Editor’s note: The following is a guest post from Kjell Carlsson, VP analyst at Gartner.
Tech giants might be trying to lure AI researchers with mind-boggling compensation packages, but everyone else needs affordable AI talent.
To successfully drive value with AI, organizations need AI leadership, data scientists, AI engineers, product managers and other talent. CIOs need this talent to identify the best AI opportunities across the business, apply AI tools, integrate the features across business applications and, above all, create differentiated, transformative AI solutions tailored for specific use cases.
But the question remains: How can CIOs compete for this talent against the allure of startups and tech giants that offer millions of dollars in compensation packages?
The shortage of experienced AI talent is real. In a recent Gartner survey, only 17% of firms report having enough qualified AI talent. Further, a Gartner Peer Community poll showed nearly half of respondents found that the costs associated with talent attraction reduced the impact of AI projects.
The good news is that most organizations are far better equipped to succeed in the war for AI talent than they realize. With the right strategy and leadership, all organizations can punch above their weight, hiring and retaining AI teams that deliver extraordinary results.
To get there, it's critical to understand business needs, look for the right attributes, build a talent pipeline and gain insight into what makes the organization the place where you want to work.
Finding high-potential AI talent
AI is still so new that most organizations don’t know what kind of talent they actually need. Rather than figure this out, leaders are tempted to rely on generic indicators of AI success, including experience at top tech companies, senior titles and degrees from elite institutions.
But this is a losing strategy in the search for affordable AI talent. These individuals are costly and hard to retain.
Instead, organizations should recruit for the specific, actual and upcoming needs of their AI projects. A specialist in fine-tuning large language models isn’t needed if all they have to work with is a low-code tool for developing simple chatbots. Knowledge of agent-to-agent protocols is exciting, but experience building retrieval augmented generation solutions will likely be more immediately useful.
Of course, CIOs will need to invest in the hard work of creating a detailed AI strategy and mapping out planned AI projects, but the effort will more than pay for itself in terms of the ability to hire effectively, not to mention the ability to execute AI initiatives generally.
When it comes to experience, the reality is that there just aren’t enough candidates with substantial real-world AI experience. Everyone will need to continuously learn new skills to keep up with the rapidly changing AI landscape.
Companies should recruit candidates who have the aptitude, curiosity and entrepreneurial mindset to learn and apply both the technical and interpersonal skills necessary for success. With a strong onboarding and training program, an organization can create its own AI talent in a cost-effective way.
Communicate the company's value proposition
Like everyone else, AI talent seeks purpose-driven work. Given that an organization at this stage has been successful enough to be able to invest in an AI team, odds are that it has plenty of unique aspects that make it a compelling place to work.
It's key to highlight these positive attributes as well as the exciting projects the team will be tackling, the unique mandate they’ll help drive forward, the supportive community, the rich data resources or cutting-edge tools at their disposal and the opportunity to drive real-world impact.
Also, companies can't wait for talent to come to them. Partnerships with universities and professional societies can help access emerging talent pools. Internships and hackathons can help engage potential hires early and provide invaluable insight into their skills.
Existing staff is an asset, too. Upskilling business analysts, data engineers or software developers through targeted training programs can unlock their AI potential while reinforcing loyalty among employees who already understand the business context. This multipronged approach lets CIOs access motivated individuals who are excited to contribute as AI becomes central to company strategy.
Compete smarter for AI talent
The race for top AI talent is only growing more intense. Winners will be those who play to their strengths.
Organizations must go beyond conventional recruiting tactics by actively showcasing their mission, culture and opportunities for meaningful impact including addressing hot-button issues like AI’s environmental footprint or social good.
Leaders need to communicate why their work matters not just to shareholders but also to the talent they hope to attract.
Proactive organizations seize market opportunities as they arise, whether it’s tapping into fresh pools of skilled professionals during industry layoffs or welcoming disillusioned experts seeking greater flexibility in hybrid or remote roles. The best candidates aren’t chasing paychecks. They want collaboration with smart colleagues, engaging projects that stretch their abilities, and a chance to make a real difference for customers, employees or society at large.
And if an organization really doesn’t have anything to attract eager AI talent, CIOs just might want to consider a career change too.
