking certainty in decision-making. However, as an operator, I learned that making timely decisions with 70% clarity is usually more effective than waiting three months for 90% certainty. Recognizing the law of diminishing returns in decision quality is crucial. 4) A/B Testing Utility: A/B testing is the gold standard for calculating true causal impact, but as a business operator, I encountered scenarios where rigorous testing was either impractical or even impossible. Finding alternative validation methods become essential in such cases. 5) The Value of a Good Strategy: Perhaps the most significant mindset change is appreciating the foundational value of a good strategy. Ironically, a good strategy may not be informed directly by data but it provides the framework for analytical teams to drive operational excellence.

AI Just Changed Leadership Forever—And The Data Proves It (Including Mine). #realtimedisruption Leadership used to be about instinct. Now? It’s about data, clarity, and structured decision-making. Over the last three weeks, I ran an AI-Speed Leadership Assessment to track how AI is reshaping decision-making, hesitation, and trust in leadership—including my own. The results? Game-changing. Speed of Leadership Decisions: +42.86% (AI helped me cut through hesitation, making my decisions clearer and faster.) Handling Hesitation in Others: +50.00% (Seeing hesitation as a structural issue rather than a frustration completely changed how I approach it.) Emotional Weight Processing: +80.00% (Biggest unlock? Separating emotion from execution. AI helped me process challenges without getting stuck in them.) Structuring Leadership Trust: +50.00% (Trust isn’t just assumed—it has to be intentionally structured to keep leadership alignment strong.) Engagement with Hesitant Leaders: +60.00% (Leadership momentum doesn’t have to stall when people hesitate—structured re-engagement strategies make all the difference.) The Big Takeaway? AI isn’t just making leadership faster—it’s making hesitation instantly visible. I’ve seen firsthand how what used to be a slow, strategic process now happens in real time. Leaders who once had weeks or months to process power shifts now have to adjust instantly. Most firms are still using AI for tasks instead of leadership. But the real power is in AI-assisted decision-making, strategic processing, and clarity in high-stakes situations. 📢 These were my scores—where would you land? If you’re not thinking about how AI changes leadership, you’re missing the real disruption. Let’s talk. 👇 #AILeadership #DataDrivenLeadership #CPATransformation #radicalcpa #accountingandaccountants #leadership

🧀 Just read this thoughtful piece by Insight Partners’ Gary Survis about embracing change in the AI era, and it really resonated with me. Gary applies the message about adapting to change from “Who Moved My Cheese?” to today's AI revolution, and he's absolutely right: This isn't just another tech shift - it's potentially THE defining transformation of our careers. It’s what I’ve been referring to as #Discontinuity, rather than mere disruption. Discontinuity requires a profound change in mindset. Gary offers several actionable strategies: Invest in yourself: It's not enough to just dabble in AI. We need to deeply understand how these tools can drive real ROI in our organizations. The landscape of free and paid resources he shared (from Andrew Ng to Paul Roetzer) shows there's no excuse not to level up. Stay informed: Love his point that "waiting until the dust settles" isn't a strategy. In today's rapid-fire AI landscape, leaders need to actively track developments. Following voices like Sam Altman and Ethan Mollick isn't just about staying current - it's about seeing where the puck is heading. Embrace curiosity: As leaders, we need to move beyond our comfort zones and experiment constantly. It's not about single big changes, but continuous adaptation and learning. The cheese has moved for all of us in business. At our firm, D'Ornano + Co., we’re constantly challenging our own assumptions and trying to remain as agile as possible. The question isn't whether to adapt, but how quickly we can embrace this change and lead our teams through it. #Leadership #AI #Innovation #GenAI #FutureOfWork