Perspectives from ISB

Every once in a while, a new technology shows up and promises to change everything. Think steam engines, electricity, the internet… and now – Artificial Intelligence.

From boardrooms to policy circles, AI is being called the next General-Purpose Technology (GPT) – a class of innovations so powerful, they transform every industry. But here’s the twist: while we see incredible demos and headlines, the real-world productivity impact of AI still feels underwhelming. So, is AI really the new electricity? Or just another overhyped gadget in the tech toolkit?

In this blog, we explore the difference between hype and historical patterns, and why understanding AI’s trajectory through the lens of past GPTs could be the key to unlocking its long- term value.

First, What Makes a Technology “General-Purpose”?

A GPT isn’t just a great idea – it’s a foundational shift. GPTs spark other innovations, cut across
industries, and boost productivity at scale.

Electricity, for example, didn’t just light up homes. It restructured factories, birthed new workflows, and powered decades of growth. Same with Information and Communication Technology (ICT), which eventually led to everything from CRMs to cloud computing. GPTs don’t explode overnight. They evolve, scale, and then dominate.

Why People Believe AI is the Next Big Thing

AI’s rise has been staggering.

  • AI patent filings saw two major surges – around 2007 and 2014, tracking breakthroughs in machine learning. During this period, AI expanded its influence across an array of fields, including healthcare, finance, manufacturing, retail, and so much more.
  • Venture capital bets on AI startups spiked after 2016, especially with deep learning in the spotlight.
  • By 2021, the number of AI unicorns had surged impressively, reflecting the high hopes people have for AI-driven businesses.

These numbers are strong signals that AI is being taken seriously as a game-changer. And let’s not forget: AI isn’t just producing outputs—it’s redefining how outputs are created, from drug discovery to content generation. It’s a method of invention. That’s classic GPT behavior.

But, Where are the Productivity Gains?

Here’s the catch: for all the hype, global productivity hasn’t skyrocketed.

A 2023 McKinsey survey revealed that AI adoption actually plateaued. The Stanford AI Index showed a 26.7% drop in private AI investment in 2022. AI job postings slowed down in several regions. And economists like Larry Summers and Robert Gordon have pointed out that productivity growth stayed sluggish throughout the 2010s—even as AI boomed.

Sound familiar? It should. In the early years of electricity and computers, productivity barely budged. It took decades—and many failed attempts—before the real gains arrived.

Why the AI Boom Feels Slow (But Isn’t)

Think of AI like electricity in the 1890s. The potential is real, but the supporting systems aren’t fully in place. Factories back then had to redesign layouts to use electric motors. Today, businesses need to redesign workflows, upskill teams, and invest in data infrastructure to use AI effectively.

We’re still in the transition phase – the awkward, expensive, slow-moving middle. That doesn’t mean AI won’t deliver. It just means we’re not there yet.

What Smart Leaders Should Do Right Now?

If you’re a decision-maker wondering whether to pull back or press forward on AI—here’s the takeaway:

Don’t get distracted by the current slowdown. Focus on building the complementary capabilities that unlock AI’s power. That means:

  • Rethinking business models
  • Training teams
  • Upgrading systems
  • Embedding AI into core strategy

The companies that succeed won’t be the ones that simply “use AI.” They’ll be the ones that reinvent themselves around it.

Wrapping Up

AI may not be changing the world overnight. But neither did electricity or the internet. The path to transformation is rarely a straight line.

So, is AI a passing fad? Definitely not.

But is it guaranteed to change your business? Only if you put in the work to make it happen. The real winners in the AI era won’t just adopt new tools, they’ll build the future around them.

Curious to explore the full research-backed take on this? Read the original article by ISB: Sorting Hype from Reality: Advancing AI as a General-Purpose Technology

Author’s Bio:

Anand Nandkumar
Associate Professor, Strategy Executive Director – SRITNE

He explores industry and firm level phenomena that influence innovation – the generation of new ideas and entrepreneurship – distribution and commercialization of new ideas. His research focuses on high technology industries such as pharmaceuticals, bio-technology and software, and it falls in between industrial organisation (IO), economics of technological change and strategy. Professor Anand current work in the innovation stream examines the effect of stronger IPR on different aspects of innovation such as the influence of stronger patents on long run incentives for innovation or the influence of stronger patents on the functioning of Markets for Technology (MFT). In the entrepreneurship stream, his current work examines the influence of venture capitalists on entrepreneurial performance.

Professor Anand graduated with a PhD in Public Policy and Management, with a focus in strategy and entrepreneurship from Carnegie Mellon University in 2008. Prior to his PhD, he worked for about 3 years with a start-up in the Silicon Valley and prior to that in New York City with one of the world’s largest financial services firm. True to his expertise, at the ISB, Professor Anand teaches Strategic Innovation Management and Strategic Challenges for Innovation based start-up’s.

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