USA 
United Kingdom
Elon Musk revealed on Wednesday that Tesla is increasing compensation for its AI engineering team in response to OpenAI’s ‘aggressive’ attempts to recruit its staff.
Writing on X, Musk responded to an article from The Information reporting a move from a machine learning scientist moving from Tesla to xAI, Musk’s AI company:
“Ethan was going to join OpenAI, so it was either xAI or them. They have been aggressively recruiting Tesla engineers with massive compensation offers and have unfortunately been successful in a few cases.”
Musk went on to confirm that Tesla is upping the salaries for its AI engineers to compete with the packages being offered by OpenAI. “Tesla is increasing comp (contingent on progress milestones) of our AI,” the controversial businessman wrote.
The monetary move from Musk is unusual. Typically, tech companies such as Tesla prefer to avoid ‘counteroffering’ candidates who have attained lucrative packages elsewhere, and counteroffers are widely advised against.
The often-touted statistic is that 80% of employees who accept a counteroffer leave within the next six months. There’s no actual data to support that claim, but the arguments against counteroffers are compelling. The rationale is that once an employer knows the employee is open to leaving, they are likely to question the worker’s loyalty. They may be overlooked for future pay increases and promotions, and often the underlying issue behind the employee seeking a new role isn’t addressed.
The employee asks, ‘If I’m so valuable, why are they only rewarding me when they’ve got something to lose?’ The employer wonders, ‘If all that’s keeping them here is money, what if another, improved offer comes along?’
So, what’s prompting Musk to take this drastic move?
Well, this isn’t your typical talent war…
Big tech throws out the retention rulebook in ‘Craziest talent war’
“The talent war for AI is the craziest talent war I’ve ever seen!” Musk writes. For once, he has a point.
The battle for AI talent has seen the biggest tech companies throw out the recruitment and retention rulebooks.
Last week, HR Grapevine reported on the news that Meta CEO Mark Zuckerberg has resorted to directly emailing Google DeepMind employees about joining his company and making offers to candidates without conducting any interviews. Meta, like Tesla, is also revoking historic retention policies, attempting to keep candidates with job offers from other AI firms by counteroffering higher pay packages.
‘Rewarding our team’ | Target doubles bonuses for salaried employees
Google is also getting creative with its retention policy. Sergey Brin, a Google co-founder, personally called an employee who was considering joining competitor OpenAI and offered the employee a pay rise to stay.
Counteroffers won’t work, right?
Are attempts to counteroffer and keep employees with better pay packages a good idea for Musk and his big tech counterparts? It depends on the execution.
The details from Musk are vague – pay increases, he notes, are contingent on engineers hitting progress milestones – and it’s not completely clear whether employees are only entitled to a pay rise if they have received an offer elsewhere.
If pay increases are across the board, this is arguably a positive move from Musk to reward workers and keep compensation in line with the rest of the market and may serve as a compelling tool for retention.
But, if pay increases are only for those who have another offer in hand or for those Tesla pre-emptively expects to receive one, employees may well feel it is too little, too late, or that they are being taken advantage of. And of course, it may turn out that offers from OpenAI or competitors are too lucrative or compelling to turn down, even with the prospect of a better salary at Tesla.
However, with all the big players seemingly happy to throw out the recruitment and retention rulebooks, the battle for AI talent in a highly candidate-driven market could yet throw up some unexpected results.
It's a bold move from Musk, but it could just be the difference in keeping employees like the Ethan, the machine learning engineer, on his team.
