by Robyn Bolton | Jul 29, 2026 | AI
Peak profit is a good news/bad news sort of thing. It’s good news when other metrics, like revenue, customer satisfaction, and employee engagement, are also at their peak. It’s bad news when it signals that you’re in the endgame of disruption. But how can you tell which situation you’re in?
Most students of Creative Destruction or Disruptive innovation will tell you it’s a “bad news” situation if peak profit is preceded by the launch of a radical new technology. They’re partly right.
But it’s not the technology that should scare you. It’s the new business model it unleashes.
What is a business model?
“Business model,” like so many other words popularized during innovation’s heyday, is a buzzword that everyone uses and no one defines in the same way.
A business model is how an organization creates, captures, and delivers value.
That’s it. It’s that simple.
What’s not simple is how to represent all the types of business models, how they work, and what elements make them work. That’s why the Business Model Canvas became so popular. It made visible an interrelated system of decisions that was once assumed, or worse, unknown.
Changing any one element of a business model typically requires changes to other elements, resulting in a new business model.
is also why it’s so hard for existing companies to change their business models or even copy successful new ones.
As a result, companies don’t change their business models unless they’re forced to. Usually by a new technology.
When does disruption actually occur?
When a new technology bursts into the market, it’s an event. The new tech is suddenly everywhere: on the news, in stores, dominating our conversations. It becomes a “where were you when” moment. Where were you when you first logged on to the internet (Miami University’s computer lab, fall 1995)? Used a smartphone (Natick, 2007)? Prompted ChatGPT (Watertown, winter 2022)?
What isn’t an event, but is far more disruptive, is the business model that emerges from the new technology:
While new business models are appearing more quickly after the debut of new technologies, it still takes years for the new business models to “prove” themselves in the marketplace. That’s why it’s so easy to dismiss them even if, like Borders and Blockbuster, you see them emerging.
Why should I worry about it now?
As Hemingway wrote, “How did you go bankrupt? Two ways: Gradually, then suddenly.”
I’m sure executives at Borders and Blockbuster never thought they would be able to speak from experience when quoting that line. I’m also sure there are at least a dozen CEOs right now, reaping the rewards of record revenue and profits, thinking the same thing.
After all, AI and LLMs felt disruptive in 2022 but by 2026, companies have harnessed the technology’s power to cut costs, increase efficiency, and maximize profit.
But in just the last 90 days, people have started to openly discuss the need for new business models:
- SaaS: From seat/feature pricing to outcomes
- Marketing agencies, law firms, and consulting: From charging by the hour to value delivered
- Network operators: From usage-based (volume) to per-connection pricing
How much time do you have?
The disruptive technology is here. The new business models it’s driving are appearing. Peak profits and revenue aren’t far behind. The question you need to ask is how long will it take for “gradually, then suddenly” to hit your business?
Special shoutout to my friends at Jedi On the Fly for their research support via their Jedi Signals intelligence platform
by Robyn Bolton | Jul 21, 2026 | Leadership, Leading Through Uncertainty, Stories & Examples
“Disruption [is] driven by the pursuit of profit. That’s the causal mechanism for these things…”
Clayton Christensen at the 2011 Gartner Symposium ITExpo
When I told a client that peak profit was one of the signs that they were about to be disrupted, his jaw fell open. He didn’t believe me because, like any businessperson, achieving record profit is THE reason to celebrate. His company had just doubled revenue in the past five years and was positioned to double again in the next five. AND they supply mission-critical systems to build out data centers.
Business literally could not be better.
Which is exactly what the CEOs of Big Steel thought in 1968.
It wasn’t too big to fail.
“US Steel posted record profit margins in the years prior to unseating by the minimills; in many ways it was blind to its disruption.”
Clayton Christensen in HBR
Since the mid 1850s, steel was produced in integrated steel mills that performed every function required to produce the material that was building America. The costs to build a mill were high, about $8B in today’s dollars, and, to operate efficiently, mills ran 24/7 to produce at least 2M tons of steel per year.
In 1968, a metallurgist at Nucor invented something called the minimill. It could only perform half of the functions of an integrated mill and produced only rebar, the lowest quality of steel. But the minimill cost only $6M and could be profitable at just 50,000 tons of production.
Christensen called the minimill “not good enough.” He was being nice. The minimill was a joke.
Rebar was a joke, too. At just 4% of the steel market, it had the lowest gross margin of any type of steel. Ceding it to minimills freed up integrated mill capacity to produce more high profit steel. By 1977, Nucor was the leading manufacturer of rebar.
It had also spent 7 years improving the minimill.
The pattern continued:
- 1984: Big steel cedes the angle iron, bars, and rods to Nucor
- 1989: Bethlehem Steel’s market value jumps to $2.4B, from $175M just 3 years earlier
- 1993: Minimills directly compete with integrated mills in all segments of the market.
- 1995: Bethlehem Steel’s primary plant ceases operations
- 2001: Bethlehem Steel files for Chapter 11
- 2003: Minimills production exceeds integrated mills while Bethlehem Steel ceases to exist.
By 2017, only 9 integrated mills were still operating in the US, compared to 111 active minimills. The disruption took 35 years to play out.
You don’t have 35 years
The steel industry isn’t the only example:
| Company |
Time to Disruption |
Peak |
Disruption |
Disruptor |
| Sears |
30 years |
1969: World’s largest retailer |
1999: Removed from Dow Jones Industrial Average |
Walmart, Kmart, Target, Amazon |
| Kodak |
16 years |
1996: Record $16B revenue |
2012: Filed for Chapter 11 bankruptcy protection |
Digital photography |
| Blockbuster |
6 years |
2004: Record revenue: $6B |
2010: Filed for Chapter 11 bankruptcy protection |
Redbox, Netflix |
| Nokia |
7 years |
2007: Record Net Profit $51B, 40% of global handset market |
2014: Handset business sold to Microsoft for $7.2B |
iPhone, Android |
| Intel |
3 years |
2021: Record revenue $79B |
2024: Worst ever stock year as price goes below $18/share |
TSMC, Nvidia |
It’s happening right now. Are you seeing it?
“Financial results measure how healthy the business was, not how healthy the business is. Financial results are a particularly bad tool to manage disruption, because moving up-market feels good financially.”
Clayton Christensen and Michael E. Raynor, The Innovator’s Solution
Executives and shareholders may feel good right now because, despite supply chain disruptions and high interest rates, earnings are buoyed by “margin expansion” and “revenue beats.” AI feels like an opportunity, not a threat. And there’s no reason to believe that tomorrow’s results will be worse than today’s numbers.
It’s exactly how the CEOs of Big Steel felt in 1968.
You still have time to find the joke.
by Robyn Bolton | Jul 14, 2026 | AI
You could practically hear the soaring, triumphant anthem playing over a scene of unwashed yet unbowed humans crawling out of hiding as the machines’ ominous hums slowed and the evil tech overlords realized that their reign was ending.
“Ford’s AI Hiccups Lead Carmaker to Rehire ‘Gray Beard” Engineers’ the Bloomberg headline proclaimed.
It was only one company, but the news was received as if winning this battle foretold winning the war.
Sure, other companies, like IBM, Commonwealth Bank of Australia, and Klarna, rehired humans after AI-motivated layoffs. But the Ford decision just hit different because of the honesty that accompanied the announcement: “Mistakenly we thought that by just introducing artificial intelligence and ingesting the design requirements that we had, that that would produce a high-quality product.”
It’s the honesty, more than the action, that signals a new era emerging.
The fever dream takes hold
Since ChatGPT burst onto the scene in November 2022, companies scrambled to “adopt AI” and cram it down employees’ throats in the most striking demonstration of the Red Queen hypothesis since Lewis Carroll penned the words, “Now here, you see, it takes all the running you can do, to keep in the same place.”
The past three years saw a lot of running (and spending) with not a lot of progress. MIT reported earlier this year that 95% of AI pilots fail and even published an article titled, “What leaders still get wrong about AI” listing the following;
- Treating AI as something you do, not a tool to get results
- Starting AI projects without a clear path to value
- Getting stuck in pilots instead of scaling
- Overlooking how AI changes the business itself
- Mistaking productivity gains for value
Two months after publication, there are signs that leaders are starting to get things right.
Signs we’re waking up
After spending $2.5-$3T between 2022 and 2025, companies’ approach to AI isn’t going to change overnight. But there are indications that leaders are learning and adopting new strategies for AI adoption and implementation.
Executives are admitting mistakes.
After boldly committing to AI and promising step-changes in efficiency, innovation, and earnings, executives are moderating their tone and even admitting their mistakes:
- “Artificial intelligence is a fantastic tool, but it’s only as good as the information you use to train it.” Charles Poon, VP Vehicle Hardware Engineering , Ford
- We “did not adequately consider all relevant business considerations…we should have been more thorough in our assessment of the roles required.” CBA announcing its reversal of AI-related job cuts
- “Really, investing in the quality of human support is the way of the future for us,” Sebastian Siemiatkowski, CEO of Klarna, when rehiring 700 customer service agents
Managers are changing who they hire
After years of layoffs, recent analysis indicates that technical jobs aren’t going away. They’re changing what’s required for success.
In a review of 2.85 million job descriptions posted between June 2025 and June 2026, researchers found a dramatic increase in skills related to “judgment, design, and accountability,” and a decrease in skills related to routine work like “boilerplate coding” and manual testing.
Companies are engaging employees
With 70% of large companies monitoring employee AI activity, it’s no surprise that fatigue and anxiety are increasing, trust is plummeting, and employees are resisting.
But in a switch from the authoritarian, top-down, “because I said so” AI implementation model of the past, companies are starting to engage employees as advocates and trainers. Some are going a step further and shifting their approach from “use AI” to “what tools, including AI, do you need to become the professional you aspire to be.”
Slow then fast
Just like waking up from a dream or crawling out of hiding after the apocalypse, the shift from “AI IS EVERYTHING!” to “AI is a tool” will take time. But the process is beginning.
