Embracing the AI future

In 1967, I began my first job working with computers. The company was presciently named International Data Highways (IDH), the brainchild of my remarkable mentor, Charlie Ross. Even in the infancy of computing, Charlie was pushing the boundaries of what computer science could achieve. He envisioned a world where financial and business information would be instantly accessible via terminal. His foresight was extraordinary, especially considering the limitations of the time.

Charlie was a visionary, driven by possibilities invisible to others but clear as day to him. He created an environment where curiosity was expected and boldness rewarded. It was a heady environment for a 19-year-old to be thrown into—and Charlie believed in throwing people in the deep end. He wanted his team to be brave, empowered, and unafraid to fail. This mindset was radical in 1967 Britain, where conformity and rigid corporate hierarchies ruled.

That early baptism by fire prepared me for the revolutionary journey computers would take over the next half-century. Little did I know that I had joined the most transformative industry the world had ever seen.

The rise and fall of giants

The first computer I worked on was the Sperry Univac 418—a massive, complex machine with a 24-bit word structure and a 12-bit addressing mechanism. It used a storage device known as a FastRand drum, which weighed two and a half tons and could store a mind-bending 100 megabytes of data. In those days, IBM dominated the industry with batch processing, while Sperry and others pushed the frontier of real-time computing.

IBM’s market share in the early 1970s was nearly 80% of the global computing market. But by the 1990s, the once-mighty firm teetered on the edge of collapse. Agile, innovative players like Digital Equipment Corporation and Data General had emerged, and IBM’s fall was swift and brutal. Watching this unfold in real time impressed upon me one core truth: this is an industry where today’s titan is tomorrow’s toast.

Much of this volatility can be traced to Moore’s Law. In 1965, Gordon Moore predicted that the speed and capacity of transistors would double every 18–24 months. This exponential growth would continue to redefine the limits of possibility—not just in computing power but in how quickly innovation itself could accelerate. Two years after Moore’s prediction, I entered the industry. The rest is history—and we’re still writing it.

From constraints to catalysts

The innovations of the past five decades—mainframes, PCs, the internet, mobile devices—were the hors d’oeuvres. What we are now witnessing with AI is the main course. The difference lies not just in power, but in liberation. For most of my career, progress was constrained by the lack of computing power, limited storage, and slow processing speeds. Cloud computing, distributed architecture, and global broadband have obliterated those limits.

Today, we operate in a world of universal access. Storage is cheap and nearly infinite. Computing power is on demand. Barriers are gone. And with that, we have opened a new door—one that leads not to incremental improvement, but to a new industrial revolution.

This is not a wave. It’s a tsunami.

Those sitting comfortably on the beach, sipping tea and admiring the view, are about to be swept away. Those who grab a surfboard and paddle out to meet the surge head-on will experience the ride of a lifetime.

AI: the great equalizer

Perhaps the most stunning transformation AI brings is the democratization of knowledge. For centuries, information was locked behind paywalls—academic, professional, institutional. In some industries, guild-like structures guarded specialized knowledge jealously. AI changes that. It is the ultimate key, unlocking access for anyone with a connection and curiosity.

Professional hierarchies will flatten. Management will face new levels of transparency and accountability thanks to real-time analytics. Strategic decisions once made in echo chambers will now be data-informed and challengeable.

This will not be a time for the timid. It will favor the bold, the agile, the open-minded. Yet the true revolution lies not in how companies operate—but in how people live, learn, and grow.

The coming reinvention of education

Education may be the sector most radically transformed by AI. For too long, students have been shuffled through one-size-fits-all classrooms, forced to memorize facts, and judged by standardized exams. AI opens the door to personalized, adaptive learning—customized in real time to each student’s strengths, weaknesses, and interests.

Imagine a system where students are assessed continuously through participation and engagement, not just snapshots on test days. AI can identify knowledge gaps and tailor content dynamically—favoring subjects that spark passion, curiosity, and intrinsic motivation. Students will no longer be treated as production units that must progress at the same pace. They will be treated as individuals.

Parents will no longer need to buy homes in expensive school districts to access quality education. World-class learning will be accessible to everyone, everywhere. Finally, education will be democratized—just as knowledge is.

Compare this to China’s Gaokao, where every high school student takes a life-determining university entrance exam on the same day in June. Should a teenager’s future be determined by two days of testing—or by twelve years of continuous growth and learning? AI makes that question more than rhetorical. It makes a new model possible.

Unleashing human creativity

Beyond education, AI promises to unlock a renaissance of human creativity. By automating repetitive and menial tasks, it will free the mind to focus on imagination, problem-solving, and innovation. AI will allow people to color outside the lines again—something that corporate culture and standardized education often suppress.

Innovation will no longer come just from elite R&D labs or top universities. It will come from a billion creative minds newly empowered. AI will not just be a tool of efficiency—it will be a force of liberation.

Conclusion: embrace the future

Looking back on my 57-year journey—from machine code to machine learning—I’m reminded of how much has changed, and yet, how many principles remain the same. Vision, courage, curiosity, and resilience remain the essential traits of any innovator.

The tools may change. The pace will accelerate. But the opportunity—for impact, for growth, for transformation—has never been greater. We stand at the edge of something vast. The surf is up and the surfboards are ready.

Let’s enjoy the ride.

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