How IBM Lost Two Technological Revolutions — And How Google Avoided the Same Fate
A former IBMer’s reflection on strategic courage, cultural inertia, and the world after ChatGPT.
Two Companies, One Moment, Opposite Reactions
Two giants faced world-changing technological revolutions: IBM, which once dominated enterprise computing, and Google, the modern leader of internet infrastructure and AI research.
Both had resources, talent, and early advantages. Both had visionary warnings from leadership. Both saw the future long before it arrived.
Yet only one company adapted. The other resisted—and declined.
As a former IBMer, I experienced firsthand how IBM missed both the cloud revolution and the early AI revolution. Watching Google confront the rise of ChatGPT made the contrast unmistakable.
IBM’s First Miss: Cloud
Lou Gerstner, the legendary CEO who saved IBM in the 1990s, left the company with a clear vision: cloud and on-demand computing would define the future.
He was right. But IBM leadership after Gerstner chose to protect existing revenue streams instead of building cloud infrastructure.
What IBM leaders believed internally: AWS is losing money. Enterprises won’t trust Amazon. We’ll enter cloud when the market matures. Our enterprise brand guarantees victory.
Meanwhile, AWS was learning through iteration, investing in massive infrastructure, building developer loyalty, and accepting early losses to shape a new computing paradigm.
IBM defended the past. AWS built the future. By the time IBM took cloud seriously, the market was already gone.
The $130 Billion Mistake
From 2003–2013, IBM spent over $130 billion on stock buybacks. This boosted short-term earnings per share, which tied directly to executive compensation.
That money could have built three AWS-sized cloud platforms, or ten DeepMind-scale research labs, or a hundred OpenAI-scale organizations.
Instead, IBM optimized its financial metrics rather than its future. This is not a story about poor technology. It’s a story about misaligned incentives.
IBM’s Second Miss: Watson
In 2011, Watson’s Jeopardy! victory made IBM the global face of AI. It looked like IBM’s second major transformation.
What happened next became a textbook example of overconfidence without research depth.
IBM tried to commercialize AI far too early. Watson for Oncology was the most visible failure: MD Anderson Cancer Center spent $62 million on the project before abandoning it. Doctors reported dangerous or inaccurate recommendations. Memorial Sloan Kettering later ended its partnership as well.
Instead of building foundational AI science over a decade—as Google and DeepMind did—IBM attempted to sell AI as a finished enterprise product. The result: a public loss of credibility in AI just as the field was reaching breakthrough momentum.
The Cultural Root Cause
The $130 billion in buybacks wasn’t just a financial decision—it was a cultural one. When executive compensation is tied to EPS targets, every decision filters through a single question: will this hurt next quarter’s numbers?
This incentive structure shaped IBM’s entire organizational DNA. Leaders who protected existing revenue were rewarded. Those who proposed disruptive investments—the kind that lose money for years before paying off—were sidelined. Over time, IBM selected for caution and against risk.
The result: a company that couldn’t disrupt today’s revenue, even when tomorrow’s survival depended on it.
The consequences showed in talent flow. From 2015–2020, IBM experienced significant brain drain. AI researchers left for Google Brain and DeepMind. Cloud engineers went to AWS and Azure. Young engineers chose companies with faster culture and better tooling.
Talent is the strongest signal of a company’s future health. IBM’s best people left. Google’s best people stayed—and more joined.
Why I Decided to Leave IBM
For me, the turning point wasn’t dramatic—it was a slow realization.
I worked as a DB2 technical support engineer. I learned a lot, but I began to see that opportunities to grow were shrinking. The technical ecosystem was becoming outdated. Internal tools lagged far behind industry standards. IBM products were losing influence in modern developer communities.
At the same time, open-source ecosystems were exploding. Cloud-native tools were maturing. Deep learning was achieving real breakthroughs. Medical imaging AI was becoming scientifically meaningful.
I wanted to work with modern open tools. I wanted to dive deeper into AI, especially imaging and computational methods.
So I left. And that decision shaped my entire technical career.
My decision to leave was a personal escape from a culture that resisted the very change that was about to rock the entire tech industry years later. And when that moment arrived—the launch of ChatGPT—the contrast between my old company and the new leader became brutally clear
November 30, 2022: ChatGPT Launches
Now compare IBM’s decade-long hesitation with Google’s reaction to ChatGPT.
When ChatGPT launched, Google experienced a shock IBM never felt—or never admitted. Engineers immediately saw ChatGPT outperforming Bard. Internal threads exploded. Executives realized they were behind in public perception.
Within 24 hours, Sundar Pichai declared Code Red. AI became Google’s top priority. Major product plans were frozen. DeepMind leadership was called into emergency strategy sessions. The entire AI roadmap was restructured.
IBM denied cloud for years. Google acknowledged AI disruption instantly.
This is the difference.
Google’s Response: Fast, Structural, Courageous
Research consolidation. Google Brain and DeepMind merged into Google DeepMind—an unprecedented move unifying research and engineering under one elite unit. IBM never executed a reorganization this bold for cloud or AI.
Release culture transformed. Before ChatGPT, Google was overly cautious with long internal reviews. After ChatGPT: Bard launched quickly, Gemini followed, Gemini 1.5 introduced record-long context windows, and Android, Search, Pixel, Chrome, and Workspace integrated AI features within months. Google moved from careful perfection to execution velocity.
Company-wide alignment. Google reorganized itself around AI-first everything: Search, Cloud, Android, Chrome, YouTube. This wasn’t a slogan—it was structural reorientation.
Sustained research commitment. Google doubled down on multimodal LLMs, reinforcement learning, scaling laws, safety research, TPU acceleration, and long-context attention mechanisms. Meanwhile, IBM had stepped back from cutting-edge AI research for nearly a decade.
The Strategic Contrast
| Dimension | Google (Post-ChatGPT) | IBM (Post-Gerstner) |
|---|---|---|
| Leadership reaction | Immediate | Delayed / denial |
| Organizational courage | Merged elite research units | Never restructured deeply |
| Execution speed | Months | Years |
| Product philosophy | Ship, improve, iterate | Oversell, under-deliver |
| Research culture | Expanding | Shrinking |
| Talent flow | Top engineers join | Top engineers leave |
To be fair, IBM still does some things well. The Red Hat acquisition was strategically sound. Hybrid cloud has real enterprise value. Consulting and security remain strong.
But these are defensive positions. They don’t define the future.
Google is actively shaping the next decade of computing. IBM is participating from the sidelines.
The Lesson
The difference between IBM and Google isn’t resources or talent or early awareness. Both companies had all three.
The difference is what they did when disruption arrived.
IBM protected legacy revenue. Google restructured everything.
IBM denied the threat. Google declared Code Red.
IBM’s culture resisted change. Google’s culture adapted.
In today’s AI-driven world, only one kind of organization survives: those that choose courage over comfort, innovation over legacy, research over marketing.
Google proved this. IBM didn’t.
The question every company must now ask is simple: when your ChatGPT moment arrives, will you react like Google—or like IBM?
Your answer determines whether you lead the next decade or watch it from the sidelines.
The choice is simple, and it determines the fate of your company: Strategic Courage over Cultural Comfort.