This essay is based on a conversation with Max Votek, co-founder and managing partner of Customertimes, an enterprise consulting firm that helps Fortune 500 companies implement AI. This essay has been edited for length and clarity.
Companies are rushing to blame artificial intelligence for layoffs. But as I sit and advise Fortune 500 companies on AI implementation, that’s often not the whole story.
I’m the co-founder and managing partner of Customertimes, a 1,000-employee consulting firm that helps companies implement AI. Prior to that, he spent nearly 10 years leading technology transformation projects in the pharmaceutical industry. I work with CFOs, CIOs, and CEOs every week, and what we hear behind closed doors often doesn’t match what’s out there.
Here’s what people misunderstand about AI-driven layoffs.
Companies need to be honest about AI
AI has an image problem, and companies are making it worse by refusing to explain what’s going on.
When a company announces layoffs, reports record profits, and never explains where those savings went, people naturally assume the worst. If a company withdraws If there’s an information vacuum, someone else will fill it.
People want transparency. They are asking companies to explain how they are using AI, how they are protecting customer data, and whether the benefits are being passed on to employees and customers.
That’s why I believe companies should disclose how their AI savings are being used. If the profitability from AI is flowing to employee bonuses, lower customer prices, or investments to improve the business, companies should say so.
A simple ledger showing where those profits go would eliminate many doubts.
Currently, too many companies are silent. And they end up writing conspiracy theories themselves.
Where do the savings actually go?
Our research found that 86% of adults believe companies that save money through AI should lower prices for consumers. I think that’s a natural expectation.
Many people think that companies will lay off employees, pocket the savings, and hand out larger bonuses to executives.
It’s even more complicated than that.
Behind the scenes, companies are being billed huge amounts by AI providers. CFOs and CIOs regularly tell me that they underestimate the cost of tokens and many organizations are burning through their AI budgets much faster than expected.
Some executives are even talking about “token maximization,” which can burn through allotted AI spending within months without achieving the productivity gains originally anticipated.
In addition, companies invest heavily in protecting internal knowledge. They don’t want their proprietary business processes and trade secrets flowing into public, large-scale language models, so they’re building additional AI infrastructure to keep that information in-house.
These investments aren’t cheap.
The public often has misconceptions about where AI savings will actually go. In many cases, it does not simply flow to executive compensation. They are engulfed in infrastructure, token costs, AI licensing, and building secure internal systems.
Companies have always sought efficiency
Long before generative AI, companies were using robotic process automation to eliminate repetitive tasks. The goal hasn’t changed. It’s about finding inefficient business processes, automating routine tasks, and freeing people from repetitive, unpleasant tasks.
I rarely hear executives talking about replacing humans with AI. I talk to CFOs, CIOs, and CEOs every week, and internal conversations aren’t structured that way.
Instead, I think many companies are using AI to explain restructuring decisions that they had already planned.
AI often masks underlying inefficiencies. Some companies identify processes that no longer make sense, restructure them, and wrap those decisions in AI language.
Restructuring is nothing new. Companies have always reorganized to increase efficiency. The problem is that many companies are not being honest with their employees and shareholders about what actually motivates them to make these decisions.
The reality is more nuanced than many headlines suggest. AI is very good at handling repeatable tasks, but it is no substitute for accountability. You can automate CEO presentations with AI avatars, but you can’t automate the responsibilities that come with leading a company.
I have also seen many employees adapt. My company invests heavily in AI training, allowing our testers and business consultants to learn new AI skills in just a few weeks.
In many cases, you’ll be able to offer more, not less.