In the softly lit conference hall at MDM West 2025, Dr. Shawn DuBravac stood before a crowd of industry veterans and innovators, telling a story not just about technology, but about human potential. As he spoke about the transition from digitization to datification, I found myself leaning forward, captivated not by the abstract promise of artificial intelligence, but by the deeply human narrative unfolding in his examples.

When Chess Masters and Machines Join Forces

The most compelling moment came as DuBravac concluded with the story of Gary Kasparov—world chess champion whose relationship with AI evolved from adversary to advocate. In 1997, after losing to IBM's Deep Blue in a highly publicized match, Kasparov could have retreated into bitterness. Instead, he embarked on a journey that would reshape our understanding of human-machine collaboration.

"What he would go on to discover," DuBravac explained with quiet intensity, "is that weak human plus machine plus better process was superior to a strong computer alone and, more remarkably, superior to a strong human plus machine plus inferior process."

This revelation emerged from Kasparov's "freestyle" chess tournaments, where participants could compete as individuals, as pure AI systems, or as hybrid teams. The winners weren't grandmasters or sophisticated algorithms working in isolation. Instead, victory consistently went to teams of "two strong amateurs with five software programs" who had developed an intuitive understanding of when to trust human intuition and when to defer to computational analysis.

This isn't just a story about chess—it's a parable for the future of innovation itself.

The Human Element in an Age of Algorithms

Throughout his keynote, DuBravac wove a narrative that challenged the prevailing anxiety about AI replacing human creativity. His examples—from Coca-Cola's data-driven product development to Georgia Pacific's knowledge management platform—revealed a more nuanced reality where AI amplifies rather than replaces human capability.

Consider Georgia Pacific's experience. Their challenge wasn't a lack of expertise but its fragmentation across different facilities, teams, and generations of workers. Their AI solution didn't replace human knowledge; it connected it, making the collective wisdom of the organization accessible to everyone.

"Each one of those plants ends up being unique," DuBravac observed. "It has unique knowledge embedded in its workers... and then just embedded information." The AI platform they developed captured this distributed intelligence, allowing workers to access critical information that might have been locked away in manuals, digital repositories, or the minds of colleagues they'd never met.

The emotional resonance of this example lies in its recognition of the value of human experience. The AI didn't dismiss the tacit knowledge accumulated by workers over decades; it honored it by preserving and sharing it.

From Selling Products to Delivering Outcomes

Perhaps the most profound transformation DuBravac described wasn't technological but relational. As companies embrace AI and datification, they're fundamentally reimagining their relationship with customers.

John Deere's story exemplifies this shift. For decades, their business model was straightforward: build tractors, sell them for cost plus margin, reinvest some profits in R&D, and repeat. Now, with their sea spray tractor—equipped with 30 cameras and AI that can identify and selectively treat individual weeds—they've moved to an outcome-based model.

"Rather than selling this for cost plus margin and reinvesting it, they're selling it on a per acre basis," DuBravac explained. "It's $4 an acre, whether you're a thousand acre farm or a 10,000 acre farm or 100,000 acre farm."

This transformation isn't merely transactional. It represents a profound realignment of values and incentives. By pricing based on outcomes rather than physical assets, John Deere has fundamentally changed their relationship with farmers. They're no longer just selling equipment; they're investing in their customers' success.

For those of us developing medical devices and life science tools, this insight carries immense potential. Imagine a future where a diagnostic device isn't just sold as hardware but priced based on accurate diagnoses delivered, or where therapy devices generate revenue based on improved patient outcomes.

Navigating Multiple Horizons: The Innovation Challenge

The central tension in DuBravac's talk—and perhaps in all innovation—lies in what he called "competing time horizons." How do we balance immediate business needs with future possibilities? How do we maintain current revenue streams while investing in technologies that might render them obsolete?

"One of the challenges, I think all of you have, and leaders in this industry face, is how do I make the leap?" DuBravac asked rhetorically. "How do I make the jump? How do I drive my business forward in a time of rapid change?"

His answer resonated with the innovation journey we've witnessed with our clients at Product Creation Studio: "Think about working across competing time horizons simultaneously. Yes, you have to worry about what's happening this week, this month, this year... but you also have to be thinking about what the customer is gonna look like in five years or ten years."

This is where the concept of "super teams" becomes truly transformative. By bringing together human creativity, strategic thinking, and AI capabilities, organizations can navigate these competing horizons more effectively than ever before.

The Alchemy of Innovation: Creating Super Teams in Practice

At Product Creation Studio, we've seen firsthand how building effective "super teams" transforms the innovation process. These aren't simply groups that use AI tools; they're integrated teams where human and artificial intelligence complement and enhance each other.

Consider our work with LumiThera on their Valeda Light Delivery System—the first FDA-authorized treatment for vision loss in dry age-related macular degeneration. The breakthrough wasn't just technical; it emerged from a deep collaboration between clinicians who understood patient needs, engineers who could translate those needs into design parameters, and data analytics that could validate efficacy.

Similarly, our partnership with Orlance on their MACH-1 system for needle-free vaccine delivery succeeded because we created a team where clinical insight, engineering expertise, and computational analysis worked in concert. The human team members provided the vision and context; the computational tools helped optimize designs and predict performance.

This is the essence of what DuBravac described: not AI replacing human innovation, but AI and humans forming "super teams" that accomplish what neither could achieve alone.

Embracing the Future: From Fear to Collaboration

DuBravac began his talk with a historical example of ice harvesting—an industry transformed by technological change that left incumbent leaders behind. The message was clear: technological shifts don't just change how we work; they change who leads.

The end of one industry (ice harvesting) and the start of another (refrigerators and air conditioners).

Yet his conclusion offers a more hopeful perspective. By embracing the complementary strengths of humans and machines—by building "super teams" that combine human creativity with AI's analytical power—we can navigate technological transitions more successfully than previous generations.

The future belongs not to those who resist change nor to those who blindly embrace every new technology, but to those who thoughtfully integrate human and artificial intelligence to solve meaningful problems.

As we left the conference hall, conversations buzzed with energy. The narrative had shifted from fear of replacement to excitement about collaboration. DuBravac had accomplished what all great storytellers do—he'd helped us see ourselves not as passive observers of technological change, but as active participants in shaping its direction.

For innovation leaders navigating this transition, the path forward is clear: invest in building your own "super teams," experiment thoughtfully with AI applications, and remember that the most powerful innovations come not from technology alone, but from its thoughtful integration with human insight, creativity, and purpose.

Key Takeaways for Innovation Leaders

The Power of Super Teams: The most successful innovation comes not from AI alone or humans alone, but from carefully structured collaborations where each contributes their unique strengths. As Kasparov discovered, "weak human plus machine plus better process" outperforms either working in isolation.
From Digitization to Datification: Move beyond simply having digital processes to actually leveraging the data generated by those processes. The richest opportunities often lie in data that was always there but never properly utilized.
Shifting Business Models: Consider how AI might transform your relationship with customers—potentially moving from selling products to selling outcomes, as demonstrated by John Deere's per-acre pricing model.
Knowledge Integration: Use AI to capture and connect dispersed expertise across your organization, making collective wisdom accessible to everyone, as Georgia Pacific did with their generative AI platform.
Navigate Multiple Time Horizons: Build the capability to address immediate business needs while simultaneously exploring longer-term possibilities that may fundamentally change your market.
Embrace Experimentation: Create safe spaces to test AI applications, recognizing that the most valuable implementations may emerge from unexpected directions. As DuBravac noted, "Technology moves very slowly until suddenly it doesn't."
Anticipate Workflow Transformation: Prepare for AI to change not just what you do but how you do it—potentially automating routine tasks and creating space for more creative and strategic work.
Value Human Expertise: Remember that AI works best when it augments rather than replaces human capability, preserving and amplifying the tacit knowledge and intuition that only comes from experience.

The Rise of Super Teams: How AI is Reshaping the Innovation Landscape