The Future of Work: How Automation and AI are Impacting Tech Work Culture

A note from 2026. I wrote this in May 2023, a few months after everyone started paying attention, and I have left the text below exactly as it was.

The part I would still defend is that the change worth watching was to the shape of the work rather than to headcount. The part I got wrong is the framing. Treating “automation” and “AI” as two separate forces was already stale when I published it, and “the future of work” turned out to be a far more boring question than it sounded: not whether machines take jobs, but which specific Thursday-morning task is worth handing over, and whether anyone will still be maintaining it in a year. Almost everything I have actually been paid to do in this area since has been that second question.

What I think now is at the end.

The tech industry is constantly evolving, and with it, the way we work. Automation and AI are two of the most disruptive technologies of our time, and they are having a profound impact on the tech work culture.

Automation

Automation is the use of machines to perform tasks previously done by humans. This can include anything from simple tasks like data entry to more complex tasks like customer service and even surgery. Automation is already having a major impact on the tech industry, and it is only becoming more prevalent in the years to come.

AI

AI, or artificial intelligence, is a branch of computer science that deals with the creation of intelligent agents, which are systems that can reason, learn, and act autonomously. AI is still in its early stages, but it has already made significant progress in a number of areas, including natural language processing, image recognition, and robotics.

How Automation and AI are Impacting Tech Work Culture

Automation and AI are having a major impact on tech work culture in many ways. First, they are leading to the displacement of some jobs. As machines become more capable, they are able to take over more and more tasks that were previously done by humans. This is leading to job losses in some areas, particularly in manufacturing and customer service.

Second, automation and AI are changing the nature of work. As machines take over more tasks, humans are being freed up to focus on more creative and strategic work. This is leading to a shift from a “blue-collar” workforce to a “white-collar” workforce.

Third, automation and AI are leading to a more collaborative work environment. As machines become more intelligent, they are able to work more effectively with humans. This is leading to a more team-based approach to work, where humans and machines work together to achieve common goals.

The Future of Work

The future of work is uncertain, but it is clear that automation and AI will play a major role. Businesses should start thinking about how these technologies will impact their workforce and culture. By planning ahead, businesses can ensure that they are prepared for the changes that are coming.

Here are some tips for businesses that are looking to prepare for the future of work:

• Invest in training and development. As machines become more capable, it is critical to ensure that your employees have the skills they need to succeed in an evolving economy. This means providing them with training on the latest technologies and updated ways of working — a culture of continuous learning rather than a one-off course.
• Create a culture of innovation. Innovation is the key to success in the future economy. Businesses need to create a culture where employees feel comfortable taking risks and trying various things.
• Be flexible. The future of work is uncertain, and businesses need to be prepared to adapt to change. This means being flexible in terms of work hours, work locations, and even the types of jobs that are offered.

The future of work is full of possibilities, but it is also full of challenges. By preparing for the changes that are coming, businesses can ensure that they are ready to succeed in a changing economy.

---

What I Think Now

Three years on, the question I get asked is never “will AI change our industry.” It is some version of “everyone here is using these tools and I cannot point at a single hour we got back.”

That usually has a boring cause. The work that got automated was the work that was easy to automate, not the work that was expensive. Nobody scored the candidates before building, so the thing that shipped was whichever one someone found interesting on a Tuesday. And the automation that did save real time now has no owner, so the first time it breaks quietly, everyone goes back to doing it by hand and nobody mentions it.

The same discipline applies here as anywhere else: solve one problem completely before you generalise, which is the argument I made about over-abstraction in code and in startups. Most failed automation projects are that mistake wearing a different hat.

So the honest version of this article’s advice, in 2026, is narrower than what I wrote in 2023. Find the repeated work that actually costs hours. Check the data for it already exists. Ask what happens when it is wrong, and whether anyone would notice. Then automate the two or three that survive all of that, and give each one a name of a person who owns it.

That is roughly what an AI and automation audit is — going through the real workflows and coming back with the three worth doing, and the seven that are not.