If you have a primarily desk-based job, then you likely spend roughly a fifth of your working week on presentations. That’s an entire day gone to slide creation. And nearly half of that time isn’t spent on thinking or analysis, but on design, aligning boxes, fixing fonts, wrestling with layouts. If you’ve ever stayed up until 2 am reformatting a slide deck for a board presentation, conference or lecture delivery, you know exactly what I mean.

Enter Generative AI

I’ve been working directly, getting my hands dirty and teaching AI skills to business people since 2023. I’ve seen how AI handles work tasks, writing and design, well and not so well. A reliable PowerPoint solution has successfully eluded me, perhaps until now. I enjoy designing materials and writing content, so I don’t mind spending time in the process, making sure it’s my voice and that “I know” the content. But sometimes, I just don’t have the time in my schedule to spend 8 or 10 hours on a 50+ slide presentation.

Generative AI for writing code? From my amateur standpoint, it seems remarkably good. Text? Very good, but with limitations you need to be aware of. Spreadsheets? I’m impressed so far, and AI seems to be increasingly competent. PowerPoint, however, has been the stubborn holdout—the task that AI seems to find genuinely difficult (think layout, image alignment, whitespace, text boxes, and animations).

There are third-party solutions like Beautiful AI, Make, and GenSpark AI, all of which are impressive based on my testing. But I don’t want another third-party tool to manage. I don’t want another subscription and the increased security concerns that come with it. I want to run the solution on my own machine, using my personal files and the local Microsoft PowerPoint application.

The caveat here is that to use an AI to produce a complex presentation from a detailed document or collection of documents, you’ve got to already know the content. Otherwise, you’re just chancing your arm. Work away if you must, but there seems too much risk to credibility in that for me.

AI & PowerPoint Workshop

The Problem with Presentations

Here’s the thing about PowerPoint that makes it genuinely difficult for AI. It’s two jobs pretending to be one. You’re doing analysis, synthesising data, building an argument, and structuring a narrative. And you’re doing design, arranging elements on a canvas, managing visual hierarchy, making sure the thing is readable from the back of a conference room and so on. This is a different kind of thinking that incorporates several elements in parallel.

Large language models are mostly trained on text. They understand narrative, argument, and logical flow (arguably). But design, alignment, alternative storytelling maybe not so much. Where should this chart sit relative to that text block? Is there enough contrast between the background and the font? That’s a different kind of intelligence entirely. They don’t possess the intuition and understanding that you do. They don’t understand at all, in fact. They are statistical predictive machines that don’t reason.

I’ve tested several tools and became frustrated and impatient with most of them. The AI gets the content right, but not all the time. The visuals are usually unimpressive. Text sliding underneath decorative boxes. Charts with black text on navy backgrounds. Executive summaries are hidden in tiny fonts while irrelevant details sprawl across the screen. It’s disappointing because you can see the intelligence at work, but the output can’t be used. To boot, they don’t necessarily remember what you told them last time.

Claude Code running your AI Business OS does, however.

Magic Single-Shot Prompts Won’t Work

If you’re looking for a single prompt that solves this, I haven’t found one, and I doubt you will either. What actually works is a system with specific guidelines and constraints, dos and don’ts that guide the AI and prevent it from making formatting and design errors, like what I have built into my AI Business OS. The more complex the task for humans, the more brainpower is required, and the more exact our guidance of the AI needs to be.

Since using Claude Code in my local developer application (no third parties), I’ve learned, for example, that running /command to execute a specified and predetermined workflow (rather than letting it decide) produces dramatically better results. Specifying in my workflow “no border boxes around text elements” eliminates a whole category of layout disasters. Requiring minimum font sizes and contrast ratios catches accessibility issues before they become embarrassing. Specifying brand colours and providing examples also helps guide the AI.

This isn’t about creating unnecessary work for yourself. It’s about acknowledging that presentation generation requires a different kind of precision than text generation. The AI needs guardrails not because it’s stupid, but because the task itself is genuinely complex. You’re asking a language model to think and plan as you do. So give it rules to follow. Take the time to build it once and take a sigh of relief.

Simple PowerPoint Versus Big Ones

Not every presentation needs the same approach. A weekly status update—six to eight slides summarising progress, risks, and next steps or whatever, can arguably be generated in a single-shot prompt. You provide your data, specify your corporate styling, describe the slide structure, and get something usable in only a few minutes. But a presentation of 50+ slides with multiple data sources and a complex narrative? That’s a different story altogether.

I’ve had success using what you might call a multi-stage approach. One conversation for planning the structure, separate conversations for generating each section, and a final pass to check consistency across the whole presentation. I’m asking myself, do the numbers match? Does the story flow? Are the section layouts consistent? Is the brand and styling maintained throughout?

It sounds like a lot more work, and you’d be right, it is more upfront effort. But compare that to multiple people spending a week preparing a quarterly review, or you alone spending two days building a presentation for a conference and putting every other important thing on hold. Suddenly, working with an AI for two to three hours seems reasonable.

What AI Can’t Do

The time you save on producing the presentation doesn’t necessarily allow you to lie carefree in your hammock-that’s not what we are chasing. We want to spend our time working on things that stir our creativity and genuinely excite us. We reallocate this saved time to the parts of presentation work that AI genuinely can’t handle, or something else like rehearsal.

Interpreting the data, anticipating responses and questions, knowing how this thing we’ve studied and analysed is likely to impact the business, the broader market or society. Deciding what to emphasise, what to leave out, and where to adlib. Navigating the politics of who gets credit and who gets blamed. Working out what your audience actually needs to hear versus what you want to say.

These are human elements, and they require understanding context, reading rooms, and managing relationships. No prompt will automate these. And honestly, I’m not sure we’d want it to.

What AI does is strip away the repetitive mechanical labour—the formatting, the layout, the tedious back-and-forth of “can you make the font bigger” and “can we try a different chart type.” That work added little value. Now it happens in minutes instead of hours.

The Human In The Process

None of this works without clear thinking on your part.

AI can’t generate a good presentation from vague inputs. It needs to know what story you’re telling, what data supports it, and what decisions you’re asking for. The logic that used to live in your head, how you reconcile conflicting figures, which metrics matter most, what trade-offs you’re willing to accept, all of that has to become explicit. You have to articulate it and direct the AI accordingly.

In a sense, AI forces us to be clear and unambiguous. Think Daniel Kahneman’s System 2, that aspect of mind that requires deliberation and planning. The AI machine requires precision direction, and in that, it is not truly intelligent-you are, however. If you haven’t thought it through properly, the AI will show it in its output.

Some people will find this frustrating, though, I accept that. I think it’s an opportunity, however. The people who’ll benefit most won’t be the ones with the best prompts. Instead, they’ll be the ones who actually know what they’re trying to say and take the time upfront to guide their AI in the way that it needs to.

🗓️ Learn AI for PowerPoint Live

If you want to see how this actually works in practice, I’m running a free workshop this Friday, 2nd January, at 11 am (Irish time). We’ll cover the basics of AI for both Excel and PowerPoint, with live demonstrations of the techniques I’ve described here. No fluff, just practical workflows you can use immediately. The recording will be available afterwards.

AI & PowerPoint Workshop

When Softbank sells its entire Nvidia holding (Silicon Republic, 2025), JP Morgan’s Jamie Dimon warns that tech stocks are overheated, and Jeff Bezos admits there’s an AI bubble, perhaps we should pay attention. That said, Big Tech firms are collectively spending nearly $400 billion on AI infrastructure this year alone (NPR, 2025), 30% of European workers now use AI daily according to the European Commission Joint Research Centre (2025), and US workplace AI usage rose from 40% to 45% between Q2 and Q3 2025 (Gallup, 2025). At the same time, Irish workers seem reluctant to adopt AI tools at work. According to PwC, only 10% of Irish workers use AI tools daily versus 14% globally. Adoption rates tell a mixed story. So are we witnessing genuine workplace transformation, or a cycle of speculation that will inevitably collapse leaving ordinary working people out of work and out of pocket?

Bubbles Too Easily Forgotten

Remember the last speculative bubble? If you were around when it popped in 2008/9, you’ll know what comes with a collapse. It was a bizarre time. All of a sudden, the roads were empty and the airports were full. Construction equipment filled auction yards while jobs disappeared like fairy dust. Some people handed keys to their houses back to the banks and left. Others who couldn’t cope were found on the end of ropes. It took until early 2010 for the penny to drop for me, when one by one, I let my staff go and closed the doors. I regard myself as one of the fortunate ones, though.

We were collectively consumed by the hype machine, convinced that the party would never end. This time, I get the same uncomfortable feeling. The gap between reality and fiction has widened. Just look at the numbers – Goldman Sachs estimates AI capital expenditure will reach $390 billion this year. AI-related stocks have contributed 75% of the S&P 500’s returns and 90% of capital spending growth since ChatGPT launched in 2022 (Cingari, 2025). The heads of JP Morgan, Morgan Stanley, Goldman Sachs, and The Bank of England have all warned of an impending correction (RTE News, 2025). Even technology tycoon Jeff Bozo is warning us there’s a bubble. When beneficiaries of a boom start hedging their bets, or moving to the other side altogether, maybe we should take heed.

While market analysts debate whether there’s a bubble or not, the European Commission has adopted two AI strategies this year to accelerate AI adoption (Integrin, 2025). The AI Continent Action Plan outlines the EU’s goal to be a global leader in Artificial Intelligence. In addition, a report by the EU Commission says that more than a quarter of European adults are already experimenting with AI at work (European Commission Joint Research Centre, 2025). Implementation powers ahead, it seems, despite market risk. At a micro level, I see strong interest amongst businesses to train their people. A business AI program I put together with a colleague in 2023 continues to sell out every time we run it. We’re into our eighth cohort as of January 2026. So, while we stress whether our pension pot will survive the AI boom, on the ground at least, there is an appetite for learning AI.

Learn AI For Work

The Circular Investment Problem

Part of what’s fuelling AI concerns is the tight circular nature of AI investments. For example, Microsoft’s valuation has been rising on belief that OpenAI will become profitable despite it being deep in the hole, and at the same time, hedging its bets with Anthropic (Microsoft, 2025). Nvidia’s revenue boom stems from the broader scramble to build AI infrastructure. Enter Larry Ellison’s Oracle, who has borrowed up to its oxters ($300 billion according to Bloomberg) betting that data centre leasing will double the value of his company. The big players are investing in the smaller players, who are handing it back to the bigger players and everyone is excited about everyone’s growth. When you look at who’s funding who, you can see that all this growth looks like financial incest.

Side note here: As it is with most CEOs, Ellison is hyper-competitive, perhaps even a little psychopathic. Not to mention an ethically questionable business history. He makes big, bold bets and his AI move looks like it’s cracking at the seams (Oracle down 44% since September). Oracle might be one of the first to blow up, and if it does, it may take the whole AI game down with it.

Compare this gap between debt and profitability to the dot-com bubble. The top tech companies of the time traded at 70 times forward earnings in 2000. Today’s AI giants sit around 26 times earnings (iShares, 2025). Not exactly cheap, but maybe not the same inflated valuation. The difference, AI evangelists argue, is that today’s Big Tech generates real revenue from real customers albeit not where it needs to be. PE, however, is only one metric and not enough in itself to calm my nerves.

Profitability and productivity aren’t the same thing either. AI might be profitable for Nvidia at the moment without necessarily being productive for organisations buying it. Research from MIT earlier this year found that 95% of businesses implementing AI reported zero measurable value (MIT Technology Review, 2025). That should raise eyebrows. An Upwork study found AI agents from OpenAI, Google DeepMind, and Anthropic failed to complete many straightforward workplace tasks autonomously. Even Ilya Sutskever, former chief scientist at OpenAI, now highlights that large language models aren’t the pathway to artificial general intelligence many assumed. While the money flows around in tight-knit circles, the productivity gains they promised seem to remain elusive, at least for now.

What’s Happening at Work

From what I see training business people and educators on AI, whether or not stocks are overvalued is somewhat irrelevant. I work at the intersection of people and technology, and I see an appetite for leaning generative AI, to improve workflows and create efficiencies. And I believe that Gen AI is capable of delivering on that if people know how to use it, if they can develop a particular structural way of thinking. The hype machine suggests that you just type a one-shot or two-shot prompt into ChatGPT or Claude and your problem is solved, but that’s not how it works. To get the best from AI tools requires strategic thought and ability to see where the gaps are. The AI needs humans to give it structure and direction, otherwise it gives you inaccuracies at best, gibberish at worst.

Even if this bubble bursts, the genie isn’t going back in the bottle. Much like the internet in the 2000s, this technology isn’t going away, in my opinion. These tools are good, if we can accept that people are the key to digital transformation, not the technology itself. The tech is agnostic, it’s how organisations test, plan, train, and implement that will ultimately count. The businesses that get this right will thrive regardless what the markets do.

If investment flows into learning and development, up-skilling workers and digitally transforming workplaces, then a correction might hurt investors without devastating workplaces. But if spending is primarily speculative, chasing short-term returns through cost-cutting automation, the bursting bubble could leave organisations with expensive technology and a workforce that’s been deskilled or displaced. Critical thinking and decision making outsourced to statistical predictive machines that can’t imagine, feel, empathise or interpret the real world will be the real catastrophe. As Gerald C. Kane wrote in The Technology Fallacy (2019), digital transformation is fundamentally about people, not technology.

Learn AI For Work

Where Do We Go From Here?

The bubble question is fundamentally for investors, but valid for ordinary people too, nonetheless, given its potential impact on jobs and the future of work. For those of us down in the trenches getting our hands dirty, the questions are a little different. Change is inevitable, so are we willing to learn new ways of working? What kind of work do we value and want to preserve? Which tasks are we relieved to delegate to an AI?

McKinsey estimates AI automation could unlock $2.9 trillion in US economic value by 2030 (McKinsey Global Institute, 2025). But value for whom? Distributed how? Will we realise more time to do things we actually enjoy? Nobody will accept a lower standard of living, especially given the ongoing erosion of real wages – there’s only so much ordinary people will endure before they fight back.

The danger isn’t artificial intelligence itself. The danger is treating a socio-technical transformation as merely a financial opportunity. Bubbles come and go, but what work means to us beyond productivity continues to matter. Productivity for productivity’s sake is a farce. It allows organisations to think of people as machines, objects to be manipulated and, perhaps, even be replaced altogether. Whether this bubble bursts or deflates gradually, the real work is building systems that treat humans as more than resources to be optimised for shareholder benefit.

🎓 Learn AI For Work

I’m not talking about creating avatars for social media, writing emails, making stupid cat pictures, generating a muffin recipe, or having ChatGPT write your essay for college...I’m talking real AI Skills. Ones that allow you create something that solves a problem, or speeds up a workflow. You can develop the skills to do your work faster and have more time for yourself. Put money in your pocket and claw back your time. Learn GenAI Skills.

Welcome to The Future of Work, the weekly newsletter of curated content from Peak Performer that explores the evolving landscape of work, leadership, and technology. Each week, I'll bring you perspectives from industry, research and popular media that dive into the critical topics shaping how we live and work in an era of rapid technological change. Whether you’re a manager striving to inspire your team, an industry leader navigating disruption, a graduate entering the workforce, or a worker adapting to new challenges, this newsletter is your go-to resource for news and insights to thrive in the future of work.

The future of work isn’t a distant concept—it’s unfolding now. From cultural shifts to cutting-edge technologies and the evolving nature of leadership, the goal of this weekly publication is to keep you informed and empowered to navigate these changes confidently.

After an extended Christmas break, I’m returning with interesting research to highlight. Rather than offer several sources this week in The Future of Work article, I’m zeroing in on an article from Dr Michael Gerlich, Head of the Center for Strategic Corporate Foresight and Sustainability at SBS-Swiss Business School. It’s a natural follow-up to the recent article here on the importance of handwriting for cognition. This current offering is open to everyone.

Cognitive Offloading and Its Impact on Learning and Memory

Cognitive offloading, which involves delegating mental tasks to external tools, has become increasingly relevant in today’s technology-driven world. Whether using a calendar app to remember your appointments or leaning on artificial intelligence to interpret a complex dataset, cognitive offloading shapes how we interact with our environment. While this practice can potentially enhance workplace efficiency, it raises significant concerns about its implications for learning, development, memory, and critical thinking skills. Some researchers suggest that a dumbing down of the human intellect is underway, and the negative consequences outweigh the benefits. In this article, I’m exploring this concept, highlighting the benefits and potential pitfalls with a

What Is Cognitive Offloading?

Cognitive offloading refers to using tools and devices to externalise mental processes and reduce cognitive load or mental effort. This practice is developed from the “extended mind” theory, proposed by Clark and Chalmers (1998)1, which suggests that these devices act as external aids and function as extensions of our cognitive systems—they extend the human mind. And it’s not just digital technology. This offloading exercise has gone on for centuries, maybe millennia. From the early use of physical tools like the abacus to contemporary reliance on AI systems, offloading has been a hallmark of human creativity and ingenuity. The brain is an energy-hungry organ, and this tactic allows us to conserve mental energy and focus on higher-order tasks, such as creative problem-solving or strategic planning.

Despite its benefits, cognitive offloading is a double-edged sword. While it supports task performance by lightening the cognitive load, it may also, after a time, undermine the internal cognitive processes required for critical thinking and memory formation and retrieval. As Grinschgl et al. (2021)2 note, offloading can impair long-term memory retention because we bypass the effortful encoding processes essential for durable memory. For example, when information is readily available through search engines or AI tools, we are more likely to remember where to find information than the information itself—a phenomenon known as “transactive memory”3. This duality underscores the need to examine when and how cognitive offloading is most beneficial carefully.

Origins of Research in Cognitive Offloading

The study of cognitive offloading has a rich history, beginning with early explorations of external memory aids like note-taking and progressing to sophisticated investigations into digital tools and AI. Early experiments, such as the Pattern Copy Task4, provided insights into how human beings balance internal and external strategies for completing tasks. These studies revealed that people tend to offload more when external aids are easily accessible and the perceived costs of offloading are low. In other words, we ask ourselves where are the benefits and downsides of using this technology. Sometimes, this is an unconscious decision.

More recent research has focused on the role of digital technologies in offloading. The rise of smartphones, virtual assistants, and AI systems has transformed how cognitive tasks are distributed between internal and external resources. Studies by Gerlich (2024)5 emphasise the dual impact of AI: while it enhances task performance and decision-making, it also creates an over-reliance, which can erode critical thinking skills. These findings highlight the need for continued research into the cognitive trade-offs associated with technological advances.

Main findings from the 2025 study “AI Tools in Society: Impacts on Cognitive Offloading and the Future of Critical Thinking” by Michael Gerlich:

1. Negative Correlation Between AI Usage and Critical Thinking: The study found a significant negative correlation between frequent AI tool usage and critical thinking abilities. This means that higher usage of AI tools is associated with lower critical thinking skills.

2. Cognitive Offloading as a Mediator: Cognitive offloading, where individuals rely on AI tools to perform cognitive tasks, was identified as a mediating factor. Increased cognitive offloading due to AI tool usage reduces engagement in deep, reflective thinking, essential for critical thinking.

3. Age and Educational Differences: Younger participants showed higher dependence on AI tools and lower critical thinking scores than older participants. Additionally, individuals with higher educational attainment exhibited better critical thinking skills, regardless of their AI tool usage^.

4. Educational Recommendations: The study emphasises the need for educational strategies that promote critical engagement with AI technologies. It suggests that fostering critical thinking skills is crucial in an AI-driven world to mitigate the cognitive costs of reliance on AI tools.

Ai Tools In Society Impacts On Cognitive Offloading And The Future Of Critical Thinking 2025

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2025 paper by Michael Gerlich on the impact of cognitive e offloading to AI tools

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Why Do Humans Use Cognitive Offloading?

Cognitive offloading is driven by a natural human tendency to optimise mental resources. From an evolutionary perspective, humans have over many thousands of years developed strategies to manage working memory and attention limitations. External aids, such as writing or visual cues, have long extended the mind’s capabilities. Modern digital tools have amplified these possibilities, offering solutions that are faster, more precise, and more accessible. This becomes more pronounced and arguably more detrimental when productivity and efficiency in the workplace are emphasised. We forget that humans are not machines; our needs and requirements go much deeper than the commercial world demands.

Metacognition—the ability to think about thoughts, and to assess and regulate one’s cognitive processes, also plays a significant role in offloading. We often consciously offload tasks when we perceive our internal memory or problem-solving abilities to be inadequate. For instance, if you are like me, you may feel that remembering your wife’s birthday is impossible, so you create a reminder in your Google calendar. This conscious decision-making is about minimising the mental effort associated with remembering. However, research by Gilbert (2020)6 showed that people often overuse external reminders, even when their internal memory could suffice because they prefer to avoid cognitive effort. This phenomenon, termed “cognitive laziness,” reflects the growing reliance on technology to perform tasks that require mental engagement. While this reduces immediate cognitive strain, it raises questions about the long-term effects on internal cognitive abilities.

Benefits of Cognitive Offloading for Learning and Development

Cognitive offloading offers significant benefits, particularly in learning and productivity contexts. Reducing the cognitive load associated with routine tasks frees up mental resources for complex and creative thinking. For instance, adaptive learning platforms that tailor educational content to individual needs enable students to focus on higher-order skills like analysis and synthesis.

Moreover, offloading can make learning more accessible. Digital tools support learners with disabilities, allowing them to overcome challenges related to memory or attention. In resource-constrained environments, technology can bridge gaps in educational access, offering opportunities for self-paced and personalized learning. These applications illustrate how cognitive offloading can judiciously enhance individual and collective learning outcomes.

Negative Impacts of AI-Driven Cognitive Offloading

While the benefits of cognitive offloading are undeniable, the growing reliance on AI tools raises concerns about its long-term implications for cognitive development. One of the most significant risks is the erosion of critical thinking skills. Critical thinking requires active cognitive engagement, such as questioning assumptions, evaluating evidence, and synthesising diverse perspectives. However, where AI tools provide instantaneous, ready-made solutions, they discourage us from engaging in these deeper cognitive processes. We couldn’t be bothered! As machines and algorithms take over everyday living, art, creativity, walking the dog, and cleaning the house, what of human beings?

Is the ultimate goal of these technological conveniences that we can merely lay on the couch and order everything by mere thought? Do we not make ourselves redundant? Perhaps the old adage, “use it or lose it” is appropriate.

Memory retention is another area of concern. Studies by Grinschgl et al. (2021) show frequent offloading diminishes our ability to recall information independently. This effect is particularly pronounced when we rely on AI systems to store and retrieve information without actively processing it. Over time, this can lead to a superficial understanding of complex issues and a reduced capacity for independent thought. And when the battery dies on the iPad, you lose connection to your outsourced brain.

The societal implications are obviously troubling. Great for the power centres of global corporations, government, and finance, but not so much for people’s freedom. As AI tools become ubiquitous, we risk becoming more susceptible to misinformation and less capable of discerning credible sources. This risks undermining individual decision-making and challenges democratic processes that rely on informed and critically engaged citizens—or do they? the jury is out on that one.

The Ethical and Developmental Case for Doing the Work Yourself

Given these risks, finding a balanced approach to offloading our cognitive abilities is vitally important. Even things we take for granted, such as typing on a computer keyboard or tapping on a screen, might get things done quicker, but at a potentially significant cost to our cognitive function. I wrote about that here a few weeks ago. While external aids can enhance efficiency, we must also cultivate our internal cognitive capacities, especially in youth education. Engaging in effortful cognitive tasks promotes memory retention, critical thinking, and problem-solving skills. It is also a feature of doing things that are worthwhile in and of themselves. It is what Aristotle referred to in Nicomachean Ethics as “The Good Life7”. These abilities are essential for personal growth, professional success, and ethical decision-making.

Educators and policymakers have a vital role to play in this endeavour. Educational systems should integrate AI tools in ways that complement rather than replace traditional cognitive tasks. For example, students could be encouraged to use AI as a tool for exploration rather than as a definitive source of answers. Assignments could require them to critically evaluate AI-generated outputs and consider alternative perspectives, fostering more profound engagement with the material.

At an individual level, cultivating mindfulness about technology use can help mitigate risks of overreliance. Setting boundaries, such as limiting digital reminders or intentionally solving problems without external aids, can strengthen internal cognitive skills. These practices enhance personal development and contribute to a more resilient and adaptive society.

Conclusion

Cognitive offloading can be an effective means to transform how we manage mental tasks, offering convenience and efficiency both inside and outside the workplace. However, its growing prevalence, particularly in the age of AI, demands careful consideration of its impact on learning, memory, and critical thinking skills. Who holds ultimate responsibility for the outcomes of our lives, and are we willing to abdicate our responsibility to machines? We’re doing it already—we are outsourcing our brains—so the question now is, to what ultimate outcome?

I guess it’s a product of this always-on world we live in where the demands on our attention are incessant. Everyone wants a piece of us, and work has become so much more demanding. John Maynard Keynes said in 1930 that we would be working only 15 hours per week, and machines would be doing the laborious work8. What happened to that promise? I’ll tell you…The time and efficiency that technology created went into the pockets of CEOs.

Ok, hold the rant…

To finish, we need to balance the use of external aids and foster internal cognitive engagement to harness the benefits of offloading without compromising our intellectual growth. This balanced approach is essential for personal development and building a society capable of navigating the complexities of this dramatically changing world of work.

References

Welcome to The Future of Work, the weekly newsletter from Peak Performer that explores the evolving landscape of work, leadership, and technology. Each week, I dig into the critical topics shaping how we live and work in an era of rapid technological change. Whether you’re a manager striving to inspire your team, an industry leader navigating disruption, a graduate entering the workforce, or a worker adapting to new challenges, this newsletter is your go-to resource for news and insights to thrive in the future of work.

This week in TFOW, the Fast Company article, particularly, caught my attention—but for all the wrong reasons. Well, why bother sharing it then? It serves to illustrate the utter bullshit that exists in the world of business and management when it comes to being effective. So, let’s dive in.

What is strategy? Porter (1996) says strategy is “the creation of a unique and valuable position, involving a different set of activities” that allows an organisation to achieve competitive advantage by making trade-offs in choosing what not to do. Mintzberg (1987) suggests that strategy is a pattern in a stream of decisions, which can be deliberate (planned) or emergent (arising from organisational actions over time).

Very poetic.

Strategy represents the plan we design and execute in the pursuit of our goals. In the modern world of work, it mostly has material ends in mind. In business, that plan, effectively externalising as much of the cost as possible, usually leaves a trail of destruction behind it. We need only notice how mass consumerism destroys the environment and alienates millions to see how true this is. Sure, those of us in the Global North have our gadgets and cheap clothes, but there is an unavoidable pay-off for which we will eventually have to pony up. So, when we talk about strategy and couple it with things like emotional intelligence and empathy, for example, it sets off alarm bells for me.

Goleman’s work on Emotional Intelligence eventually made this idea very popular. HBR ran an article extolling its virtues and the advantages executives might garner from its application. Almost overnight, EI assessments, programs, books, articles, and so on were everywhere. Understanding oneself and others was now a necessary component of effective leadership, not because you necessarily cared about your people, but because it helped you get what you wanted or what was demanded of you from the job. Goleman was now a business and management guru, and the stage was set for EI to become the must-have people management tool.

Surely, understanding the needs of others and making ethical decisions in business can be done without a strategy. Or maybe not. Perhaps the fundamental premise and the incessant demands of the competitive marketplace train us out of our concern for others and require a counterbalance. Business leaders must be re-trained to be human. Or, more accurately, to hold two incompatible concepts of self in mind at once. If you occupy positions of responsibility within a corporate organisation, you must be assessed psychometrically and attend EI leadership training. You must learn the skills of being human so that you may appropriately apply them in the attainment of material ends. It all seems somewhat contrived to me–what Arlie Hochschild referred to as "surface-acting" (2019).

Is this not what Machiavelli proposed in his 16th Century Guidebook to Kings? (The Prince, 1513). Psychopaths, Machiavellians, and Narcissists are usually adept, or maybe become so through half-day leadership workshops, at the skills of reading and manipulating others. They understand the social rules governing healthy social and familial interaction and use these to achieve their material ends. Is it that the world of work and business has provided the environment where these maniacs can flourish? Or do its demands transform ordinarily good people into bad? Is this why many organisations will go to whatever extent necessary to achieve their commercial ends and feel no discomfort in doing so? It's only business, after all. No wonder, then, that Goleman and his cohort have come under scrutiny.

Some have praised emotional intelligence (EI) for enhancing workplace relationships and leadership effectiveness (Kerr et al., 2005). However, it faces significant criticism from scholars arguing that it lacks a clear and consistent definition and overlaps with established personality traits such as conscientiousness and empathy (Murphy, 2013). Additionally, the predictive validity of EI has come into question. Studies have shown that when factors like IQ and personality are controlled, EI's influence on job performance and leadership effectiveness diminishes substantially (Antonakis et al., 2009). Critics also suggest that the lack of rigorous empirical evidence makes Emotional Intelligence no more than "pop psychology" rather than a robust scientific construct (Waterhouse, 2006).

The message here is to be wary of trendy ideas, especially this one, and if you care about sincerity and authenticity, audit your people. Understanding and having empathy for others is a fundamental aspect of being human. It is not something that you need to practice and develop as a tool in the execution of your job. So, be human, and don’t let the machine make a machine of you.

Culture: Why Emotional Intelligence Is Key to Building a Great Company Culture

An article from Fast Company emphasises the apparently pivotal role of emotional intelligence in cultivating a thriving company culture. No doubt, being a human does just this, but beware of ulterior motives. EI involves recognising, understanding, and managing one's emotions and empathising with others. It is said that leaders with high EI can navigate complex interpersonal dynamics, foster open communication, and build team trust. The piece highlights that organisations prioritising EI in their leadership development see enhanced collaboration, increased employee engagement, and reduced turnover. In the context of the future of work, where remote and hybrid models are becoming the norm, EI becomes even more critical. It enables leaders to connect with their teams authentically, address challenges proactively, and create an inclusive environment that adapts to change. For managers and industry leaders, investing in EQ development is beneficial and essential for sustaining a positive workplace culture in an evolving work landscape.

Read the full article here.

Leadership: Design Work to Prevent Burnout

An MIT Sloan Management Review article suggests leaders adopt a SMART Work Design model to mitigate employee burnout and enhance engagement. The model emphasises five key job characteristics: Stimulating work, mastery, autonomy, relational aspects, and demands tolerance. By incorporating these elements, organisations can create healthier and more sustainable jobs, increasing employee satisfaction, motivation, and commitment. The authors argue that traditional "fix-the-worker" approaches, such as offering productivity tips or mindfulness training, fail to address the root causes of burnout, which often stem from poor work design. Instead, they advocate for a comprehensive approach that considers positive and negative work characteristics to create an environment supporting employee well-being and performance. As Frederick Herzberg suggested in 1959, “If you want people to do a good job, give them a good job to do — an enriched job.”

Read the full article here.

Artificial Intelligence: OpenAI Whistleblower Found Dead

Mashable India reports on the former OpenAI researcher turned whistleblower Suchir Balaji, who tragically took his own life recently. His body was discovered on 26 November 2024 after police conducted a welfare check prompted by a concerned call. The BBC reported, “The San Francisco medical examiner's office determined his death to be suicide, and police found no evidence of foul play.”

Balaji spent four years as a researcher at OpenAI before concluding that the organisation’s practices, including using copyrighted data to train ChatGPT, were potentially unlawful. He also voiced concerns about the broader impact of technologies like ChatGPT, arguing they were harmful to the integrity of the Internet. Balaji shared these concerns in an interview with The New York Times.

Balaji said, "AI companies are destroying the commercial viability of the individuals, businesses, and internet services that created the digital data used to train these A.I. systems."

Read the full article here.

Wellbeing: Uncertainty Is Part of Being Human

An insightful article from The Guardian explores the inherent uncertainty of human existence and offers strategies to navigate it. David Spiegelhalter, a professor of statistics, shares personal anecdotes and professional insights into how acknowledging and reframing our perceptions of uncertainty can lead to better mental health. He suggests that accepting uncertainty as a fundamental aspect of life allows individuals to engage more fully with the world, reducing anxiety and enhancing decision-making. Being comfortable with uncertainty becomes crucial in the future of work, where rapid technological advancements and shifting job landscapes are prevalent. Building resilience and adaptability in the face of the unknown can lead to more fulfilling careers and personal growth for workers and graduates.

Read the full article here.

Work: Five Hybrid Work Trends to Watch in 2025

A recent MIT Sloan Management Review article outlines emerging trends in hybrid work models anticipated for 2025. The piece highlights that while many believed debates over hybrid work had settled, recent developments have reignited discussions. Key trends include the evolution and refinement of hybrid work models, the impact of return-to-office mandates, and the ongoing balance between flexibility and productivity. For managers and industry leaders, staying informed about these trends is essential to navigate the complexities of hybrid work arrangements effectively. The article suggests that the shift away from an overly simplistic focus is common to each trend. Many leaders see an advantage in redesigning their approach to focus on outcomes, particularly when driving engagement in talented teams.

Read the full article here.

I think my fears are less about the technology itself and more about the fact that it is developed and controlled by a handful of large corporations whose interests are, of course, the interests of the corporation and profit and growth and the pleasing of shareholders, not necessarily the social good.

– Meredith Whittaker, CEO Signal

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Welcome to The Future of Work, the weekly newsletter of curated content from Peak Performer that explores the evolving landscape of work, leadership, and technology. Each week, we dive into the critical topics shaping how we live and work in an era of rapid technological change. Whether you’re a manager striving to inspire your team, an industry leader navigating disruption, a graduate entering the workforce, or a worker adapting to new challenges, this newsletter is your go-to resource for news and insights to thrive in the future of work.

Shoshana Zuboff says that we are in the age of surveillance capitalism. "The digital realm is overtaking and redefining everything," she says. Technology is ubiquitous, and it serves us to approach it with eyes wide open. Where does our data go? Who can see it, and how is it used? Can we trust technology? Are the rules enough to ensure our interests are met? Should we trust the machine? More so, can we trust the people who have made this machine? Scepticism keeps us alive. It is the foundation of the scientific pursuit of answers to worldly problems. Therefore, we must be willing to question what others tell us and, indeed, what the data machine tells us. This question, or awareness of it, serves as an anchor in the stormy sea of technological change. Apart from anything else, it's simply good business sense.

This week’s Culture piece from HBR delves into how AI can enhance collaboration, allowing us to meet inclusivity requirements and workplace efficiency. The Leadership article from Forbes explores integrating micro-coaching with online learning platforms to transform leadership development. In Artificial Intelligence, the article examines the complex interplay between AI, intellectual property, and the creative industries. The Wellbeing section highlights the persistent challenges of addressing mental health in the workplace and the need for comprehensive strategies. Finally, the Work article discusses the resurgence of the traditional office environment and the evolving dynamics between leadership mandates and employee preferences.

The future of work isn’t a distant concept—it’s unfolding now. From cultural shifts to cutting-edge technologies and the evolving nature of leadership, this weekly publication aims to keep you informed and empowered to navigate these changes confidently.

Culture: Enhancing Meeting Inclusivity with AI

Digital transformation is about people rather than technology. So says Dr Gerald Kane, Author of The Technology Fallacy. Harvard Business Review reinforces this idea in a recent article by Tomas Chamorro-Premuzic. He outlines strategies for integrating artificial intelligence into team workflows to boost efficiency and innovation. The author suggests that AI is a tool to augment, not replace, human capabilities, emphasising the synergy between AI's strengths and human creativity.

The article stresses the importance of AI literacy, encouraging organisations to provide training that helps employees understand AI's potential and limitations. Identifying tasks suitable for AI, such as automating data-heavy or routine processes, is also key. This allows team members to focus on complex, strategic work, enhancing productivity.

Ensuring data quality is another critical aspect. AI relies on high-quality data for accuracy, making robust data policies, planning and management essential. Ethical development, deployment and use of AI are paramount, as highlighted recently by the AI Act in the EU and similar actions globally. Organisations must establish guidelines to ensure AI is transparent, unbiased, and aligned with ethical standards, maintaining trust among all stakeholders.

Finally, the article emphasises fostering a culture of continuous learning. With AI technologies evolving rapidly, teams must collaborate and stay updated on developments and best practices. By addressing these areas, organisations can effectively integrate AI into their operations, allowing them to move quickly when circumstances require it.

Source: Harvard Business Review

Leadership: Transforming Leadership Development with Microcoaching

This week's Leadership article is from Forbes and examines integrating micro-coaching with online learning platforms to enhance leadership development. This combined approach aims to enrich the learning experience and optimize organizational investment in leadership training.

Decision-making cannot be left entirely to machines or, perhaps, at all. Technology can inform decision-making but should not replace the human being. This underscores the critical need for human-centred leadership. Yet, the article suggests, many organisations persist with outdated leadership development models that fail to adequately prepare leaders to succeed in this rapidly changing environment.

Microcoaching involves brief, focused coaching sessions that address specific challenges or skills, providing personalised guidance on performing the leadership role. When paired with online learning, it allows leaders to apply theoretical knowledge in practical scenarios, reinforcing learning outcomes.

The article suggests that this blended method can lead to more effective leadership development by offering tailored support and flexibility, catering to individual learning styles and schedules. After all, it's not simply about the information but how it is applied. This approach enhances skill acquisition and promotes continuous learning and adaptability among leaders.

By adopting a 5-star approach that combines micro-coaching with digital learning tools, organisations can foster a culture of ongoing development and ensure that leadership capabilities evolve in alignment with personal and organisational goals and the demanding business environment.

Source: Forbes

Artificial Intelligence: Navigating AI, Intellectual Property, and the Creative Industries

The London School of Economics and Political Science (LSE) is hosting a hybrid event titled "Artificial Intelligence, Intellectual Property, and the Creative Industries." It is free and will take place on 4 March 2025. This event will explore the challenges that artificial intelligence (AI) technologies present within creative sectors such as film, theatre, music, and video games.

Key Discussion Points:

• Generative AI and Intellectual Property (IP): The panel will examine legal issues arising from using generative AI models like ChatGPT and Stable Diffusion, which create text, art, and music. A central focus will be on how these models interact with existing IP laws, particularly concerning copyright and trademark infringements.

• Image Rights of Performers: The discussion will extend to AI's implications for performers' image rights, exploring how AI-generated content may affect the control and use of a performer's likeness.

• Legal Rights and Licensing Solutions: The event explores the legal rights of authors, performers, and users in the context of AI-generated works. It will also consider the feasibility of regional or global IP licensing solutions to address the complexities introduced by AI in creative processes.

Find out more: London School of Economics

Wellbeing: Workplace Mental Health Needs More Than a Quick Fix

Despite growing awareness and initiatives, the article highlights the persistent challenges in addressing mental health in professional environments. The World Health Organisation estimates 12 billion lost workdays and an annual $1 trillion impact on the global economy and emphasises the significant economic toll of untreated mental health issues.

A key focus is the need for organisations to move beyond surface-level solutions, advocating for a comprehensive approach that integrates mental health into workplace culture. Leaders are encouraged to actively listen to employees and show authentic concern for their well-being. Strategies such as conducting “stay interviews” help proactively address issues, while training programs equip teams to recognise and counteract workplace bullying, for example.

The article argues that fostering a supportive workplace environment goes beyond reactive measures and requires systemic change and commitment from leadership. By prioritising these efforts, organisations can improve employee mental health, reduce turnover, and enhance their people's overall performance.

For managers and industry leaders, this underscores the importance of creating a supportive culture that is human-centric rather than outcome-centric. By addressing systemic issues and promoting a healthy work-life/personal-life balance, organisations can enhance productivity and ensure a more resilient workforce

Source: Fast Company

Work: The Office Comeback

An insightful article from Work Design Magazine examines the resurgence of the traditional office environment, highlighting the evolving dynamics between leadership mandates and employee preferences. Many organisations have required employees to return to physical offices post-pandemic, citing benefits such as enhanced innovation, improved communication, and stronger organisational engagement. However, these mandates have sparked debates, with some viewing them as indirect methods to reduce headcount without formal layoffs.

The author notes that Gen Z is at the forefront of this return-to-office movement. Having entered the workforce during the pandemic, many Gen Zers value in-person experiences for mentorship, networking, and career development opportunities that are less accessible in remote settings. This generational shift underscores a broader recognition of the unique advantages physical workplaces provide, which virtual environments may not fully replicate.

This trend emphasises the importance of creating office spaces that foster genuine connections and collaborative opportunities for managers and industry leaders. By understanding and addressing the diverse needs of their workforce, organisations can design environments that encourage voluntary return, thereby enhancing engagement and productivity. This approach aligns with the future of work, where flexibility and intentionality in workspace design are crucial for attracting and retaining talent.

Source: Work Design Magazine

“Intelligent machines with this capability would be able to look further into the future than humans can. They would also be able to take into account far more information. These two capabilities combined lead inevitably to better real-world decisions. In any kind of conflict situation between humans and machines, we would quickly find, like Garry Kasparov and Lee Sedol, that our every move has been anticipated and blocked. We would lose the game before it even started.”

― Stuart Russell, Human Compatible: AI and the Problem of Control

Thanks for reading

See you next time...

Welcome to The Future of Work, the weekly newsletter of curated content from Peak Performer that explores the evolving landscape of work, leadership, and technology. Each week, I'll bring you perspectives from industry, research and popular media that dive into the critical topics shaping how we live and work in an era of rapid technological change. Whether you’re a manager striving to inspire your team, an industry leader navigating disruption, a graduate entering the workforce, or a worker adapting to new challenges, this newsletter is your go-to resource for news and insights to thrive in the future of work.

On the technology front, AI continues to transform industries, creating both opportunities and ethical dilemmas. We examine the latest news in AI development and its implications for the workforce. Workplace well-being is another key theme each week as we explore how understanding oneself and others can be harnessed for personal and professional growth. Finally, this week, we take a thought-provoking look at the often-reviled Karl Marx, whose theory offers an alternative perspective on labour, inequality, and systemic change in modern work environments.

The future of work isn’t a distant concept—it’s unfolding now. From cultural shifts to cutting-edge technologies and the evolving nature of leadership, the goal of this weekly publication is to keep you informed and empowered to navigate these changes confidently.

Culture: "Your AI Strategy Will Fail Without a Culture That Supports It"

Read the article here

Any AI strategy will fail if the organisation’s culture does not actively support it. Many companies focus on the technical aspects of AI implementation while neglecting the cultural and individual transformations needed for success. People must be at the centre of this technological change. Poor leadership communication, lack of collaboration, resistance to change, fear of job loss, and a lack of transparency are key cultural barriers to integrating AI. To overcome these obstacles, leaders must cultivate a culture that promotes innovation, adaptability, and trust. This includes clear communication about AI’s purpose, investment in employee upskilling, and aligning AI initiatives with individual and organisational values. As AI becomes increasingly central to business operations, fostering such a culture ensures smoother transitions and better utilisation of these technologies. In this article, Gallup suggests that this perspective is vital for understanding the future of work, where technological advancements are only as effective as the people and systems that support them.

Leadership: "Four Leadership Loads That Keep Getting Heavier"

Read the article here

Organisational leaders face intensifying pressures in this rapidly changing technological workplace. From managing increasingly diverse teams to dealing with information overload, leaders now juggle more responsibilities than ever. The four "loads" identified in the article by The Sloan Management Review include keeping teams motivated in times of uncertainty, navigating misinformation, maintaining strategic focus amid constant change, and prioritising personal well-being. The article provides actionable strategies for alleviating these burdens, such as delegating effectively, fostering effective communication, and creating time for self-reflection. The insights are particularly relevant in the future of work, where rapid technological advancements, increasing global crises, and evolving workforce expectations demand resilient and adaptable leadership. This piece underscores the need for leaders to manage external demands and care for their mental and physical health to sustain long-term effectiveness.

Artificial Intelligence: "Artificial Intelligence Review"

Read the article here

This comprehensive review by Springer Nature examines the current state of artificial intelligence (AI) and its future trajectory. Covering AI methodologies, applications, and ethical implications, the article provides a detailed exploration of how AI shapes industries and society. From advancements in machine learning and natural language processing to healthcare, education, and finance applications, the article reveals the transformative potential of AI technologies. Ethical concerns, such as bias in AI algorithms, data privacy, and the risk of job displacement, are also addressed, emphasising the need for responsible AI development, deployment, and assessment. The article highlights AI’s dual role as both a challenge and an opportunity in the future of work, where its integration will redefine job roles, skill requirements, and organisational structures. The article provides a roadmap for navigating the AI-driven workplace by fostering a deeper understanding of these dynamics.

Wellbeing: "Can Anger Help You Achieve Your Goals"

Read the article here

This article in Scientific American suggests that contrary to common perceptions, anger may be a positive force when channelled effectively. Anger, often viewed negatively, can, in fact, drive us toward achieving our goals. Citing a number of studies, the article demonstrates how anger can increase motivation, improve focus, and strengthen determination. For instance, the energy generated by anger can be redirected to tackle challenges or address injustices constructively. In Self Determination terms, it may provide "the energy for action", as Ed Deci puts it. The key, however, lies in managing anger appropriately—understanding its triggers and applying it in ways that foster progress rather than conflict. In the workplace, where emotional intelligence and resilience are increasingly valued, this perspective encourages professionals to embrace and utilise emotions rather than suppress them. As we look to the future of work, the ability to transform negative emotions into positive outcomes will be a crucial skill for personal and professional growth.

Work: "What is Marxist Theory and Why Do We Need It?"

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This article by Judy Cox in Socialist Worker magazine emphasises the importance of Marxist theory in understanding the underlying mechanisms of capitalism that shape societal experiences. Cox argues that while individuals may be aware of issues like low wages and housing insecurity, comprehending the systemic causes requires a theoretical framework. Marxist theory provides tools to analyse how capitalism operates, revealing the often concealed processes that lead to social inequalities. The article critiques mainstream and far-right explanations for societal crises, suggesting they offer misleading or superficial solutions. Instead, Cox advocates for a scientific approach to social analysis, as proposed by Karl Marx, to uncover the true nature of unjust and unfair societal structures. This perspective is deemed essential for those of us seeking to challenge and change the status quo, as it equips us with a deeper understanding of the economic and social forces at play.

Quote of The Week

"If you look around, there are very few examples of more intelligent things being controlled by less intelligent things, which makes you wonder whether when AI gets smarter than us, it’s going to take over control.”

Geofrey Hinton | Cognitive Scientist

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