Technology Was Never the Lesson: What Foresight Taught Me About Leading Transformation

The most valuable thing foresight ever taught me wasn't how to predict the future—it was how to help organizations prepare for it.

Ironically, I didn't learn that by studying the future. I learned it by asking better questions in the present.

In 2021, during one of our Horizon Z workshops, we posed a question that sounded almost absurd at the time.

What if one day purchasing decisions weren't made by people?

Not because humans disappeared.

But because intelligent systems had become sophisticated enough to evaluate options, compare products and make recommendations—or even decisions—on behalf of customers.

At the time, our discussions weren't focused on generative AI. ChatGPT didn't exist yet.

We were exploring emerging technologies like digital twins, robotics, automation, machine learning and other technologies that could fundamentally reshape industries over the next decade.

The question wasn't whether one specific technology would make this happen.

The question was:

If technology changes how decisions are made, what does that mean for businesses?

Within minutes, the conversation shifted.

We quickly realized the technology wasn't the most interesting part of the conversation. Its implications were.

If intelligent systems were evaluating products...

Would emotional marketing still matter?

Would brand reputation influence the decision in the same way?

Or would purchasing become increasingly based on technical performance, interoperability, lifecycle cost and measurable outcomes?

Then the discussion became even more interesting.

Where would those systems get their information?

Would they trust manufacturers describing their own products?

Would independent third-party testing become the most trusted source?

Would peer recommendations matter more than advertising?

Would structured product data become a competitive advantage?

Would superior engineering matter even more than superior messaging?

By the end of the workshop, we weren't trying to predict whether this exact future would happen.

We were asking a much more important question.

If this future became reality, how would we need to think differently today?

That conversation fundamentally changed how I thought about foresight.

Not because we found the answer.

But because we discovered better questions.

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Horizon Z wasn't really about technology

Several years ago, I had the opportunity to establish and co-lead Horizon Z, an initiative created to help our organization explore emerging technologies and prepare for the future of business.

On paper, it looked like an innovation program.

We explored artificial intelligence, robotics, automation, digital twins, quantum computing, gamification, and future ways of working.

Initially, I thought our job was to understand these technologies.

It didn't take long before I realized something.

The technology was never the destination.

It was the catalyst.

Our goal wasn't to become experts in emerging technologies. It was to use those technologies to challenge assumptions, expand thinking, and prepare our organization for transformational change.

Each new technology became an opportunity to challenge long-held assumptions about customers, markets, products and business models.

Over time, I realized the hardest part wasn't understanding the technology.

It was helping people become comfortable questioning the way things had always been done.

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The questions that mattered were different

Every emerging technology generated the same initial questions.

What does it do?

Should we invest?

What's the business case?

How quickly should we adopt it?

Those are important questions.

But they rarely led to transformation.

The conversations that ultimately changed our thinking sounded different.

• What assumptions does this technology challenge?
• If this became mainstream, how would customer expectations change?
• What new sources of competitive advantage might emerge?
• If we were building our business today, would we design it the same way?
• What capabilities should we begin developing before the market demands them?

Those questions weren't about predicting the future.

They were about preparing for multiple possible futures. In foresight and scenario planning, we often explore possible, plausible, probable, and preferred futures—not to predict which one will happen, but to help organizations become more resilient regardless of which future unfolds.

That realization fundamentally changed how I viewed foresight.

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Foresight isn't about predicting the future

One of the biggest misconceptions about foresight is that its purpose is to predict the future correctly.

In my experience, it's something much more practical.

Foresight builds an organization's ability to navigate uncertainty.

It creates space to challenge assumptions before they become constraints.

It encourages leaders to ask better questions before rushing toward better answers.

Most importantly, it helps organizations prepare before change becomes unavoidable.

Because transformational technologies don't arrive with certainty.

They arrive with ambiguity.

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When Generative AI went Mainstream..

When ChatGPT was released in November 2022, something interesting happened.

A technology that had once felt distant suddenly became accessible to everyone.

Almost overnight, organizations began asking,

"What AI use cases should we build?"

The pattern felt remarkably familiar.

It was the same instinct we had seen with every transformational technology before it.

Jump to implementation.

Find quick wins.

Start building.

A few months later, our executive leadership asked the Horizon Z team to help the organization understand what generative AI could mean for the business as the technology matured.

We deliberately chose a different starting point.

Before building use cases, we built understanding.

We invited external experts to explain what large language models actually were—and just as importantly, what they weren't.

We created opportunities for people to experiment, learn, share ideas, and explore possibilities together.

The goal wasn't simply to teach people how to use a new tool. It was to help them think differently about how work itself could change.

The conversations evolved.

People stopped asking,

"Can AI do this?"

They started asking,

"What becomes possible if we redesign the way we work?"

That shift in thinking was far more valuable than any single AI use case.

Looking back, Horizon Z taught me that technology was never the lesson.

It was simply the catalyst that challenged us to think differently.

Because foresight isn't about predicting the future.

Because the future doesn't reward the organizations that predict it perfectly. It rewards the ones that are prepared to adapt when it arrives.