Apple needs good AI acquisition hires

When it comes to artificial intelligence development, Apple seems more interested than usual in seeking out good acquisition targets, potentially building on the small acquisitions it makes most months. The company has, in fact, led the industry when it comes to strategic AI acquisitions since 2023.

Why? Because it must.

And the reason is pretty straightforward: the company is putting huge resources into Apple Intelligence development, but it can’t get the staff it needs for the big push.

It takes a village

A quick glance at Apple’s recruitment website today revealed that it currently has 399 open roles in its machine learning and AI teams. That’s almost enough people to form a small village.

Apple’s search for villages of AI professionals isn’t unique; everybody’s doing it. OpenAI lists 149 jobs. Google has 277 machine learning jobs. One year ago, AI accounted for 27% of all open UK tech roles. Given that the hype and expectations in the sector have only grown since then, it’s hard to believe there’s been any decline in demand.

What’s driving this is that as the number of potential AI implementations grows, so does the demand for workers to build them. Large, small, and medium-sized players across enterprise tech share the need. 

They aren’t just being greedy. They understand the huge strategic imperative behind the AI evolution.

Nations, technology companies, a growing number of enterprises, government organizations, and start-ups are all competing to recruit the best staff. They know that, “we are at a tipping point in business and society where AI will revolutionize how we work, live and interact at scale,” Mohamed Kande, global chair for PricewaterhouseCoopers International, explained last year.

More jobs, few people

Yet they recognize that as ever more processes get digitized, the demand for people with experience will become a hindrance to AI industry development because that demand is not being met.

As McKinsey explained last year: “Our survey of 3.5 million job postings in these tech trends found that many of the skills in greatest demand have less than half as many qualified practitioners per posting as the global average.”

And yet the World Economic Forum predicts AI will create 97 million new jobs by the end of the year.

Like everything else, the global race for brains to build AI is, of course, made a whole lot harder by trade embargoes, and ever-increasing international tensions. The ever-evolving regulatory landscape forms another barrier to industry growth. The same skills shortfall exists across other critical tech areas, too: edge, cloud, quantum computing, data process management, analytics, CSR. As these sectors grow exponentially, the skills gap continues to widen. 

So, if you can’t recruit the talent, what do you do? 

If you can’t hire it, buy it

Globally, there were 245 AI-related industry acquisitions in Q1 2024 alone, said McKinsey. Apple, then, is right in the thick of it all with the acquisition of numerous AI startups in 2023 and its famous purchase of Darwin AI and at least three other AI-related firms last year (including Drishti, Mayday Labs, and Datakalab).

The company tends to be tight-lipped when making acquisitions, so it might well have secured even more companies we just don’t know about. We only know of the IP purchase from Mayday Labs as a result of an EU filing.

The thing is, this is all about scale. That means that even if Apple does recruit that village of AI experts, the acceleration in demand for AI is going to continue, and it will probably need to recruit a second village full a few weeks later. Again, it won’t be alone. That need for skill is an imperative forcing tech firms (most likely including OpenAI, and certainly including Apple) to focus their efforts on specific goals when building new generative AI (genAI) services. While effective management within scarcity has always been par for the course — Apple is really good at this — those companies who best approach development within those constraints will be best placed to make it all the way to that looming AI mountain and climb to the top. 

All the same, to outsiders focused on AI-related hype, the reality is that the challenges facing industry evolution mean innovation will soon begin to seem incremental, rather than revolutionary, as the “move fast, break things,” approach is replaced by a more business-like, objective, and slow strategic resource allocation-driven approach. Those who break through the noise to deliver the highest value tools and services will be those that win this AI space race.

As long as they can get the staff.

You can follow me on social media! Join me on BlueSky,  LinkedIn, Mastodon, and MeWe.