Innovation Storytellers

Innovation Storytellers Equip your people with the skills they need to effectively communicate their breakthrough ideas.

09/08/2026

One of the biggest mistakes I see leaders make when telling stories about innovation is assuming the story should center on the innovation itself.

In this clip from the Innovation Storytellers Show, Park Howell explains why that instinct backfires and why even the most impressive product, initiative, or breakthrough falls flat when the audience cannot see themselves in it.

Park puts it plainly. People do not care about your innovation, your brand, or your widget. They care about what changes in their lives result from it. When storytelling shifts from self-focused to audience-focused, something important happens. Trust starts to form. Understanding, appreciation, and empathy come into play. And suddenly, the story has weight.

What struck me most in this moment is how tightly story and trust are linked. When leaders make the story about the audience, they show that they understand what people want, why it matters, and what is standing in the way. That is when stories stop being slides and start becoming catalysts for action.

Curious to hear your take. Where have you seen stories fail because they focused on the offering instead of the outcome?

https://zurl.co/i5fvT

09/03/2026

I ask every guest on the Innovation Storytellers Show the same three questions, and this exchange with Stephen Parkins really stayed with me.

When asked about the greatest innovation of all time, Stephen lands on the internet. Not as a perfect force for good, but as a world changing shift that connected places that had never been connected before, expanded access to education, and reshaped opportunity on a global scale. He is clear that even the most powerful innovations come with tradeoffs, and that tension matters.

When he talks about the innovation team he would have joined, his answer goes back to the early days of Airbnb. Before scale, before polish, when the team was wrestling with the chicken and egg problem of marketplaces and doing whatever it took to make the model work. Air beds, cereal boxes, and a lot of uncertainty. That moment captures something many organizations forget. Innovation rarely looks impressive while it is happening.

The final question is the most telling. What the world needs now is not a single breakthrough, but a shift in mindset. Less retreat into short term preservation. More willingness to think long term, explore scenarios, and build options in a chaotic world. Stephen points to foresight, simulation, and AI enabled scenario tools as ways leaders can regain perspective rather than control.

What I appreciate most about this response is that it does not chase easy answers. It acknowledges complexity, uncertainty, and responsibility.

So I am curious. When you think about the innovation the world needs now, do you think first about technology, or about mindset?

https://zurl.co/kTAeb

09/01/2026

Risk has quietly become a dirty word inside many organizations.

In this clip, I reflect on my interview with Stephen Parkins who explained something I hear far too often when speaking with innovation leaders and CFOs.

Companies say they want innovation, but the moment risk enters the conversation, the instinct is to retreat.

Stephen makes a simple but uncomfortable point. Exposure is not recklessness. If you invest in the stock market, you choose what you are exposed to. If you are a bank, you should understand finance deeply enough to take informed bets. If you are a food company, you should understand demand well enough to invest with confidence. Innovation works the same way.

When risk is treated as something to avoid at all costs, culture shifts in subtle ways. Innovators start protecting themselves. Forecasts become conservative. Teams chase easy wins. Difficult hypotheses are postponed. Uncertainty is avoided rather than explored. Progress looks good on slides, but very little real value is created.

That is how organizations drift into innovation theater without realizing it.

The question this clip raises is uncomfortable but necessary. Are we actually choosing where we want exposure, or are we spreading ourselves thin so we can say we took no real risks at all?

I am curious how others see this. How does your organization decide where it is willing to be exposed, and where it is not?

https://zurl.co/ArzRK

08/27/2026

One of my favorite moments from my conversation with Amy Freeze Meteorologist came from a place no innovation lab could ever design. Burnout.

After decades in broadcast meteorology, moving from Portland to Denver to Philadelphia, Chicago, and New York, Amy hit a moment many high performers quietly recognize. Working nonstop. Feeling automated. Running on repeat.

Her pivot into AI did not start with a grand strategy or a Silicon Valley pitch deck. It started while changing a refrigerator filter.

She went to YouTube for help and watched the algorithm surface independent weather creators holding hundreds of thousands of people during live events. Basement studios. Solo explainers. Entire audiences built outside traditional media.

That was the moment she realized the rules had already changed. This clip is a reminder that innovation often arrives when experience meets curiosity, and when exhaustion creates clarity. Sometimes the future does not knock politely. Sometimes it shows up disguised as changing a water filter.

I would love to hear this from others. Have you ever had a turning point that came from the most ordinary moment?

Watch the clip and share your story

https://zurl.co/w6Ex4

08/25/2026

During the summer holidays, I'm reflecting on the most popular episodes of 2026. This week, Im re-airing my podcast chat with Amy Freeze Meteorologist.

In this clip, she explained something many AI debates miss completely.

Not all information needs a human in the loop. But some information absolutely does.

Amy broke it down in a way that immediately clicked for me. There are questions with absolute answers. Is there a weather watch in the area? Is there a warning right now? That kind of information needs speed, accuracy, and repetition. That is where a digital twin or avatar can step in and do the work reliably, over and over again.

Then there is the other side. The personal context. Will my kid’s baseball game get rained out? What does this storm mean for my street, my house, my plans? That is where human judgment, experience, and trust still matter deeply.

What struck me was how calmly she dismantled the fear around jobs. Creating a digital twin does not remove the expert. It depends on them. The avatar only knows what the human teaches it.

The automation handles the repeatable work so the person can focus on nuance, relationships, and one on one connection.

This clip reframes AI in a way I think more leaders need to hear. Scaling does not mean disappearing. It means choosing where your human time is most valuable.

I am curious how others see this. Where do you draw the line between automation and human judgment in your own work?

https://zurl.co/SfYdI

08/21/2026

Many organizations say they want people to experiment, but their expectations tell a different story.

Kevin Surace argues that one of the biggest mistakes large companies make is placing everything behind one innovation project and then expecting it to succeed. His alternative is much closer to the way venture investors operate.

Try multiple ideas. Invest a smaller amount in each. Learn from customers. Watch for product-market fit and timing. Then place more resources behind the opportunities that begin producing evidence.

The difficult part is accepting what this means for the projects that don’t work. Kevin believes the people behind an unsuccessful experiment should not automatically be associated with failure. In some cases, he argues they should be rewarded for taking the risk and generating the learning.

There is an interesting leadership question here. Organizations cannot ask employees to pursue ideas with uncertain outcomes while making those same employees afraid of what happens when an experiment fails.

An innovation culture is shaped not only by which ideas leaders fund, but by what happens to the people behind the ideas they stop funding.

Does your organization really reward experimentation, or only the experiments that succeed?

https://zurl.co/X82he

08/20/2026

Long before Siri and Alexa became part of everyday life, Kevin Surace and his team were asking a much simpler question. What happens when someone leaves their desk?

In the late 1990s, the internet had arrived and people could access email, calendars, contacts, and other information from their computers. The moment they walked away, much of that access disappeared.

Kevin saw the problem and wondered whether technology could give ordinary people something he already had: an assistant. His team created Mary, a virtual assistant that could communicate using natural language, recognize callers, answer the phone, and even arrange meetings on Kevin's calendar. This was 1998.

What stands out to me is that the idea did not begin with a desire to create artificial intelligence. It began by observing a problem. That distinction feels increasingly important as organizations race to develop AI products, agents, and experiences.

Starting with the technology can leave teams searching for somewhere to use it. Starting with the customer creates a reason for the technology to exist.

Kevin's story is a wonderful example of storytelling for AI innovation because the breakthrough is easier to understand when we first understand the human frustration behind it.

Is your organization starting its AI conversations with what the technology can do, or with what customers actually need?

https://zurl.co/qDpBo

08/18/2026

Curiosity is often treated like a personality trait. Kevin Surace sees it as something much more valuable: a way of finding problems worth solving.

Kevin's pioneering work on virtual assistants helped create the path toward technologies such as Siri and Alexa, but when I asked where his instinct for innovation came from, he did not talk about intelligence, patents, or technological expertise. He talked about curiosity.

As a teenager, Kevin took apart radios, televisions, tape recorders, and anything else that allowed him to understand how things worked. That habit stayed with him.

His argument is simple. If you want to innovate, you first need to notice where people are struggling. Curiosity helps us ask why something works the way it does, why a customer accepts a frustrating experience, and whether a problem everyone has learned to tolerate could actually be solved. Technology comes later.

I think that distinction matters enormously at a time when organizations have access to more powerful AI tools than ever before. Technology can give us new ways to build solutions, but it cannot decide which problems are worth solving. It all begins with paying attention.

Watch this clip from my conversation with Kevin Surace on the Innovation Storytellers Show.

What customer frustration has your organization become so accustomed to that nobody asks why it still exists?

https://zurl.co/vKnCK

08/14/2026

What is the innovation the world needs most right now? Ron Johnson’s answer was not another device, platform, or AI breakthrough. It was a better way for people to connect.

In this closing clip Ron reflects on the Apple team he joined in 2000 and why he would choose to be part of that same group again. His explanation challenges the familiar image of innovation being driven by a lone genius.

At Apple, progress came from bringing a small group of talented people into a room, allowing different experiences and perspectives to meet, and creating an environment where the strongest idea could win.

The objective was not to protect individual agendas. It was to solve the problem together.

Ron also considers the contradiction at the heart of modern technology. We have more tools for communication than any previous generation, but many of us are becoming increasingly isolated from the people and places around us.

He remains optimistic about AI because it can give people something genuinely valuable: time. But saving time is only meaningful if we make thoughtful choices about how we use it.

Do we fill every spare moment with more content, notifications, and digital noise? Or do we use some of that time to convene, hold better conversations, and reconnect with one another?

Maybe the next great innovation will not be defined by what technology allows us to do but by what it gives us the time to become.

How could your organization use the time saved by AI to create more meaningful human connection?

https://zurl.co/peoSi

08/13/2026

The Genius Bar could have been called the Geek Bar. That was the name Steve Jobs suggested when Ron Johnson first presented the idea for a place where Apple customers could receive friendly technical support.

Ron pushed back because he understood that the name would influence far more than the sign above the counter.

“Genius” was aspirational. It gave customers confidence that they would receive expert help, while giving employees a role with meaning and status. “Geek” would have reinforced the same fear and exclusivity the Apple Store was designed to remove.

The eventual name told customers what to expect, helped attract the right employees, and became one of the most recognizable parts of the Apple Store experience.

It is a useful reminder that language does not simply describe an innovation. It can determine how people understand it, whether they trust it, and whether they want to become part of it.

Watch this clip from my conversation with Ron Johnson.

How much attention does your organization give to the names attached to its biggest ideas?

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