Should CTOs stop hiring and focus on AI?

I've had this question from several CEOs. In some cases they shrunk in last year's tough economy. In other cases they have new funding but are deciding where to invest. Here's my perspective.

Photo by Brian Patrick Tagalog on Unsplash

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Over the past few months, several clients have posed similar questions regarding strategic decision-making related to AI, so I thought it would be helpful for others if I wrote up some of the information I’ve shared with them.

The key questions I’ve been asked (paraphrased):

• Is AI a truly disruptive trend or a bubble?

• Should I stop pursuing growth through hiring and instead focus on improving the efficiency of how we build software using AI?

• What software development principles are subject to change in the AI-assisted software development era?

• How can I encourage the development and data teams to explore the possibilities with new AI capabilities?

• How should I think about spending on software developers and AI in the near future?

These same questions were discussed at several tech leader events I recently attended, and I’ve also seen some similar threads in the blogosphere. It appears these are questions in the Zeitgeist.

In this post, I will focus on the following question, and I have addressed the other questions in other posts:

Do AI-assisted software development efficiency gains mean smaller teams?

There appear to be several camps regarding whether AI will lead to job losses. Some analysts project large-scale job losses. Others argue that new types of jobs will replace the jobs lost. Another group I covered in a recent post suggests that AI is largely unproven, and the jury is still out on whether technologies such as generative AI will have a significant impact.

From my vantage point, through my career experience leading teams who built AI capabilities for competitive advantage, and through the visibility I have by working with the companies I am now, I think it’s safe to say that the evidence that AI is already starting to have the anticipated impact is discoverable by those who look for it.

The presence of a bubble is not evidence of a lack of value.

This doesn’t mean there isn’t an investment bubble. There certainly is - one can examine the economics implied by the astronomical investments in foundational model providers such as OpenAI and Anthropic, and then perform some back-of-the-envelope calculations to determine what would need to be true to support those assumptions.

As an industry, we seem to have developed a knack for inflating markets around opportunities. No doubt, many people have become skilled at profiting from such bubbles.

Corrections from such bubbles can often be painful and even introduce key risks. But the presence of a bubble does not refute the existence of underlying value.

What is important is what is changing, and especially what is changing not just because of the presence of investment but because of the fundamental changes in the technology landscape.

What components have evolved, and what effect has that had on other components in the value chain? Which ones are viable only with the current investment levels, and which ones are resilient to a correction?

AI-assisted development has already changed software development forever

A case in point is AI-assisted software development. There are changes across the entire SDLC that shift the software workflow to the point where it's almost unrecognisable from how software development occurred before.

There are, of course, still practices that are from the before times, but how you leverage these has evolved. For instance, unit testing was an early warning system, allowing you to detect issues quickly. Now it’s feedback for your assistant and a source of instantaneous fixes. Test-driven development is a source of signals for the intent of the software, which can help provide more reliable assistance and so on.

Often, when people refer to AI, they are talking about the current generation of generative AI systems, which are only a subset of what had previously been described as AI. There may well be an investment bubble in the impact that generative AI will have across all the industries where it could be applied. I am more sceptical that the effect in software development is quite as overstated.

Even if the foundation models spiked in price, it’s practical for companies to deploy models locally, providing an almost equivalent experience, which improves both productivity and the quality of the software developed. The genie is out of the bottle, and there is no going back.

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The Advice I’ve Given CEOs

1. Most companies already overhire

2. Grow only when necessary.

3. AI-assisted development offers the opportunity to achieve more and better results.

4. AI-assisted development changes the assumptions, such as team size and composition.

5. Conclusion