AI can help leaders transform a productivity windfall into tangible benefits for both businesses and employees
The view that AI will zap a meaningful portion of jobs carried out by humans is widely held, yet mistaken. It’s perpetuated by headlines that often take vague job descriptions, calculate the potential labor impact of AI and extrapolate it to hypothetical job losses.
This is catnip to AI alarmists. It makes it easy to jump to the conclusion that doubled productivity within a given function must demand an equally substantial wave of job losses.
However, this thinking assumes companies are only ever operating at the maximum capacity they wish they had for a particular job function. Which, of course, isn’t usually how businesses work. In most cases, it’s the opposite – companies only hire at the level they can afford.
So, let’s take a step back and – rather than assuming the worst – look at how leaders might transform a productivity windfall into tangible benefits for both businesses and employees.
Imagine you’re leading a software company. You have the budget to employ 10 engineers, based on your current revenue. Unfortunately, if you’re like most businesses on the planet, your customers’ long list of demands currently trumps those engineers’ capacity to deliver on them quickly.
So, you decide to invest in generative AI. Each engineer becomes – in this scenario – 50% more productive. Suddenly, tasks like writing new code, documenting code functionality and testing for bugs, are completed in record time. You now have an equivalent of 15 engineers working for you for the previous cost of 10. And you’re able to deliver on more of your customers’ priorities.
It’s a basic equation and, of course, results will vary. But AI does promise more productivity. So, what does this mean long term? For most companies with a pipeline of features on their product roadmap, it means they can finally start building them. Which, in turn, will generate more revenue. More revenue results in the growth of other functions within the business, meaning the creation of new roles – not least to support that thriving customer base.
At this stage, it comes back to you, the leader, to decide whether to remain satisfied with your 10 engineers with their output of 15 or redirect this incremental value towards hiring even more engineers that can support that next iteration. If it’s the latter, then AI has done the opposite of what skeptics might expect. It has empowered the business to hire more people, because each current employee’s productivity is higher, therefore generating more return – and, you guessed it, more revenue.
It’s important to recognize that, yes, a leader could decide to use that increased output as a reason to cut staff, keeping their original level of output flat. But as we’ve seen, by doing so, they would slash their own ability to innovate and serve customers. Which company do we expect to succeed – the one that increases productivity to invest in its product, its people and its customers? Or the one that attempts to cut corners and offer the bare minimum?
The above scenario works for pretty much any function within any business. Even back-office functions – those that govern employee workloads, large volumes of unstructured data and training, for example – that aren’t directly linked to revenue, are often bottlenecks to growth in one way or another.
And so, when we start to consider the world outside a zero-sum view of a specific function's productivity, we just might start to perceive AI’s potential, for both our people and our businesses, differently.
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