What does the future of innovation sound like?

A perfectly synchronized orchestra — every section in harmony, building to a soaring crescendo?
Or the electric pulse of jazz — unpredictable, improvisational, sometimes messy, but alive with possibility?

This past week, I found myself sitting with that exact question during the SDIT 2025 AI immersion in Milan — part of my Master's of Design Methods program at the Institute of Design, Illinois Tech. Over the course of a week, we moved through Milan — a city where design past and futures collide. We sat in studios, boardrooms, and lecture halls with some of the sharpest minds in design and AI. But what stuck with me wasn’t a single framework or case study.

It was the realization that two distinct futures of innovation are barreling toward us. Both powered by AI. Both driven by design. But each shaping the world — and our roles as designers and leaders — in radically different ways.

Future One: The Orchestra — AI Embedded, Transparent, and Aligned

In this world, innovation is precise. Composed. Aligned.
AI becomes a second brain, deeply embedded in how companies operate.

Every team has its own AI “digital twin” — emotionally intelligent, tuned to the team’s culture, and openly showing its reasoning. No black boxes. No shadow algorithms. Just visible collaboration between humans and machines. Designers, strategists, and developers don’t get replaced — they become conductors. Setting tempo. Curating which insights matter. Ensuring every note aligns with the mission, the ethics, the brand.

The innovation payoff? Compounded creativity. Ideas don’t just spark; they stack. Knowledge moves across teams faster than ever, building momentum toward breakthroughs that feel inevitable. If you’re hearing the hum of AI copilots, generative design tools, and transparent APIs already — you’re not wrong. This future is well on its way.

Future Two: The Jazz — Open-Source, Collective, Disruptive

But what if innovation takes a wilder path? One that rejects orchestration altogether?

In this future, AI is community-owned — open-source, transparent, and trained on lived experience instead of market data. Neighborhoods, unions, activist groups — they all have their own AI agents. Not to optimize productivity, but to fight eviction notices, map climate threats, write better policy proposals. Data is controlled by people, managed through Data Trusts that serve the collective good.

There are no conductors here. Just a messy, beautiful improvisation — new ideas rising from real-world needs, not corporate strategy decks. And the signals are already flashing: the rise of open-source LLMs, data sovereignty movements, and the growing demand for AI that serves people, not platforms.

Why This Choice Matters — and Why It’s Coming Fast

The most provocative takeaway from Milan? Both futures are plausible. Both are already emerging.

On one side — corporations embedding AI agents, aligning them to culture, ethics, and strategy.
On the other — communities reclaiming technology, pushing back against monopolies, designing AI that serves the many, not the few.

It’s not just a tech question. It’s a systems question. A design question. A leadership question. Because the real challenge ahead isn’t whether we’ll innovate with AI — it’s who controls the tools, what values shape them, and who gets to participate.

How Do We Prepare for Both?

If AI is set to reshape innovation, here’s what I walked away believing we need to do next:

• Learn to work with AI — not just use it. Practice co-creation, not command-and-control.

• Design the ethical guardrails now. AI will follow the incentives we create — good or bad.

• Push for open-source alternatives and data sovereignty. Because collective intelligence should belong to all of us.

• Invest in the skills that let us conduct and improvise. The future will reward those who can switch between symphony and jazz.

Maybe the real work ahead is learning how to move between both — building systems that can scale and stay human. Because either way — we get to choose the song. And that, to me, is the future of design, leadership, and systems thinking.

What Comes Next: Organizational Models for Innovation

This reflection sparked a bigger question for me:
If we know these futures are coming, what does adaptation actually look like inside an organization?

Over the past quarter, I explored this in depth — designing a future-facing model for how a large Latin American financial conglomerate could begin adapting toward AI-powered open innovation. If you’re interested in how these ideas move from theory into organizational strategy, you can check out that project here: Credicorp - Organizational Models for Innovation