Erik Brynjolfsson is in great demand. The US professor whose research focuses on the relationship between digital tech and human productivity is nearing the end of a European speaking tour that's lasted nearly a month. Speaking via Zoom as he prepares for his imminent lecture in Oxford, the director of the Digital Economy Lab at the Stanford Institute for Human-Centered AI is enthused by recent "seminal breakthroughs" in the field. Brynjolfsson's tour – which has included appearances at the World Economic Forum in Davos and the Institute for the Future of Work in London – is neatly timed, because the recent arrival of ChatGPT on the scene has been capturing human minds, if not yet hearts. The large-scale language model, fed 300 billion words by developer OpenAI, caused a sensation with its powerful capabilities, attracting 1 million users within five days of its release in late November 2022.

Under CEO Ginni Rometty's leadership, IBM has been undergoing its riskiest transformation since the Gerstner era. With massive bets on artificial intelligence, blockchain, and quantum computing, Big Blue is essentially using its massive inertia and deep pockets as the bluest chip in tech to drive innovation forward. After a few years questioning IBM's ability to execute on this world-changing vision, I trekked to the IBM Think 2018 conference – the company's largest conference ever, now that it has rolled its InterConnect, Edge, World of Watson, and PartnerWorld conferences into one massive Las Vegas shindig. The central lesson of the show: while IBM's bets are both massive and risky, it has chosen its bets wisely – hoping to get into the ground floor of world-changing trends that each promise to follow Moore's Law patterns of exponential growth. True, IBM still carries the baggage of legacy products and business models, and the Big Blue battleship is slow to turn, but if any of its bets pay off, IBM will once again be at the top of its game.

"Exponential emerging technological changes run counter-intuitive to the way our linear brains make projections about change, and so we don't realize how fast the future is coming." The concept of exponential technologies has been popularized by organizations like Singularity University, which defines it as technologies where the power and/or speed doubles each year, and/or the cost drops by half. One of the big challenges with exponential technology change in business is that – by definition – it starts off slow. In the early days, pilot projects can look like they're failing compared to the incremental improvements of more established approaches. The result is that the projects look like a bad deal, resulting in organizations taking too long to invest – until it's too late to catch up with those who adopted early.