At this year’s Analytics Leadership Consortium (ALC) Summit in Portland, Oregon, senior analytics leaders came together for in-depth discussion and connection. Against the backdrop of panoramic views, hands-on activities, and one-of-a-kind venues like the Oregon Museum of Science and Industry and Portland City Grill, the gathering reminded us of something critical: the most transformative insights happen when people feel energized, engaged, and genuinely connected.
Over the course of two days, attendees leaned into honest, nuanced conversations about the future of analytics and the human dynamics that shape it. From the data debt behind generative AI to the leadership practices that drive sustainable transformation, the sessions were as grounded as they were illuminating.
What follows are highlights from two of those standout sessions that speak directly to the challenges analytics professionals face today.
Generative AI: Our Expectations and Its Demands
Presented by Marc Demarest, IIA Expert and Principal at Noumenal
Generative AI sits at the familiar intersection of promise and reality—where lofty marketing claims often outpace real-world outcomes. As IIA Expert Marc Demarest put it during the ALC Summit in Portland, “It’s not a matter of sticking. It’s a matter of being real versus being BS.”
The case of Delta Airlines is instructive. After a high-profile launch of an AI-powered pricing model in 2024, the excitement vanished. Was it successful? No one knows. And this gap—between splashy announcements and measurable business impact—is one the data and analytics community knows all too well.
For D&A leaders, that gap is the battleground. Generative AI tempts us with the idea of skipping the grind—offering sudden breakthroughs instead of incremental gains. But the truth is: the wins so far are modest. Smarter chatbots, minor cost savings, a few nudges in personalization. And the same old problems—unclean data, siloed systems, organizational misalignment—still haunt us.
In fact, with AI, our data debt is compounding. As we scramble to feed large language models, we’re simply scaling messy inputs. And the dream that AI will resolve our wicked problems—those thorny, multidimensional issues with no clear answer—is still just that: a dream.
These wicked problems demand more than tools. They demand human judgment, collective debate, the willingness to challenge assumptions, and the honesty to admit what isn’t working. In a world increasingly tempted to "just ask AI," critical thinking is becoming dangerously devalued. As Demarest warned, “When we stop asking why, we lose our leverage.”
And yet, organizations continue to chase a wish list: measurable ROI, competitive advantage, and pragmatic AI use cases. But most of the real value still sits with a handful of dominant tech providers who own the foundational models, infrastructure, and usage pipelines. Are they selling tools? Or are they mining us for training data?
Demarest outlined four plausible futures:
- The Gentle Singularity (P=.15*): AGI arrives smoothly, ushering in a productivity boom.
- The Great Correction (P=.35*): Hype crashes, investments dry up, and AI enters a cooling period.
- Energy & Infrastructure Starvation (P=.3*): Physical constraints throttle growth.
- The Regulated Future (P=.4*): Policy finally catches up and reins things in.
*Probabilities calculated using Gemini.
In any scenario, analytics leaders have a mandate: educate up and out. Boards, execs, and frontlines need help separating signal from noise. That means guarding attention, sustaining judgment, and doubling down on critical thinking.
As Demarest closed: “In the end, our most precious currency is still our attention, our judgment, and our leadership. Spend them wisely. Guard them fiercely. And use them to build what marketing promises can’t deliver on their own.”
Elevating Data and Analytics Leadership
Presented by Brad Schwartz, IIA Expert and Founder of Tech Leaders Coach
With generative AI accelerating digital transformation, the pressure on data and analytics teams to deliver real business value is higher than ever. Yet most transformation efforts still fail, mostly because the human systems around it break down. Brad Schwartz, IIA Expert and founder of Tech Leaders Coach, argues that the differentiator isn’t technical know-how—it’s leadership. The kind that builds trust, creates space for honest dialogue, and turns high-performing individuals into aligned, resilient teams.
Schwartz identifies three foundational leadership practices that help data and analytics leaders move from insight to sustainable impact: building trust, listening to understand, and strengthening self-awareness. Trust creates the psychological safety teams need to take risks and learn. Deep listening helps leaders connect across functions and diffuse tension. And self-awareness allows leaders to model the behaviors they want to see in others—turning internal work into organizational momentum.
More than a framework, these practices are daily habits. By tuning into your team’s emotional dynamics and owning your own mindset, you equip your organization to navigate uncertainty and change with confidence. Technical skills still matter, but the way you lead will determine whether your transformation sticks.
Key Takeaways
- Building trust fuels experimentation, speed, and alignment.
- Reflective listening increases connection and reduces friction.
- Self-awareness helps leaders lead with intention, not reactivity.
- Leadership habits—not just strategies—enable lasting transformation.