These days, attracting talented AI experts to your company is hard. Total global demand is measured in millions while total available talent is an order of magnitude smaller. There are very good reasons for the demand: ignoring AI today is akin to ignoring the internet twenty years ago.

Throwing money at it is not a viable option. You must offer competitive rates, of course, but beyond that the returns quickly diminish. 

To attract AI talent, you need to improve the work environment of your company. (Unless, of course, it’s already perfect, in which case please email me because I want to talk to you.)

AI experts are human beings. Obviously, sure, but much of what you need to attract them is no different from what is needed for attracting any human being to your company. I use ‘company’ deliberately here over ‘business’; the former originates from the late latin ‘companio’, literally ‘bread fellow’, while the latter stems from the old English ‘bisignes’, meaning ‘care, anxiety, occupation.’ Attracting human beings is more about companio than bisignes. 

The whole ‘work/life balance’ concept, or dichotomy, has never sat right with me. Work is life. It’s not all of life, but it certainly is an important and significant part of life. And whatever we mean when we say ‘life’, as being apart from ‘work’, certainly is a lot of work, a lot of the time. 

Work should not be about turning ‘life’ off. Work should be good living – close fellowship with work companions, in a great work environment. To attract AI talent, we must first create a great work environment for human beings by creating great company culture, great structure and great incentives.

You can get a good start by adhering to the following principles. 

Principles for creating great structure

• Every project gets a top-management sponsor, ensuring resources and overcoming bureaucratic hurdles
• Create separate divisions with their own P&L for proven, transformative projects and let the people move with the projects 
• Cross-functional teams over ‘specialist labs’, every time
• Keep hierarchies as flat as possible
• Don’t do transformation – new business models – within the same structure that runs your existing business models. 

Principles for creating great culture

• Allow people to spend some time developing whatever they want – keep them accountable for the outcomes.
• Accept failure – but keep people accountable for learning from those failures. 
• Reward learning from failure as much as succeeding
• Let people take initiatives and make decisions
• To paraphrase Simon Sinek, people are in your charge, more than you are in charge of them. Culture without empathy is hollow.
• Be honest and transparent. Don’t allow dishonesty anywhere. 
• Always explain, always engage
• Set clear expectations for everyone

Principles for creating great incentives

• Establish career ladders for non-managers, such as data scientists and AI experts, so that they can advance to the top without competing with managers.
• Reward teams that create successful new products.
• Spin-off new business models when they show real promise. Create new divisions with their own P&L, allow the creators to follow and give them ownership in the spin-off. This is especially powerful for those AI experts who come with an entrepreneurial mindset – and those are the people you really, really want to attract!
• Set goals for top managers stating that a significant chunk of all revenue must come from new divisions/units. 

For all of these, the core principle is engagement – everyone is involved – and explanation – everyone understands why their work environment needs to improve. Ignoring these fundamental principles sabotages the culture that you’re going for in the first place. 

Emphasize what AI experts love

In addition to those fundamental human needs, top-tier AI experts – machine learning researchers, data scientists, etc. – typically feel certain needs more strongly: 

• Working on difficult problems
• Working with the best people
• Easy access to good, diverse, valuable data
• Working in cross-functional teams with SMEs so they can really understand the problems they are solving
• Seeing that the solutions they build are used by actual customers and users.

This boils down to common sense steps and priorities. For example, while you can go for attitude over skills, don’t settle for mediocre attitudes. And you absolutely need someone on each team with strong, not mediocre, AI skills.

Invest in data infrastructure, be increasingly ambitious in how you leverage AI, and give your teams access to customers all the time – make that easy for them. Help them with communication and teach them to become better at it.

For real-life examples of companies that have succeeded in creating great work environments, see these quotes from people at the top places to work in 2021, according to Glassdoor. Can you recognize culture, structure and incentives in these quotes?

Creating a combination of great culture, structure and incentives comes with enormous benefits beyond attracting AI talent. It should be a no-brainer.