AI Didn't Start with ChatGPT: It Started with Sputnik
As the soviet sphere became a real sphere orbiting earth, MIT saw the potential for computer cognition decades ago.
When your life flashes before your eyes - thanks to COVID gone wrong - that life highlights the importance of AI and expert systems I’ve been focusing on my entire life.
Sputnik jolted the world in 1957; by 1958 when GenX’s parents were young children and later generations an abstract thought, MIT had already spun up an Artificial Intelligence project. They weren’t demo-ing chatbots to investors—they were wrestling with how cognition itself might be modeled in silicon. So when someone in 2025 claims they’re “first” to fuse AI with business strategy, I can’t help but ask: first to do what, exactly?
Remember MYCIN? R1/XCON? Google?! (inventor of the technology that gives us chatty AI). Those expert systems were diagnosing infections, guiding mineral exploration, and configuring VAX computers while Gen Z’s parents were still swapping mixtapes. AI has been chomping on white-collar workflows for fifty years. The novelty today isn’t that AI meets strategy—it’s that the rest of the world finally noticed.
I’ve been doing this a long time.
1980-something: I don’t even remember the first expert system I created, an industrial print estimating and production control system. I was hooked.
2002: I file a patent describing a structured, logic-guided intake system for business decisions (published 2003). I purposefully didn’t “prosecute” it leaving it “open source” prior art preventing anybody from patenting the idea.
2003: I launch ValueInnovation.net, the first public site that marries AI-guided input with Blue Ocean Strategy. That quickly led me to the authors of blue ocean strategy Chan Kim & Renée Mauborgne and I created a practitioners tool, Createware, an an independent company
2003–2025: I keep refining, shipping, and hardening that core idea, joining INSEAD as a research fellow and writing it into apps then, later as generative AI matured, into the original work. The result is VSTRAT.ai—used by MBAs, execs, and, ironically, a plethora of people that now claim selective amnesia despite an audit trail wider than an LA highway.
AI is incredibly important and structured AI for professionals has been around for a long, long time. I found myself in a French hospital (thanks, Mr. COVID!) where a structured intake system would augment physicians just as it has business people, attorneys, physicians, nurses, and countless other professionals. It would help remember what to ask besides clarifying what to output whether for individuals or professionals.
The pattern repeats everywhere: a crisis reveals what should have been obvious all along. Lying in that French hospital bed, watching doctors juggle protocols and edge cases, I saw the same gap I'd been filling for strategists since the Clinton administration. It's not about replacing expertise—it's about structured thinking that doesn't buckle under pressure.
The real breakthrough isn't LLMs getting chatty. It's that we finally have computational horsepower to make structured reasoning accessible without a PhD in knowledge engineering. When I built those early expert systems, you needed LISP machines and months of rule-crafting. Now? The same logical scaffolding that took me years to code can be dynamically assembled by models that cost pennies to run.
I watch consultants pivot to "AI transformation" as if they invented fire, armed with the same PowerPoint templates they've been recycling since decks were created by hand, or maybe with Aldus Persuasion. Meanwhile, the actual work — the unglamorous business of encoding human judgment into executable logic— gets buried under hype cycles and venture capital theater.
The French hospital taught me something else: when stakes are high, you don't want creativity. You want methodical completeness. You want systems that remember what humans forget under stress. The diagnostic tree that doesn't shortcut to the obvious answer to an illness in your body or your business.
That's what structured AI has always been about. Not replacing thinking or cranking machine generated decks, but making sure the thinking gets done. Not automating away expertise, but ensuring expertise gets applied systematically. The technology finally caught up to the vision we've been chasing for decades.
So when the next wave of "AI experts" claims they're pioneering something revolutionary, I'll be here - along with the small cadre of others who’ve been doing this for decades - battle-tested and amused, watching history repeat itself with better graphics and worse memory.
My hope is to use this technology to make the world a little bit better place than we found it. It’d be nice if others felt the same.
For readers that haven’t, please check out an article Prof. Peter Zemksy and I published at INSEAD, The Future Isn’t Horizontal: AI’s Vertical Revolution and, of course, feel free to share this article.