Before choosing solutions, it helps to understand what actually needs to change. I help leaders and teams see the system around a challenge and identify where intervention could create meaningful value.
Most organizations do not lack AI ideas. Pilots, tools and proposals multiply quickly. What is often missing is a shared understanding of what AI is actually changing for the organization, and what needs to change in response.
The challenge rarely sits in one place. It runs across work, decisions, roles, customer and employee experiences, capabilities, incentives and governance. Looking at isolated ideas can hide where value is really getting stuck, and where a well-chosen intervention could make the biggest difference. The question is not how to find more AI use cases, but where change would create meaningful value.
I use human-centered design, systems thinking, research and co-creation to understand the challenge, surface different perspectives, and identify meaningful leverage points for change.
How we work
Clarify what is changing, what is at stake, and what the organization is actually trying to improve.
Bring in different perspectives to see how people, work, decisions, technology and structures interact around the challenge.
Find where intervention could matter most, and decide what deserves further exploration or experimentation.
Typical format: Half-day (3–4 hours) or full-day (6–7 hours)
A focused leadership or cross-functional workshop to understand what AI-driven change means for the organization, surface perspectives, identify leverage points, and decide what deserves further exploration or experimentation.
If value is reduced to productivity, many of the most important opportunities for change stay invisible. Depending on the challenge, value may include:
Usually where value is already getting stuck: where information does not travel, where decisions are slow or inconsistent, and where customer or employee needs go unmet. Those places become visible by understanding the system around a challenge, not by surveying available tools.
With the challenge and the outcomes that matter. Use cases are a useful way to describe how a specific opportunity will be addressed, but as a starting point they can anchor a program to what current tools happen to do.
Look for leverage points: places where changing one part of the system could materially improve the result. A small number of well-understood leverage points, with clear value hypotheses, is a better basis for experimentation than a long list of ideas.
The workshop makes sense when the challenge is important but not yet clearly defined.
There is plenty of AI activity, but little agreement on what actually needs to change.
Leaders and teams see the challenge differently, and those views need to come together.
You want to decide what deserves exploration or experimentation before committing resources.
If the challenge is already clear enough to prototype, the Human–AI Transformation Design Sprint may be the better starting point: co-design, prototype, test and refine how a better Human–AI system could work before deciding what should scale.
Explore the Design SprintIf you are facing an important challenge and want to understand where change could create meaningful value, I am glad to think it through with you, or to shape a Human–AI Transformation Workshop around it.
Or write directly to sara@bermudez-t.com.