From writing AI memos towards a "new Gründerzeit"
If AI is the future of work, why do so many CEO memos sound like warnings? What CEOs and policy makers should do instead.
Did you get the memo yet? In recent weeks, numerous CEOs have sent AI memos to their employees, musing about the impact of AI on the labor market. The most disturbing one came from Fiverr CEO Micha Kaufman who wrote that “AI is coming for your jobs” and that “your value will decrease before you know what hit you”.
Similarly, Shopify CEO Tobias Lütke bluntly stated: “In a company growing 20-40% year over year, you must improve by at least that every year just to re-qualify”. And: “Before asking for more Headcount and resources, teams must demonstrate why they cannot get what they want done using AI.”
While the purpose of these memos surely is to create a sense of urgency among employees, they also spark anxiety and cynicism, judging from employees’ comments in internet forums.
This is a bad starting point for a transformation as big as the emerging AI economy.
Leaders need to acknowledge workers’ anxiety, not fuel it
“When people are anxious about job security, layoffs, and the constant push for productivity, they’re not in a mindset to learn. We first need to address those anxieties directly – only then can people feel curious and open to exploring AI,” Helen Kupp, co-founder of Women Defining AI recently said at the Work Forward Forum.
When describing the magnitude of AI’s impact on the economy, it is fair to compare today to the industrial revolution (even though Sam Altman suggested over lunch with the FT that he prefers to compare the AI age to the renaissance – we will come back to this later).
The key point is that AI is a transformational general purpose technology, just like steam or electricity, that will reconfigure our economy. The question is how this can be done quickly and without disrupting society. This requires us to adapt how we run businesses, regulate markets and build institutions.
Running an AI business
Firms react differently to emerging technologies: Incumbent firms tend to favor quick productivity gains by using AI to automate processes. This may however lead to accelerated path dependency and a decline in quality (as Klarna found out – or not).
Firms at the “technological frontier”1 however are likely to use AI to reimagine work processes from scratch and become AI “superstar firms”. In these firms, AI agents will increasingly emerge as a “digital workforce” that works alongside humans.
A memo however is not sufficient to get there. AI is not yet another tech rollout, it requires more fundamental changes.
Luckily, there is a precedence for how companies can do this: The shift to remote work during the pandemic. In her excellent book “Redesigning Work”,2 Lynda Gratton describes how the pandemic created a window of opportunity for firms to rethink knowledge work around the concepts of energy, focus, coordination and collaboration.
Similarly, with AI, firms should assess roles and tasks of their employees and identify areas where AI can accelerate processes, create shortcuts or maybe even cut redundancies.
“Instead of thinking about how vibecoding accelerates engineers, focus on its transformative impact for product managers and designers”, Brian Elliott writes in his Work Forward newsletter. “Suddenly they can jump straight to rapid prototyping (…) before developing formal requirements docs. This fundamentally changes workflows, not just accelerates them.”
This is the opportunity for innovation and growth, not mere efficiency gains.
Distributing AI benefits fairly
Governments, on the other hand, must create frameworks for equal access and fair distribution of AI benefits.
In “Power and Progress”,3 Nobel-Prize winner Daron Acemoğlu and Simon Johnson stress the importance of institutions and social power for the adoption and social acceptance of new technologies: “Progress has a way of leaving many people behind unless its direction is chartered in a more inclusive way. Because this direction governs who wins and who loses, there is often a struggle over it, and social power determines whose favorite direction prevails.”
It is not surprising that disruptive technologies that threaten to upend the livelihood of workers create resistance. This was the case in 19th century Britain when the Luddites destroyed manufacturing equipment in protest of the de-humanizing and labor-replacing properties of theses new machines.
Britain’s initial reaction to the Luddites was harsh: In 1812, Parliament passed the Frame-Breaking Act which made the destruction of machinery a criminal offense that was charged with the death penalty.
But even though the Luddite movement itself was crushed with force, it sparked a wider debate about the need for worker representation in political life and a fairer distribution of the economic gains of industrialization.
This debate would transform Britain into an economic powerhouse: By the mid-nineteenth century, Britain had become a “nation of upstarts”: The dissolution of traditional social classes allowed citizens, often with no or only little formal education, to advance their social status as innovators and entrepreneurs. These self-made men drove the adoption of new technologies.
In Germany, the economic boom during the industrialization was accompanied by the creation of thousands of new and innovative companies is known as the “Gründerzeit” (or “founder’s period”). Some of these firms, such as Siemens, Bayer or BASF still exist today.
That is why the comparison of the age of AI to the “Gründerzeit” (if you want to avoid the term “industrial revolution” with its connotation of poverty and suffering) is still more fitting than a comparison to the renaissance (as Sam Altman suggested). While the renaissance saw scientific discoveries and the emergence of a class of super-rich merchants, not much changed for most of the people living at that time.
The industrial revolution however challenged not only the predominant economic model but also the structure of society just like AI changes both how we work and our self-image as humans and social beings.
Avoiding the pitfalls of the AI revolution
Luckily, we can learn from historic experiences in the industrial era to make the AI revolution a less painful transformation than industrialization:
GIVE WORKERS A WORKPLACE GUARANTEE To address short-term fears of being made redundant, CEOs could give a workplace guarantee for every employee for a certain period of time instead of writing threatening AI memos. During that time, each employee can safely experiment with AI and re-imagine old routines and work processes without instantly being judged against arbitrary productivity metrics (I used AI in various ways during the research and writing of this article and AI is by no means a simple shortcut to creative expression).
Companies should follow the advice of Wharton School professord Ethan Mollick: “The future of work isn’t just about individuals adapting to AI, it’s about organizations reimagining the fundamental nature of teamwork and management structures themselves. And that’s a challenge that will require not just technological solutions, but new organizational thinking.”
This task cannot be delegated to frontline workers – CEOs, management teams and boards must lead this effort.
Workplace guarantees are not uncommon: In transition phases, large German corporations often give workplace guarantees to their employees, and during COVID, some companies promised their employees to keep them on the payroll even though offices were closed to reduce anxiety among their workforce.
UPGRADE SOCIAL SECURITY NETS Voluntary workplace guarantees could be supplemented by a social security net styled after Denmark’s principle of “flexicurity”. In Denmark, employees have less protection from being made redundant but are supported with generous unemployment benefits as well as training to quickly transition into a new job.
INVEST IN UP-SKILLING AND RE-SKILLING Investments in skills and training are another essential element for a transition strategy towards an AI economy. Singapore for example has launched the SkillsFuture fund which supports citizens aged 40 or older to up-skill and re-skill with up to 3,000 USD per month. Similarly, France grants training credits of up to 5,000 EUR to every employee and job seeker to support the acquisition of new skills.
Towards a new “Gründerzeit”
AI is not a force of nature, it is a technology. And while it is obvious that AI will massively change the economy and the labour market, we as a society ultimately decide how AI will be deployed.
Governments need to make their social security nets “AI proof” and invest in up-skilling and re-skilling of workers to make the transition into AI jobs easier.
There may be parts of the population that are especially vulnerable to AI, such as graduates and workers in the second half of their working life. The latter could be supported with skills training, the first group with apprenticeship-style entry level roles that may be partially subsidized by the state and allow graduates to get into the workforce.
Governments should also incentivize the founding of new companies to pave the way to a “new Gründerzeit”. Just like the internet, AI massively reduces the barriers to start a new business. And even if many of these firms will fail, the experience of founding and running a company are important transferable skills.
In their essay “AI as Normal Technology”, Arvind Narayanan and Sayash Kapoor look at AI from a refreshingly sober perspective, without falling for AI doomsday scenarios or unrealistic promises of endless growth. Just like I have written previously, Narayanan and Kapoor argue that the discovery of a new technology is something very different than the diffusion of this technology into our everyday life, which often takes decades, not years.
For policy makers and CEOs, the reassuring message is that this is the time for an AI strategy, not an AI memo. Narayan and Kapoor believe that building resilience is the best approach to navigate through this period as we still discover how AI will shape our work and our lives.
This is sound advice that policy makers and CEOs should adhere to.
Philippe Aghion, Céline Antonin, Simon Bunel (2021): The Power of Creative Destruction. Massachusetts: Belknap Press.
Lynda Gratton (2022): Redesigning Work. London: Penguin Business.
Daron Acemoğlu, Simon Johnson (2023): Power and Progress. New York: PublicAffairs.