Are we scaling productivity, or faking it?
While genAI is omnipresent, its value remains elusive.
Recently dubbed in a McKinsey study as “the genAI paradox,” nearly eight in ten companies use generative AI… yet just as many confess they’ve seen no real change to their bottom line.
Often described as a “scalable” solution, genAI is being slotted into workflows not because it solves the hard problems, but because it makes the easy ones even easier. It’s simpler to ask a chatbot to write an email or summarize a meeting, even if a human still needs to revise the result. And so we end up applying AI not to the rote tasks it’s best suited for, but the high-touch, human ones that need nuance.
This begs the question: genAI is “scalable” for what, exactly?
The trust gap is still wide. PwC’s 28th Annual Global CEO Survey showed half of CEOs expect GenAI to increase profitability—despite real results falling short of expectations. And still, only a third trust the technology enough to embed it into key processes.
The sentiment seems largely industry-agnostic:
- A 2024 Stack Overflow Developer Survey indicated only 2.7% of developers have high trust in AI accuracy (and 40.3% trust it “somewhat”).
- Adobe’s inaugural AI and the Creative Frontier Study showed most creatives agree AI will save time, but over half still believe it will cause harm by training on their work without consent.
- And an MX Technologies report on AI for finances showed over half of consumers trust AI for automated reminders and insights, but barely 40% trust it for investment and other financial advice.
In other words, when the stakes rise, we still bet on human judgment, as imperfectly less calculated as it may be.
We’re still far off from AI managing our wealth or doing our taxes… who’s responsible if the IRS comes knocking? And we’re still eagerly awaiting the automation of other things that, as humorist Baron Ryan put it this week, “make life hard.” AI-enabled laundry-folding robots, anyone?
For now, AI is largely abstracting away many creative aspects of life—ghostwriting our interactions, ideas, even our voices. And in the process, we risk diluting the very things that make great leaders worth following.
(People follow humans, not machines, into battle. The same goes for the boardroom.)
When scale replaces sincerity and ingenuity, we may witness higher output in less time. Maybe, if used right, we may even observe true gains in productivity. And, the long-touted promise: we might even free up space for deeper, more strategic work.
But until then, what do we lose?
The Editors
