From Hype to Human Ingenuity: Leading Innovation in the Age of AI
- Kim Getgen
- Jul 8
- 5 min read
Everywhere I turn lately — conferences, podcasts, inboxes — I’m hit with AI. Another demo. Another startup. Another bold promise.
Don’t get me wrong — I just guest-starred on a podcast hyping AI, and I host one myself. I love technology. But even I’ve been feeling a bit of AI fatigue.
It’s not that AI isn’t useful. It’s that we’re stuck in a cycle of pitching, piloting… and pausing. We’re not short on ideas. We’re short on decisions.
That’s why my recent Power Perspectives episode came at the right moment. It gave me space to step back and talk about what really matters: How do we evaluate new AI ideas and turn pilots into purpose?
As I said on the show, AI has been “hitting me in the face” everywhere I go. So maybe its time to accept AI is here to stay and instead focus on the real questions we need to properly evaluate the best ideas from ones that are not going to move the needle. We need to ready to pilot with purpose and know:
What are we solving for?
Who owns the outcome?
Why does it take so long to decide — even when the risk is low?
That’s exactly why I was invited to the podcast: to reframe the conversation. To move past the hype cycle and focus on what it really takes to turn AI from potential into progress.
Spoiler: it’s not about the tools. It’s about the people, the process, and the decisions.
Let’s talk about what’s really holding innovation back — and how we move forward.
1. New AI Ideas Require a Decision-Making Process, Not a Pitch Deck
Too many AI pilots start with excitement and end with... indecision.
They often kick off with a slick vendor demo, because let’s face it, the pressure is on to show something new, something smarter, something with more AI than the last pitch. Everyone’s chasing the next breakthrough, and that’s how we get caught in the hype cycle. But what we really need is simple: a better way to solve critical problems.
Even the most promising pilots often stall, not because the tech failed, but because the organization wasn’t ready to decide what’s next.
What’s missing isn’t just the learning. It’s the structure for what to do with the learning, and how to set the right expectations at each stage gate so you can confidently move from one step to the next.
At InnovationForce, we’ve seen the most successful utilities treat innovation as a repeatable decision-making system. They start with tight challenge statements. Frame the solution, and don’t get wrapped around AI as the goal. They scope pilots to test hypotheses quickly. And, most importantly, they know what comes after the pilot.
They don’t let results sit in a slide deck. They ask:
Should we scale it?
Integrate it?
Learn and move on?
It’s the pilot with purpose. Because if your pilots don’t end with decisions, what are they really for?
2. The Risk Illusion: Why Are We So Afraid of 90-Day Pilots?
Here’s the paradox I can’t stop thinking about:
We’re offered low-risk, low-cost 90-day pilots — no disruption to operations — and still, it takes months to decide whether to start.
I see it all the time. Sometimes the answer is, “We don’t have the resources.” Fair enough. But more often, it’s: “We’re not sure,” which usually means no.
That’s why I call time the silent killer of innovation.
It’s easy to wait a new idea out. No confrontation, no conflict, just... inertia. And eventually, the idea dies a quiet death when indecision stalls the decision-making process.
We’ve built systems where even safe, fast-learning pilots get paralyzed, not by risk, but by the fear of risk.
We treat all innovation like its high-stakes, even when it’s not. That’s not managing risk. That’s avoiding responsibility for it. And in doing so, we miss the biggest risk of all: waiting too long and falling behind.
Here’s what smart organizations do instead:
Rank and score ideas with risk as a factor
Isolate pilots from production environments
Run controlled experiments
Learn quickly and act
And when resources really are tight? Don’t just say “no.” Say: “We’ve got two people focused on five priorities. Yours is number six, and it’s up next.”
That’s prioritization, not paralysis.
And it’s how we stay adaptive in a world that’s only getting more complex. Utilities have some of the smartest engineers on the planet. They know how to assess and avoid risk. So, let’s leverage their human ingenuity, because the biggest risk now is being left behind.
3. Culture Is a Wall. Capabilities Are the Wrecking Ball.
Culture gets blamed for killing innovation — and often it does. Rigid silos. Fear of failure. “This is how we’ve always done it.”
But here’s the shift we need: don’t wait for culture to change before you start innovating. It won’t.
Instead, build capabilities that drive the change you want to see.
When teams know how to run a pilot, test safely, and make decisions — that’s when culture starts to shift. Confidence grows. Curiosity kicks in. And creative tension becomes fuel for better ideas, not friction to avoid.
We’ve seen this happen in as little as 6–12 months at organizations that intentionally work the right behaviors into their innovation process — especially the ones outlined in Linda Hill’s research on Collective Genius:
Creative Abrasion – The ability to generate ideas through robust debate and diversity of thought. Not consensus, but productive disagreement.
Creative Agility – The ability to test and refine ideas quickly. Run experiments, adapt, learn, and iterate — without fear.
Creative Resolution – The ability to make integrative decisions that combine competing ideas into something better — instead of choosing either/or.
And maybe there’s a fourth “C” we need to start naming: Celebration. Not just of wins, but of learnings. Of movement. Of progress.
Because progress builds momentum. And momentum rewires culture from the inside out.
Culture isn’t a prerequisite. It’s a product of practice.
4. Innovation Is a Build/Buy Decision — We Just Don’t Treat It That Way
Here’s a hard truth: every idea that scales has to pass through procurement.
If your innovation process is disconnected from procurement, legal, cyber, and operations — your pilot is already at risk.
Too often, AI vendors sell to innovation teams. The pilot runs. It looks promising. Then it hits the real-world roadblock:
“Wait… who’s going to own this? Who’s funding it? Did cyber sign off?”
The fix? Treating innovation like a procurement decision from the very beginning can help improve the outcomes. Simply ask:
Should we build it?
Should we buy it?
Or should we partner to scale it?
This mindset helps you pilot with purpose:
Aligns key stakeholders from day one
Reduces friction later
Gives your pilots a real shot at life beyond the lab
I am seeing practitioners of this adopt 50% more pilots into production and that’s where the real ROI is waiting to be delivered back to shareholders and customers.
Conclusion: AI Isn’t the Hero — You Are.
It’s not just about AI finding a better way to move the electrons, its about the people. It’s about human ingenuity. AI and innovation, it turns out, is a team sport.
AI is the tool that lets us move faster and smarter — if we learn how to frame problems, test solutions, and make decisions with discipline and speed.
So next time you’re in a pitch meeting, ask:
What’s the problem we’re solving?
What’s our risk threshold?
How would we procure this technology?
What happens after the pilot?
Will we be able to capture the learnings.
Because the energy transition doesn’t need more AI hype. It needs more action and leadership. That's where you can step into the driver’s seat.