Robot Writes Review, Human Falls Asleep

The promise of generative AI is tantalizing – better quality work, produced faster and with less effort. But what happens when that efficiency comes at the cost of something vital: our intrinsic motivation?

TLDR:

• AI-assisted work produces better quality outputs - longer, more analytical performance reviews and warmer, more personable emails
• When AI handles cognitive heavy lifting, we miss out on the satisfaction of solving problems ourselves
• People feel reduced ownership and control when AI generates content, leading to disengagement
• This motivation dip persists even when returning to non-AI tasks
• Organizations risk workforce disengagement, higher turnover, and potential skill stagnation
• Blend AI and human contributions rather than letting AI produce final outputs
• Design engaging solo tasks to counterbalance AI-assisted work
• Make AI collaboration transparent to maintain sense of partnership
• Rotate between AI-assisted and independent tasks throughout the workday
• Train employees to use AI mindfully, developing critical evaluation skills

Drawing on fascinating research involving over 3,500 participants, my AI agents (non human Google Notebook LM) dive into this compelling tension at the heart of workplace AI adoption. The data reveals a striking pattern: while AI collaboration significantly improves performance metrics (think more analytical performance reviews and warmer, more effective emails), it simultaneously triggers a roughly 20% drop in intrinsic motivation and a similar rise in feelings of boredom.

We explore the psychology behind this motivation decline, examining how AI can inadvertently hijack the cognitively demanding aspects of work – the very parts that often provide the greatest sense of accomplishment and ownership. When AI handles the heavy mental lifting, we lose those satisfying moments of wrestling with problems and finding solutions. This disengagement doesn't just affect AI-assisted tasks; it lingers even when we return to independent work.

For organizations embracing generative AI, these findings offer crucial guidance. Rather than avoiding this powerful technology, the research points to five specific strategies for thoughtful integration: blending AI and human contributions, designing engaging solo tasks, maintaining transparency about AI's role, rotating between AI-assisted and independent work, and training employees to use AI mindfully as partners rather than passively accepting its output.

Ready to harness AI's productivity benefits without sacrificing engagement? Listen now to discover how you can find the sweet spot where technology enhances rather than diminishes your sense of purpose and satisfaction at work.

Research: https://hbr.org/2025/05/research-gen-ai-makes-people-more-productive-and-less-motivated

Chapters

• 0:00 AI's Productivity Promise and Hidden Cost
• 1:55 Performance Benefits of AI Collaboration
• 3:08 The Motivation Dip: Boredom and Disengagement
• 6:41 Long-Term Risks for Organizations
• 8:03 Five Strategies for Effective AI Integration
• 12:14 Balancing AI Efficiency with Human Purpose

Transcript

Speaker 1: 0:00

So think about those tasks in your workday. You know the ones that require real brainpower, maybe generating fresh ideas, crafting persuasive emails, even those dreaded performance reviews. Now imagine a tool like pops up and handles those super fast, makes them sharper, quicker. That's kind of the promise of generative AI, right?

Speaker 2: 0:22

Yeah.

Speaker 1: 0:23

As it steps into our work lives.

Speaker 2: 0:24

Yeah, it's definitely appealing.

Speaker 1: 0:26

But what if that speed, that efficiency, it came at a cost, maybe hitting something vital like the drive that makes us want to do good work?

Speaker 2: 0:36

Well, that's exactly the crux of what we're digging into today. We've been looking at some really fascinating research, so there was this one study over 3,500 people involved.

Speaker 1: 0:44

Wow, that's a lot.

Speaker 2: 0:44

Yeah, and they were tackling the kind of work you probably do every day, sometimes with generative AI helping out, sometimes without it.

Speaker 1: 0:51

Okay, so real world stuff Totally.

Speaker 2: 0:53

Things like writing engaging Facebook posts, brainstorming ideas for projects, drafting those tricky marketing emails really practical applications.

Speaker 1: 1:02

And what's the headline? What jumped out from this research?

Speaker 2: 1:05

Well, it's this real push and pull, this tension. On one hand, generative AI clearly gives a pretty significant immediate boost to how well people do the tasks and how fast.

Speaker 1: 1:17

Okay, productivity win.

Speaker 2: 1:18

Definitely. But and this is the key thing there's the subtle, potentially quite significant downside hiding there. It seems to weaken our intrinsic motivation.

Speaker 1: 1:29

Intrinsic motivation.

Speaker 2: 1:30

Yeah, you mean that like internal desire, the enjoyment we get from the work itself off. What are the clear benefits of having AI as a sort of co-pilot? What are the less obvious psychological costs and, ultimately, how can we navigate this? How do we use this tech so we get the productivity and keep ourselves engaged?

Speaker 1: 1:52

Okay, let's start with the good news, then that immediate performance boost. What did the research actually show?

Speaker 2: 1:57

Yeah, the data there is pretty compelling. When people use generative AI in their workflow, the quality and the efficiency of what they produced it clearly went up.

Speaker 1: 2:06

Right Any specific examples.

Speaker 2: 2:08

Absolutely. Take writing performance reviews, for instance, something many managers do.

Speaker 1: 2:12

Not always fun.

Speaker 2: 2:14

No, but the study found that the reviews written with AI help. They were actually longer, they were more analytical and, crucially, the people getting the reviews said they were more helpful.

Speaker 1: 2:24

Oh, interesting, so tangible benefits there, definitely more analytical and, crucially, the people getting the reviews said they were more helpful.

Speaker 2: 2:27

Oh, interesting. So tangible benefits there, definitely. And it wasn't just for big formal things like reviews, even just, you know, drafting everyday emails. The AI assisted ones tended to come across as warmer, more personable. So, hitting the right tone, yeah, kind of hitting those emotional notes better, which is often tricky. It seems like the AI acts as this, like an always on editor brainstorming buddy Go ahead. Helping people put out work. That's just generally more polished, better structured. But and here's where we need to pivot a bit- Ah the.

Speaker 1: 2:56

But.

Speaker 2: 2:57

Yeah, the. But While the external results looked better, the internal experience for the person doing the work that often took a hit.

Speaker 1: 3:05

Okay, the internal experience. The person doing the work that often took a hit. Okay, the internal experience. Let's really dig into that. This is where it gets super interesting, right?

Speaker 2: 3:09

It really is. The research showed pretty consistently that participants who collaborated with generative AI on a task they felt a noticeable drop in their intrinsic motivation.

Speaker 1: 3:21

So less driven from within, exactly.

Speaker 2: 3:24

And it wasn't just a small thing. Feelings of boredom also went up significantly.

Speaker 1: 3:29

Boredom while using a cutting edge tool. That seems counterintuitive.

Speaker 2: 3:33

It does, doesn't it? But the numbers, they paint a stark picture. On average, we're talking around a 20 percent dip in intrinsic motivation 20 percent. Yeah, and a similar 20 percent increase in feeling bored for those using the AI. Now compare that to the control group people doing the same tasks just without AI. Their internal state pretty much stayed steady, which really highlights something important for you to think about, which is.

Speaker 2: 3:57

It's not just feeling less motivated while you're using the AI. That sense of disengagement, that boredom it can actually stick around, even when you switch back to tasks you do completely on your own.

Speaker 1: 4:08

Ah, ok. So it's like the AI it does its job, maybe too well on some parts, and when we go back to doing it ourselves, it feels what less stimulating, maybe dull, by comparison.

Speaker 2: 4:21

That seems to be a big part of it. Yeah, less stimulating, maybe even monotonous.

Speaker 1: 4:25

So what's going on underneath? Why the motivation drop? Why the boredom?

Speaker 2: 4:30

Well, it looks like there are a few connected things happening. The research suggests that when we work with the AI, it can kind of maybe inadvertently take over the most cognitively demanding parts of the task.

Speaker 1: 4:41

Hard-thinking parts.

Speaker 2: 4:42

Exactly the parts that are often the most well rewarding in the end. Think about that performance review again.

Speaker 1: 4:48

Okay.

Speaker 2: 4:48

There's critical thinking involved, right Evaluating performance, figuring out how to give constructive feedback, maybe problem solving, how to frame areas for improvement.

Speaker 1: 4:58

Right, the challenging bits.

Speaker 2: 4:59

Yeah, and when the AI does a lot of that initial heavy lifting, those key thinking processes can get bypassed. You know that satisfaction you get when you wrestle with a tough problem and finally crack it. Generative AI can sort of shortcut that struggle. The output might be good, maybe even great, but you miss out on that internal reward, that sense of accomplishment and maybe even the learning that happens during the struggle.

Speaker 1: 5:24

That makes total sense. It's like if you're doing a jigsaw puzzle and someone just slots in a huge section for you. You finish faster, sure, but you lose that feeling of I figured this out. Yeah, the engagement's gone, precisely.

Speaker 2: 5:36

And when the AI generates a big chunk of the content, people might feel a bit detached from it, less personally invested, like they aren't the real author.

Speaker 1: 5:44

A loss of ownership.

Speaker 2: 5:45

Yeah, a reduced sense of ownership, and that can easily lead to boredom when they then go back to tasks where they are fully responsible for creating everything from scratch. The study specifically found this initial AI collaboration can lower workers' sense of control.

Speaker 1: 6:00

Control interesting.

Speaker 2: 6:01

And that feeling of being the main driver, the primary agent of the work, and that feeling of authorship, you know, being in control of your creative output, that's a huge driver of intrinsic motivation.

Speaker 1: 6:13

So the very things that make work feel meaningful the challenge, the personal input, the feeling that you achieved it those can get sort of eroded if the AI takes too big a role.

Speaker 2: 6:24

It seems so subtly undermined.

Speaker 1: 6:26

And then, like you said, going back to working alone just highlights what feels missing now.

Speaker 2: 6:31

Exactly. The contrast becomes really noticeable. Those solo tasks might suddenly feel less enjoyable, less stimulating, which just chips away at motivation even more.

Speaker 1: 6:41

Okay. So if we zoom out a bit, think about organizations what are the potential long-term implications if companies lean really heavily on Gen AI for, say, creative work or complex thinking tasks?

Speaker 2: 6:54

Well, yeah, it paints a potentially concerning picture, doesn't it? If your workforce is consistently feeling less engaged, maybe more bored, that could easily translate into lower job satisfaction overall, maybe higher turnover, as people look for more stimulating roles and even potentially burnout over time.

Speaker 1: 7:10

Right burnout from boredom almost, or lack of fulfillment.

Speaker 2: 7:13

It's possible. And beyond just morale, there's this other risk losing chances to develop and sharpen those really essential human skills.

Speaker 1: 7:20

Like creative thinking, problem solving.

Speaker 2: 7:23

Yeah, if professionals are always leaning on AI for the first draft, the initial ideas, are they really honing their own creative muscles? Are they practicing their problem-solving grit?

Speaker 1: 7:36

Good point.

Speaker 2: 7:37

What happens to that sense of accomplishment you get from tackling a hard challenge and finding your own solution? It almost feels like we could risk a kind of a skill stagnation.

Speaker 1: 7:46

Where our own abilities in those key areas start to weaken because we're just not using them as much.

Speaker 2: 7:51

Yeah, relying on the AI instead. Exactly Through that over-reliance.

Speaker 1: 7:56

This sounds like we're navigating a bit of a minefield here, or at least walking a tightrope. So what's the answer? Just avoid generative AI. Is that what the research suggests?

Speaker 2: 8:04

No, not at all. Actually, the research is pretty clear on this. The solution isn't to ditch this powerful technology. It's more about being much more deliberate, more thoughtful about how we weave it into our work, how we design jobs and tasks with AI in mind. The study actually points to several really practical strategies companies can use.

Speaker 1: 8:23

All right, let's get into those practical steps. What can companies actually do to get the AI benefits without accidentally killing motivation?

Speaker 2: 8:31

OK. So the research pulls out five key approaches. First one blend AI and human contributions.

Speaker 1: 8:38

Blend them, how so?

Speaker 2: 8:39

So, instead of just having the AI spit out a final product, think of it more as a starting point or a collaborator. Let the AI draft an outline product. Think of it more as a starting point or a collaborator. Let the AI draft an outline, maybe generate some initial ideas, but then make sure that human expertise, personal insights, that unique perspective that's central to refining it, finalizing it like a performance review example again.

Speaker 1: 8:58

Right.

Speaker 2: 8:59

AI drafts a framework, maybe suggest some points based on data, but the manager has to personalize it. Add specific examples, nuance feedback, their own judgment that human touch is key.

Speaker 1: 9:09

That makes a lot of sense Leverage the efficiency, but keep the human value add front and center. Okay, what's strategy number two?

Speaker 2: 9:16

Second is to actively design engaging solo tasks, so to kind of counterbalance the potential downsides of AI collaboration.

Speaker 1: 9:24

Right, the boredom, the motivation dip.

Speaker 2: 9:26

Exactly. Companies should make sure strategically that employees also get regular chances to do tasks entirely on their own, tasks that give them autonomy, real intellectual challenge, a chance to solve problems creatively.

Speaker 1: 9:39

Mix it up.

Speaker 2: 9:40

Yeah, build on that email example. Maybe you use AI to help draft some routine messages, Fine. But then that same worker gets assigned to say independently, develop the strategy for a whole new marketing campaign.

Speaker 1: 9:55

Ah, ok, so they still get to flex those creative and strategic muscles fully.

Speaker 2: 9:59

Precisely. It provides that crucial balance Use AI for efficiency where it makes sense, but protect those opportunities for deep independent work and the satisfaction that comes with it. What's next?

Speaker 1: 10:10

Third strategy.

Speaker 2: 10:11

Third, make AI collaboration transparent. The research suggests that when people clearly understand how the AI is helping them, it can actually help them keep that sense of ownership and fulfillment. Just being open about what the AI is doing, what its role is, can reduce feelings of disengagement or feeling like you're just pushing buttons for a machine.

Speaker 1: 10:30

So less mystery, more partnership.

Speaker 2: 10:32

Yeah, fostering that sense of partnership with the tool rather than feeling passive or worse, replaced by it. Transparency builds trust.

Speaker 1: 10:40

Crucial in this landscape. Okay, number four.

Speaker 2: 10:44

Fourth is to rotate between tasks, so actually structuring workflows, so people regularly switch between AI-assisted tasks and fully independent tasks.

Speaker 1: 10:53

Like schedule it in.

Speaker 2: 10:54

Could be, or just design rules that naturally involve that kind of alternation. It's a really practical way to balance the productivity gains from AI with keeping employees engaged. You get the AI efficiency boost, but you also make sure people consistently get that mental stimulation from work that relies purely on their own skills.

Speaker 1: 11:13

Like shifting gears throughout the day to keep things fresh, keep the momentum, but also the engagement.

Speaker 2: 11:17

Exactly, it's a strategic way to manage workflow.

Speaker 1: 11:20

Makes sense. And a fifth and final strategy from the research.

Speaker 2: 11:24

The last one is super important Train employees to use AI mindfully, and this isn't just about teaching the buttons to click.

Speaker 1: 11:32

Right, not just technical training.

Speaker 2: 11:33

No, it's about helping people develop the ability to critically evaluate what the AI produces, to understand where AI can best complement their skills and where their own judgment is essential.

Speaker 1: 11:45

So empowering them to be smart users Exactly.

Speaker 2: 11:47

Fostering autonomy in how they use AI, encouraging them to experiment creatively with it and supporting their long-term growth. It's about making them thoughtful strategic partners with the AI, not just passive receivers of its outpin.

Speaker 1: 12:00

Okay, so wrapping this up, the big message here isn't really about fear, it's not avoid AI. It's much more about thoughtful integration, strategic design, being really conscious about how we bring AI into work so we get that balance right. Maximize the productivity stuff which is undeniable without accidentally draining our own sense of purpose, our engagement, the inherent satisfaction we get from doing good work.

Speaker 2: 12:26

That sums it up perfectly. Generative AI is, without a doubt, a really potent tool for boosting productivity, but this research makes it crystal clear Its impact on our motivation, our internal drive. That's a critical piece we have to actively think about and manage, designing our work, our workflows, thoughtfully. That seems absolutely essential if we want to unlock AI's potential effectively, without undermining the very things that make us feel good about contributing or proactively that this tech actually enhances, not diminishes, our sense of purpose our enjoyment in what we do, and what role does our own individual awareness, our own strategies, play in navigating all this?

Speaker 1: 13:14

It's definitely a crucial question for all of us, I think, to keep asking ourselves.