Big Tech layoff anxiety and AI: A leader's advice for peers

News and rumors of Big Tech layoffs have rarely been out of the headlines or far from subreddits and LinkedIn feeds since the AI wave started gathering serious pace in 2024. An atmosphere of unease and skepticism has become commonplace, leading to questions about whether adopting AI is a positive development for enterprises and society at large.

In this Q&A with TechTarget, Andrew Moore -- CEO of Lovelace AI -- shares his views on where AI can legitimately help, whether it's really to blame for recent layoffs, and how IT leaders can navigate its influence on teams.

Editor's note: This Q&A has been edited for clarity and conciseness.

Are Big Tech companies using AI as a scapegoat for layoffs?

Moore: I expect that happens, but I don't have the expertise to say so definitively. There's a closely related dynamic, though, which would probably look the same from the outside: When an organization is resistant to adopting automation, a CEO might use a carrot-and-stick approach. The stick version is essentially, "There are tools you could use to automate your work, but you're refusing to adopt them, so I'm going to force the issue by having fewer people around. The only way to survive is to do this."

That's a very tricky approach, because it's fairly common that shortly afterward, the company has to rehire people or bring in highly paid consultants, because it turns out the work couldn't actually be automated the way they assumed.

How can leaders maintain team morale amid uncertainty about whether AI will take people's jobs?

Moore: It's genuinely difficult, but there is a silver lining. I say that carefully, because I cringe when I see tech executives claiming it's all going to be great, which isn't universally true.

The silver lining is that individual employees who've wanted to change things from the bottom up are now more empowered to do so. If someone's been saying for five years, "It's crazy that we enter all this data manually; it's a shame we don't have an app for that," and management always said no to hiring someone to build it, that employee can now potentially build the solution themselves.

How much this helps really depends on the individual's position, and whether they're able to use it to create some wins, [so] the company becomes safer or delivers a better result for customers. That's a fairly rosy view, and it does assume a lot about access to training and the ability to use these tools.

But in many industries, it's amazing how many junior people are brilliant at figuring out how to use something like Excel to improve the way their organization works. Those are the people who stand to be more empowered by what's happening.

How should leaders communicate layoff decisions that are tied to AI? Should they be blunt and honest about it?

Moore: Layoffs, or reductions in force, are always incredibly painful. Nothing a leader says is going to have that much material impact on the people affected, but it's extremely important that there's follow-up support for those people in whatever comes next.

You don't usually see it, but if a CEO says something like, "Every year, we let go of the bottom 20% of performers," that effectively labels everyone laid off that year as having been one of the worst performers.

The truth is that in most layoffs, the decisions are hasty and unscientific. Nobody actually has the tools to determine precisely which individuals were the most or least productive. Saying something like that can damage the prospects of people who were caught in the crossfire, and who should be snapped up by the upstart companies about to compete with the one that just let them go.

How do you think leaders can balance AI adoption with job stability?

Moore: You have to be ready for it. If you're in an industry where you could plausibly be replaced by an efficient startup -- for example, what happened to taxi companies when Uber appeared -- that's a legitimate threat. In large, established organizations, such as a bank, an airline or a retailer, there's a real danger that a much more efficient, more customer-friendly competitor could appear, and you have to be ready for it.

However, it's easy to state this as a general principle -- reality is always more complicated. Try moving some people or some part of the organization into figuring out what your next chapter looks like. Can you build "the Uber" from within, instead of waiting for it to appear? Luckily, right now, you probably don't need to hire a large expert team to start this. You can use some available automation tools to make your existing staff more productive.

This is a good first step, and one that doesn't necessarily require slashing jobs. It also shows your board and shareholders that you're preparing for the possibility that your industry gets transformed by technology, while also maintaining your current customer base and being in the position to win the next generation of customers, too.

If you don't prepare, it can damage your organization and lose your existing customers, becoming a double hit once the Uber of your industry actually arrives.

Which industries are most at risk of being impacted by AI natives?

Moore: At the moment, it's unregulated industries, such as retail or sectors where there isn't a lot of government oversight. Heavily regulated industries like finance, healthcare and education give incumbents a real advantage over newcomers, because regulation won't let new entrants move as fast or as recklessly.

That protection will erode eventually, but probably over the next decade rather than the next two or three years. Retail, on the other hand -- they've hopefully learned some lessons already from previous waves of disruption, but they're absolutely going to be hit by anyone who works out a cheaper way of doing things.

Focusing on AI technology itself, what did you learn at Google Cloud that would be useful to share about the reality of AI integration?

Moore: I wouldn't have stayed in this industry if I didn't believe automation can improve the human condition in areas where humans, by themselves, don't quite have the capability. If you're monitoring a massive crisis and there are thousands of things going on, you need technological support to help organize it. After a major terrorist attack, for example, people often say, "I wish someone had joined the dots." Used well, AI could actually help with that.

So, the lesson for me at Google Cloud was seeing how my predecessors had done a really good job of thinking about AI as a technology that reworks how an organization works -- not something you just bring in and switch on.

It irritates me when I see some of the foundation labs implying that AI is really easy, and that you can just bring in a bucket of AI, pour it over your organization, and everything changes. That's never the case, especially in anything safety-critical. You need as much care in designing how you're going to do it as you would in building a new headquarters for that company. There's a lot to think about, and a lot of creativity required in how you introduce automation.

Is leaders' thinking that they can just "pour AI" over their organization and get outsized returns a real risk?

Moore: Yes. Organizational leaders are wise to it now, but a year ago, there was a lot of pressure on CEOs and other senior people, both in government and in large corporations. Boards were saying, "We're reading about how incredible AI is; you must be old-fashioned if you're not doing something with it right now. We want to see by next quarter that you've done something with AI."

That's led to some real disappointments. I don't blame the CEOs -- they were told it was going to be easy. It's taken a year of pain to realize that no, you actually have to work to build AI into your organization properly.

Looking ahead, where do you see the workforce and AI integration in 10 years?

Moore: Right now, the general public has a lot of distrust for AI and for those of us in the AI business, because this genuinely remarkable technology has been rolled out in such an antagonistic way.

My hope is that within 10 years, people will start to see the cases where AI is genuinely saving lives: food distributed more efficiently, fewer road accidents, fewer mistakes made in hospitals. That's the point where the public starts to see automation as something applied to improving the human condition, and that's the kind of work I've built my own career decisions around.

The important thing is that this won't happen automatically if every other industry just sits back and waits for someone else to make it happen for them. Everyone has to be involved in changing things if we're going to see the benefits.

Harriet Jamieson is a senior manager of custom content and writer for the IT Strategy team at TechTarget.