"Invest in relationships with the same seriousness that you invest in expertise": an interview with Elaine Barsoom

Before her session at Future Summit: AI, we sat down with Elaine Barsoom, Founder of Waveco to talk about how organizations move from experimentation to scalable impact when working with new technologies, and much more. Read the entire interview below:

Q1. What initially drew you to working at the intersection of innovation and business strategy? 

I came to this work through people who build. My father was an entrepreneur, and I grew up watching the practical side of building a business. Judgment calls without perfect information. Relationships earned over time. Risk, resilience, timing, and the ability to see an opportunity before it was obvious to everyone else.

Early in my career, I worked on an adtech integration into American Express, at a time when adtech was still an emerging category. I saw how a startup could bring speed, technical depth, and a new way of reaching customers into a much larger enterprise. American Express brought scale, brand, customers, and distribution. The interesting work was not the technology by itself. It was translating external innovation into enterprise growth.

That became the through line of my career. I have always been interested in the moment when emerging technology becomes business value. When it changes a workflow, creates a new business model, opens a market, improves a customer experience, or helps people do better work. Innovation on its own can become novelty. Strategy on its own can become analysis. The work that has energized me is the operating layer between the two.

Q2. What influenced your transition into working with large scale strategic deals and alliances?

I became interested in strategic deals and alliances because I saw that some capabilities are too important, or moving too quickly, to build entirely inside one company.

Negotiating the adtech integration into American Express was one of the first places I saw that clearly. It was not just about getting access to a technology. It required aligning business goals, customer experience, data, economics, brand, legal considerations, governance, and the operating model needed to make the partnership actually work inside a large company.

That shaped how I think about partnerships. The best deals are a way to increase innovation throughput. They help an organization learn faster, build new capabilities, test new models, reach customers differently, and accelerate transformation when building everything internally would take too long.

That became even more relevant at Nike, where I helped build the AI and Emerging Technology Center of Excellence. In AI, the challenge was not simply finding interesting tools or evaluating startups. The harder work was determining which capabilities Nike needed to own, where external partners could accelerate progress, how to move from pilots to adoption, and how to connect emerging technology to real business outcomes.

That is what has kept me in this work. Strategic deals and alliances can be powerful mechanisms for growth and transformation, but only when they are tied to a real operating need and structured to create measurable enterprise value.

Q3. What differentiates a successful innovation partnership from one that fails? 

A successful innovation partnership starts with a sharp business problem. Not with a tool, a trend, or a press release. The better question is always: what problem are we trying to solve, why does it matter, and can this partner help us solve it in a way we could not do as effectively on our own?

The strongest partnerships have a few things in common. They are anchored in a real business priority. The incentives are aligned. The operating model is explicit. Decision rights, governance, data access, legal guardrails, IP, compliance, execution cadence, and success metrics cannot be afterthoughts. There also has to be an internal owner with enough authority to move through the friction that comes with doing something new.

Partnerships fail when they are treated as side projects or vendor relationships. A pilot is not a business outcome. A procurement process is not an adoption strategy. A startup cannot be expected to navigate the complexity of a large organization without real sponsorship from the inside.

The human work is often the hardest part. Partnerships have to survive different speeds of decision making, different cultures, different risk tolerances, and competing priorities. The partnerships that work are the ones where both sides do the hard work after the agreement is signed. They define ownership, confront friction, keep learning, and make the new capability part of how the business actually operates.

Q4. What are you currently focused on when advising executive teams on technology and growth? 

Right now, I work with leaders and companies to answer two questions: where is value trapped, and where can AI unlock human potential? From there, the work becomes practical. Which workflows matter most? Which opportunities should be prioritized? What should be built, bought, or partnered for? What operating changes are required to move from ambition to execution?

The answer is rarely found in a roadmap alone. It comes from getting close to the people doing the work. Companies carry decades of accumulated context: tacit knowledge embedded in workflows, relationships, workarounds, and institutional memory that rarely lives cleanly in a data system. Frontline employees can see where decisions slow down, where customers get stuck, where exceptions happen, and where value disappears in handoffs.

That is why I think of this work as embedded partnership, not advisory at a distance. The goal is to redesign workflows around how the organization actually works, then use AI to compress low-value work so people can focus on judgment, creativity, relationships, and the work that matters most. When that happens, AI becomes more than a tool. It becomes a source of competitive advantage.

Q5. How can organizations move from experimentation to scalable impact when working with new technologies?

Organizations scale AI when they stop asking, “What can this technology do?” and start asking, “Where is value trapped, where is human potential underused, and what work needs to be redesigned to unlock both?” That shift moves AI from experimentation to operating discipline.

The best teams begin with the value at stake. They identify the workflows, decisions, or points of friction where improvement would materially affect growth, cost, speed, quality, risk, customer experience, or employee capacity. Then they design experiments around those areas, not around generic demonstrations.

A pilot should teach the organization something useful about feasibility, data readiness, user behavior, integration, governance, and economic impact. The path to scale has to be designed before the pilot ends. Who owns the outcome? What system does it integrate with? What data is required? What governance is needed? What behavior has to change? How will adoption and value be measured? Too many pilots stall because they were never designed to become part of the operating model.

One of the biggest lessons from my work building the AI and Emerging Technology Center of Excellence at Nike was that adoption does not happen because a tool exists. It happens when the people doing the work help design the new workflow. If they can see that AI removes routine work and gives them more capacity for the work that matters, they become participants in the change. If it feels like another layer of software forced onto an already crowded workflow, adoption stalls. Scale comes when humans are empowered and workflows are redesigned around how work actually happens.

Q6. What advice would you give to professionals looking to build a career in innovation and strategy? 

I would tell them to remember that this work is ultimately about people.

It is easy to talk about innovation through technology, platforms, business models, or capital allocation. All of those matter. But the real work happens through human capital. The people who take risks. The people who build conviction. The people who earn trust, change how work gets done, and bring others along before the outcome is obvious.

That is personal for me. My own career was shaped by relationships with people who trusted me with hard problems before I had the perfect title or the perfectly linear path. People who gave me room to learn. People who were willing to build with me through ambiguity. Looking back, the work that mattered most was never just about a deal, a strategy, or a technology. It was about the teams, the trust, and the conditions that allowed people to do meaningful work together.

So my advice is to invest in relationships with the same seriousness that you invest in expertise. Build range. Learn how companies actually operate. Spend time with customers, frontline teams, engineers, finance leaders, legal teams, and operators. Understand incentives. Understand why good ideas stall. Understand what it takes for people to adopt something new. 

And stay close to the human reason for the work. Innovation should not only be about efficiency or disruption. At its best, it should help people and organizations flourish. It should create more capacity, better decisions, stronger teams, more meaningful work, and new forms of growth. Careers in innovation and strategy are not linear. Mine was not. But if you build trust, develop judgment, stay close to the work, and keep connecting technology back to human and business value, you will build a career that compounds over time.