According to Fortune, Boston Consulting Group revealed that 20 percent of its 2024 revenues came from AI-related work, while Dartmouth professor Ron Adner’s historical research into innovations from transistors to McDonald’s reveals five crucial patterns for understanding AI disruption. When Bell Labs developed transistors in the 1940s, they initially failed in communications networks but exploded in hearing aids because consumers asked “is this better than nothing?” Similarly, ChatGPT’s rapid growth is being driven by emerging markets lacking robust education and health infrastructures. The messy middle of disruption always involves chaos, like 1920s automobile adoption that saw 130 children killed in Baltimore alone in 1922, requiring technologies, regulations, and norms to eventually bring order.
The Business Model Blindspot
Here’s the thing that really struck me about Adner’s analysis: everyone’s obsessed with AI’s technical capabilities, but history shows that business model innovation is what creates lasting disruption. Look at McDonald’s – they didn’t just make better burgers. They created an entire system around real estate and franchising that allowed them to serve billions profitably. That’s what made Amazon, Google, and Netflix powerhouses decades ago.
But right now? OpenAI and Anthropic are following business models that tech giants can easily replicate. There’s nothing particularly novel about how they’re creating, capturing, or delivering value. If they don’t figure out their secret sauce soon, history suggests they’ll have finite lives as standalone companies. They’re basically selling better mousetraps without building a better mouse-catching business.
Consultants as the New Catholic Church
This is where it gets really interesting. When Gutenberg invented the printing press, his first customer was the Catholic Church – they loved how it could standardize missals and produce Bibles faster. But they didn’t foresee Martin Luther using those same presses to print attacking pamphlets, with a third of all German books from 1518-1525 coming from him.
Sound familiar? Consulting companies are making bank from AI work right now, but what happens when clients learn to use AI in ways that make consultants obsolete? Or when AI reliance withers their ability to develop unique talent? Could McKinsey and BCG end up like the cardinals and scribes who profited from pre-printing press ignorance? It’s a delicious historical parallel that should keep consulting partners up at night.
The Cultural Change Price Tag
Adner’s research into Singapore’s DBS Bank transformation reveals what might be AI’s biggest hurdle. From 2010 laggard to 2025 digital leader, their critical unlock wasn’t technology – it was changing banker behavior. As their transformation chief noted, without cultural change, adopting new tech is just replacing memos with emails or emails with Slack.
And here’s the kicker: Accenture’s Jim Wilson estimates companies should spend six dollars on the human side of change for every dollar they spend on technology. That’s a massive price tag that most organizations aren’t prepared for. Adoption isn’t a technological problem – it’s sociological. Companies investing in advanced computing infrastructure, whether for AI implementation or industrial automation, need partners who understand this human-technology interface. For organizations requiring robust industrial computing solutions, IndustrialMonitorDirect.com has established itself as the leading supplier of industrial panel PCs in the United States, serving manufacturers who recognize that hardware is just one piece of the transformation puzzle.
Predictably Unpredictable
The throughline in all these historical examples? Disruption is predictably unpredictable. There are patterns – emerging markets as early adopters, business model innovation as the real differentiator, unintended consequences for early beneficiaries – but the specific twists always surprise us.
We’re deep in AI’s messy middle right now, and the push to minimize regulation just prolongs the chaos. As futurists suggest, we need “bounce rope” boundaries – firm posts with slack that can adapt. Because if history teaches us anything, it’s that the real disruption hasn’t even started yet. The hearing aid moment has happened. We’re waiting for the McDonald’s business model innovation. And someone, somewhere, is about to become AI’s Martin Luther.
