3 minute read

How to secure AI talent and succeed in AI recruitment

Name: 2025 DataIQ Discussion, featuring the 100 (EMEA) Live Reveal
Start: 2025-03-04
End: 2025-03-04
Location: London TBC

Data leaders must understand what is needed to recruit and retain AI talent in an environment where vacancies are prolific.

In a new era where artificial intelligence (AI) tools are the norm, data leaders need to ensure they are attracting the talent that can operate these tools effectively to achieve success. However, as DataIQ has noted previously, there has been a talent shortage across the data and analytics world even before the rise of AI-driven operations. Demand for AI talent is at an all-time high and supply is limited. Data leaders must provide a suitable amount of time and investment in recruitment and retention of essential talent, and this now needs to include AI skills.

Within the DataIQ community, different members have previously discussed their concerns surrounding the recruitment of AI talent as business decision makers may not fully appreciate the scope of skills required. To be a data leader that can showcase AI capabilities within the next five years, a clear and compelling approach to AI talent is needed; but this is not business as usual.

Stand out from the crowd

It cannot be reiterated enough that there is a chronic shortage of AI skills in the marketplace, which means that businesses must be able to stand out and draw attention to future talent. As a data leader, you must craft a unique and compelling value proposition to attract and retain this talent.

Data leaders need to understand what mix of AI skills – rather than jobs – are needed, have an insight into what those with AI talent are looking to achieve, provide reskilling and advancement opportunities (as AI tools are not going to stop evolving) and be able to keep high levels of engagement.

The 2024 DataIQ AI awards recognises and celebrates companies, individuals, and programmes that have made positive impacts using AI on society, environmental and health successes, and governance best practice over the past 12 months.

Tailor the hiring process

You want people to know you are serious about attracting the right talent, so ensure that the hiring process is updated and amended to reflect this. Work closely with HR to be a part of the hiring process and have direct contact with the candidates. It would be recommended for you to sit through the interview process and fine tune any points prior to make sure that AI talent know this is the place they want to join.

Things to consider for AI talent

As mentioned, this is not business as usual and a new angle on talent recruitment is needed to secure new team members with AI specialisms. There are numerous things that should be changed when trying to entice talent to the team:

Make sure non-tech-related differentiators are highlighted as this will differentiate competition with other tech companies.
Avoid the established slow process that is led by generalist recruiters; specific talent is required, and this must remain the central focus.
There must be a consideration for the broader mix of skills needed to succeed with AI and complement the company objectives; do not pay premiums for people that cannot provide the broader skills required.
Highlight the advancement opportunities for AI talent within your organisation.
Be open to the new talent moving around within the organisation; diversity of thought is essential in achieving success.

Organisation

It is easy to fall into an ad hoc approach to employing AI talent, particularly as the technology rapidly evolves and the skills shortage means gaps need to be filled. You cannot encourage people to join a business with a scatter-shot approach – there needs to be organisation in the way that AI is being addressed for the business.

For example, in businesses with low data maturity, the IT function will often own the data architecture, systems, and analytics. Furthermore, data capabilities are sprinkled throughout the business (often in silos), but no standardised roles or communities of practice are in place for sharing AI knowledge. These must be addressed before AI talent can be effectively introduced into the business. Chances are that data leaders will take the lead when it comes to AI hires, but this needs to be examined and a plan laid out with other business functions.

Anticipate impacts

The existing team members will likely be impacted by incoming AI talent, which has been seen before with disruptive technologies. The new hires need to be made to feel welcomed and included, which is difficult to do when existing team members hold resentments against the new technology. There are legitimate worries about how AI will affect existing roles, and it is essential that leaders are aware of this and address it accordingly. Much like when computers were first introduced into businesses, the ways in which different roles operate will naturally evolve to utilise the tools available.

As AI solutions continue to be incorporated into daily business operations, the roles of other team members will begin to evolve – and business leaders will not be exempted. This will likely require upskilling and perhaps even a redesign of the team structure – this takes time and will need funding. The amount of internal AI talent will naturally grow, and it is pivotal that this talent is retained. Not only will this improve the AI capabilities of the business, but it will encourage new AI talent to join as the culture embraces data and AI.

To enter the 2024 DataIQ AI awards and get the recognition you deserve, complete the free award entry form before the March 22 entry deadline. The AI awards will be announced at the DataIQ Summit in Miami.