The Automator’s Dilemma

The AI era comes with a peculiar tension. On the one hand, it has never been easier to automate routine tasks, streamline operations, and scale with far fewer people. On the other, every quarter we hear more and more CEOs proudly declare how much of their work, or even their code, is now handled by AI. The subtext is not subtle: they’re dog-whistling to investors that they expect to reduce costs and improve margins through layoffs and/or reduced future hiring. Whether directly or indirectly, AI is helping make those job losses possible.

Working in automation and AI today, it’s impossible - or, rather, irresponsible - to ignore the risk of contributing to job displacement. Before founding work.flowers, I worked in investment banking and digital advertising/social media (at Twitter, back when it was still Twitter) - two industries fraught with inherent tensions and conflicts of interest. These experiences taught me the importance of thoughtfully considering the tradeoffs in my work, rather than ignoring how I might be complicit in enabling potentially harmful societal trends.

That’s why our focus is on a very different kind of client: early stage startups that simply don’t have the resources to hire full-time operations staff with deep technical expertise. These companies now operate under immense investor pressure. Every hire must be laser-focused on directly generating revenue through building product or selling it. In that environment, operational maturity often becomes a “someday” goal, postponed until the team is larger and the market more forgiving.

The irony is that scalable operations matter most early on. Waiting too long can make future growth messy, slow, and costly, and operational debt comes back to bite you eventually, just like tech debt does. By offering technical operations on demand - or ops as a service - we give these founders the operational leverage of a much larger team. The kind that they can’t afford to hire full-time (yet).

Beyond the quarterly earnings calls and dystopian headlines, I hold a more optimistic vision for AI’s role in the economy. Yes, large employers will continue to use automation to cut costs and headcount. But AI also lowers the barrier for individuals and small teams (like us!) to launch new ventures - services, products, and entire business models that would have been unthinkable even five years ago, or that would have required too much upfront capital for most sane people to take the leap.

In that way, AI could have a “curve-bending” effect: redistributing economic value creation and opportunity away from a few mega-corporations and into the hands of thousands of small, nimble businesses. We’ve seen this before. Meta’s innovations in hyper-targeted, in-feed digital advertising gave rise to a wave of niche direct-to-consumer brands that simply would not have been able to find their audience before. AWS dramatically lowered the time and capital required to launch a software startup.

I believe and hope that AI can play the same enabling role for the next generation of small businesses, including services businesses like ours, as well as new business models we can’t even envision because they haven’t been invented yet.

In one of my favourite books of all time, NYU Stern economist Thomas Philippon writes about the increasing concentration of economic activity into a smaller and smaller handful of corporations, and the effect that trend has had in terms of stifling competition and innovation. This moment, I hope, represents our best shot at reversing the Great Reversal that has occurred over the past 20 years.

The question isn’t whether automation will change the way we work; it already has, and there’s no putting the genie back in the bottle. What we can influence is who this technology will empower. On our part, we want to work with the organisations that need it most: those building something new with more ambition than resources, and those working to make the world better on budgets that rarely match their mission.

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