Copilot is great, isn’t it? This week I was putting together a concept document for our new People Leaders Programme, drawn from interviews with clients and transcribed internal brainstorms. The output was magnificent – months of discussions quickly became a synthesised plan, written with incredible, value-oriented language that was a major up-level from my usual scribbles. Copilot even helped me finalise the plan into a snazzy PowerPoint.
It was FINISHED! In just one day! It felt great!
It was one of those moments where the AI tools connected me to super-abundance:
- All the information at my fingertips
- Easy to manipulate and pull out the meaning
- Speedy to create mind-blowing stuff with minimal effort
If you’ve ever been to an all-you-can-eat buffet, you’ll know the feeling. Everything you could possibly want, right there, no waiting, pile it high.
We are living in the era of AI-enabled super-abundance. But what does it mean for leaders? I can see five consequences – and, fair warning, my productive day with Copilot doesn’t come out of it unscathed.
Consequence 1: when all information is on the table, choosing becomes the skill
Organisations before the AI era were built around scarcity: scarcity of information, scarcity of creation, scarcity of analysis and scarcity of synthesis.
Scarcity made knowledge valuable. It rewarded the people who could gather information, interpret it, turn it into insight and communicate it well. Professional mastery took time, commitment, talent and often an arduous apprenticeship. Quality was essential; speed was a premium.
AI flips that logic. It makes information, creation, analysis and synthesis cheap. We can now generate material almost at the speed of thought.
You’d think that would make leadership easier. It doesn’t. It moves the premium. At a restaurant, nobody is impressed that the chef managed to cook you a plate of slop. The skill is in what your chef chooses to put on the plate to make a delicious, coherent meal. In the same way, when production of information is abundant, the value moves to discernment – knowing:
- what is true
- what matters
- what is distinctive
- what is worth acting on
Economists saw this coming. Back in 2016, Ajay Agrawal, Joshua Gans and Avi Goldfarb argued that when machines make prediction cheap, the value of human judgement goes up.
So that’s the first consequence: leaders no longer win by accessing more material. They win by exercising better judgement over what the material means.
Consequence 2: fluent output creates false confidence
Back to my one-day lovefest with Copilot. It was immensely gratifying. It delivered a huge dopamine hit. I was absolutely confident that I had nailed the brief and was ready to ‘press publish’ on my work to the whole world.
Just as a last-minute quick check, I shared the plan with one of my training team. I mainly expected to be told that it was a brilliant, perfect, uniquely impressive plan.
I was sadly disappointed.
She pointed out a major flaw that would have stripped the very ‘Ginger’ essence of what we do from the programme and made it just like every other People Leaders Programme. Bye-bye competitive advantage.
That is the second consequence. Super-abundance doesn’t only give leaders more material; it gives them material that feels finished, but isn’t. The polish can be intoxicating. It can make even experienced professionals mistake fluency for quality, speed for mastery and completion for insight.
And it turns out I’m in very good company. A 2026 Workiva survey of 2,272 finance, risk and sustainability executives found that 84% are at least somewhat confident in AI output going into critical external reports without a human reviewing it. Meanwhile 26% of them say their own internal audits have caught AI-generated errors that had already reached the board or external audiences. Ouch.
What happens to the errors we haven’t even noticed?
It’s not just the C-suite. A 2025 study by the University of Melbourne and KPMG surveyed 48,000 people across 47 countries. Among employees using AI at work, 66% rely on its output “without evaluating accuracy”, 56% have made mistakes in their work because of it, and 57% hide that they’re using it at all.
We’re all feeling brilliant. We’re not all checking.
Consequence 3: super-abundance creates attention poverty
Here’s the thing about over-abundance of food: the more food there is, the less you value each bite. At a buffet, we race to shove all we can onto the plate, but we’ll happily pass the leftovers to the waiter at the end.
Information works the same way. As the economist Herbert Simon put it back in 1971, “a wealth of information creates a poverty of attention”. The more content we can generate, the less attention each piece receives. The problem is not that there is nothing worth eating; it is that there is too much to give each item the attention it deserves.
This cuts two ways for leaders.
First, you can’t possibly check it all. And we’ve known for a long time that humans are terrible at this kind of checking. In her 1983 paper Ironies of Automation, the psychologist Lisanne Bainbridge drew on wartime studies of radar operators to conclude that “it is impossible for even a highly motivated human being to maintain effective visual attention towards a source of information on which very little happens, for more than about half an hour.” Scanning a stream of mostly-fine AI output for the one thing that’s wrong is exactly that kind of job. Half an hour in, you’re nodding it through.
Second – and this is the one that should worry communicators – nobody can attend to everything you produce either. You can’t force people to consume what you send them. Producing more, or even producing better, doesn’t guarantee that any of it lands. In a world where everyone’s plate is already full, you have to earn the listening ear.
Yes, I’m aware that this includes these very words.
Consequence 4: abundance erodes the craft needed to improve the recipe
Let’s be honest: not everything at a buffet tastes good.
Researchers at BetterUp and Stanford have even given it a name. “Workslop” is AI output that looks like good work but isn’t. In their 2025 survey of 1,150 US desk workers, four in ten had been handed some in the previous month, and each helping took around two hours to sort out.
The deeper risk is that nobody cares enough to change the recipe. When the buffet is always being replenished, weak dishes stay in circulation, because the system rewards volume and speed more than craft.
And then something worse happens: the chefs forget how to cook good food. Perhaps they’ve got used to ordering in ready-made prawn tempura; perhaps they’ve got a Thermomix to speed up the processes. Over time, the person left to check the work may be the very person who has stopped using the skills needed to create it. So the safeguard quietly weakens over time.
It happens faster than you’d think. In a 2025 Lancet study, experienced endoscopists’ detection rate when working without AI fell from 28% to 22% after just a few months of working with it. These are senior doctors, not trainees.
Wharton’s Ethan Mollick asks the question that should be keeping every Head of L&D up at night: “How do you train someone to verify work in fields they haven’t mastered, when the AI itself prevents them from developing mastery?”
Consequence 5: autonomous speed weakens collective sense-making
Of course, if we’re offered the chance to do a week’s worth of work in under two hours, it would be irrational not to say yes. As humans, we are optimised for optimising.
But these bubbles of hyper-productivity cut us off from each other. No decent chef sends out a new dish without someone else tasting it first. But the faster we work alone, the fewer chances our colleagues get to taste, cross-reference, unsettle and improve the work before it hardens into output.
Atlassian’s State of Teams 2026 survey of 12,000 knowledge workers puts numbers on it: 87% say that with everyone in execution mode, they lack the time or capacity to coordinate, and half say teams have unknowingly worked on the same thing.
This is not the same as attention poverty or failed supervision. It is a social consequence. AI makes it possible for leaders to produce more alone, but leadership work has never only been production work. It depends on shared meaning, feedback, challenge and alignment. Without those, organisations risk creating polished material that only reveals its weakness when finally tested by another human being.
Which is exactly what nearly happened to me.
So where does this leave leaders and organisations?
It means the legacy culture of leadership is ill-equipped for the super-abundance challenge. Our organisations were designed for scarcity; AI forces a new way of coordinating how people communicate, challenge, make meaning and decide. We need more collaboration, more collective sense-making and feedback cascades that dare to unsettle silo work, our proclivity towards autonomy and the temptation to hide behind the output.
What does that look like on a Tuesday morning? Two habits to start with.
- Get a taster. Nothing AI-assisted leaves the building until it has been in front of a named human who knows the craft. And tell them AI was involved, so they know what they’re tasting. That is all my colleague did for me, and it saved the programme.
- Ask “so what?” – four times. Why does this matter to me? To my team? To my target audience? To the wider purpose of the organisation? If the output can’t survive those four questions, it isn’t finished, however polished it looks.
What would you add? If you want to dig deeper, read our article on Cognitive Debt.
Neither of the above habits is fast. Or ‘optimised’. That’s rather the point. Leaders need to build cultures that tolerate a bit of slowness, because that’s the precondition for successfully going faster.
Fail to slow down and we’re just doing stupid things faster.
This brings me back to my one-day Copilot lovefest. The real risk was not that the tool failed me. It was that it succeeded so fluently that I nearly stopped doing the most human part of the work: testing whether the output still carried the distinctive judgement, taste and relational intelligence that makes it valuable.
Perhaps the final leadership insight is this: in an age of super-abundance, brilliance is not the ability to produce more. It is the discipline to pause, connect, question and protect what only humans can recognise together.
Sarah Lloyd-Hughes
The UK’s leading inspiring speaking expert & best-selling author. Sarah Lloyd-Hughes is a multiple-award winning public speaking coach, founder of Ginger and author of “How to be Brilliant at Public Speaking” (Pearson).
