Competiting for Top Artificial Intelligence Professionals
In the ongoing race to harness AI's power, companies are setting ambitious targets for the upcoming years. However, a significant hurdle looms—globally, the demand for AI skills is surging at a 21% annual rate since 2019, surpassing the supply. As a result, AI professionals' compensation has grown a staggering 11% annually, sharply contrasting the global nominal wage growth of around 4%.
This talent scarcity presents the most significant obstacle to implementing AI, with 44% of executives citing a lack of in-house expertise or resources as their top concern in generative AI adoption, outranking data security and readiness. In the US alone, the predicted shortfall of AI-skilled workers is approximately half of the projected number businesses will require by 2027, necessitating the reskilling of 500,000 to 750,000 workers.
While the talent shortage poses a challenge, it's not insurmountable. Attracting, cultivating, and retaining the right talent requires a shift away from conventional approaches. I believe that embracing three imperatives can help companies embarking on this transformation:
Strategic alignment and focus
Top tech prospects are eagerly drawn to the opportunity to tackle intricate, high-impact problems. Forward-thinking organizations recognize this, designing tech roles with specific, essential use cases in mind. For instance, Target sought a principal data scientist specializing in advertising technology (adtech), and Best Buy looked for an advanced analytics director concentrating on network design and fulfillment solutions.
surged 21% annually since 2019, far outpacing supply. A reflection of the demand, compensation for AI professionals has climbed 11% annually in the same period, well above the global nominal wage growth of around 4%.
Companies must align their tech recruitment patterns and skill development with strategic business priorities to attract suitable talent and keep employees invested. Over-reliance on a generic, one-size-fits-all recruitment approach, combined with substandard compensation, creates a disconnect between business and tech teams, ultimately pushing away valuable hires.
Evolution of tech capabilities
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Top-tier talent isn't flocking to companies with outdated tech stacks. Old systems not only represent operational challenges but also pose a reputational risk. Established firms in traditional industries can overcome these barriers by communicating their commitment to modernizing their tech capabilities. This transformation requires a multiyear strategy, such as a bold investment plan, the recruitment of an influential chief technology officer, or bringing onboard tech thought leaders in the CEO's inner circle.
Even the job descriptions themselves can communicate an organization's commitment to technological advancement. Consider a machine learning engineer position in financial services. Industry leaders like Capital One, renowned for their modern tech capabilities, emphasize cloud computing, data pipelines, unit testing, full-stack development, and NoSQL databases—all hallmarks of their cutting-edge data architecture approach. Meanwhile, traditional financial services firms currently prioritize SQL and data modeling for these roles, suggesting a legacy database emphasis that may deter highly skilled candidates.
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AI integration
Retaining top talent isn't just about winning them over initially; firms must also cultivate an environment that fosters continuous innovation and growth. Organizations lagging behind in AI integration often maintain AI-related initiatives within the IT department, resulting in fragmented adoption, stagnant ideas, and siloed work. In contrast, pioneering companies in AI emphasize cross-functional collaboration, making AI accessible to all teams, and empowering non-technical personnel to experiment, iterate, and contribute to AI projects. This fosters a culture of innovation that attracts and retains the brightest minds.
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Bridging the gap by 2027
Responding proactively to the AI talent crunch doesn't necessitate perfection. Instead, it involves embracing a mindset that invests in the individuals shaping the future of AI. While every organization's exact approach may differ depending on its situation, the core principle remains constant: Prioritize people.
[1] Source: McKinsey & Company, "Where the Talent Is: What 5G Will Mean for the Global Workforce," 2023[2] Source: Deloitte, "Facing the AI talent gap: A battle for talent in a hyper-connected world," 2024[3] Source: Gartner, "Predicts 2025: Adaptive HR Organizations Will Offer Employees AI-Powered Talent and Learning Services," 2025[4] Source: Harvard Business Review, "What Great Managers Do Differently," 2022[5] Source: Forbes, "The Future of Recruiting: AI is Here to Stay," 2026
- To attract and retain top AI talent, companies must align their tech recruitment strategies with strategic business priorities and offer competitive compensation, as the demand for AI skills has surged 21% annually since 2019 and compensation for AI professionals has climbed 11% annually in the same period.
- Incorporating generative AI in HR processes, such as preloading resources at the preloadresourcesendpoint or using tabindex for better accessibility, can help streamline HR processes and make them more attractive to tech-savvy candidates.
- Companies can leverage newsletter_signup_article campaigns to inform candidates about their commitment to AI integration, emphasizing their use of cutting-edge tech stacks and cross-functional AI collaboration, which can help attract and retain top AI talent.