Beyond Compensation: The Keys to Retaining Top AI Talent

Much of the conversation around AI focuses on attracting the right talent, but that’s only half of the challenge. The AI landscape is rapidly evolving, and organizations must hire and retain teams that will grow and evolve with them. With AI skills in such high demand and competition for talent intensifying, how can organizations prevent low retention from slowing innovation?

The latest data on AI hiring comes from a new IDC InfoBrief, commissioned by Deel, AI at Work: The Role of AI in the Global Workforce. The survey explores AI adoption, workplace transformation, and governance, and also includes insights into what helps organizations retain AI talent by identifying what they care about the most:

1. Cutting-edge tools and projects
2. Clear growth and promotion paths
3. Strong company mission and values

With these insights, leaders can build strategies that foster loyal and engaged AI-driven teams, easing adoption and keeping innovation on track. This article explores the three most influential factors in retaining AI talent, and how organizations can translate each into action, starting with access to cutting-edge tools and projects.

1. Cutting-edge tools and projects

49% of AI talent value access to cutting-edge tools and projects, making it the top consideration besides compensation. This is hardly surprising, as top AI talent thrives on experimentation and solving meaningful problems with innovative new solutions.

A common pitfall for businesses is holding onto legacy stacks and bureaucratic processes, which stifle innovation. While keeping up with the pace of change is challenging, adopting a ‘wait-and-see’ attitude for too long means lagging. AI talent want to keep up with their peers, and be part of the conversation of where AI is heading, not stuck building the same automated workflows over and over.

The solution: Freedom to experiment

This doesn’t mean letting your AI teams run amok. It means setting up spaces and channels for experimentation and free thinking. Teams should be encouraged to test out new tools, whether you’re in the market for a new stack or not. Rather than seeing it as a waste of time, see it as an opportunity to learn and better understand the evolving AI landscape. Few can predict which tools will be the next ChatGPT and which will disappear without a trace, but you can be certain that your AI talent wants to be part of the discovery process.

• Give teams sandbox access to test and deploy emerging AI tools. Provide secure, cloud-based environments with controlled datasets and API integrations so teams can experiment without risking production systems.

• Create innovation sprints or “AI labs” where talent can prototype ideas. Equip these labs with version-controlled repositories, model registries, and lightweight MLOps frameworks to rapidly test and iterate on proofs of concept.

• Encourage cross-functional collaboration between data, product, and business teams. Establish shared development pipelines and documentation standards that allow data scientists, engineers, and domain experts to align model outputs with real product objectives.

2. Clear growth and promotion paths

AI is evolving too quickly for org charts to keep up. While AI professionals expect to evolve alongside technology, organizations struggle to understand what their paths to advancement should look like. Yet, according to the survey, 43% of professionals value clear growth paths.

While many businesses promise growth, they’re unable to be transparent. This leads to flat structures that lack senior technical roles, and undefined pathways for hybrid roles (AI lead, engineer-researcher, AI-focused operations managers, etc.).

The solution: Transparent paths and learning opportunities

Retaining AI talent means rethinking your org chart and making sure their careers aren’t at risk of stagnation.

• Define dual career ladders (technical and managerial tracks). This gives AI professionals the ability to advance without leaving their area of expertise, ensuring both technical contributors and people leaders see equal recognition and opportunity.

• Offer personalized learning and certification pathways. Tailor development plans to individual skill profiles and career goals, using engagement data to recommend relevant AI courses, certifications, and upskilling opportunities.

• Provide regular growth check-ins outside of annual reviews. Frequent, structured conversations keep employees aligned on progress, surface new learning needs early, and show continuous investment in their development.

• Make promotion criteria transparent and data-driven. Use measurable performance indicators, skill proficiency data, and project impact metrics to ensure fairness, reduce bias, and build trust in advancement decisions.

• Pair rising talent with mentors or AI champions to build leadership readiness. Mentorship programs accelerate both technical mastery and soft-skill development, helping emerging leaders translate expertise into influence and cross-team impact.

3. Strong company mission and values

It’s little surprise that 31% of AI professionals value a strong company mission. Alignment between purpose and innovation is the key to leading in a rapidly changing field, and AI talent wants to feel like their work is making a difference.

As AI policies and governance begin to take more shape, the most attractive businesses for top talent will be those that prioritize ethics and compliance.

The solution: Culture-building and communication

Gain the competitive edge by talking not just about how you’re using AI, but why. Being an AI-forward organization means creating an environment where every decision is driven by purpose. That’s true for your overall company mission and your approach to AI.

• Clearly communicate ethical AI policies. Embed these policies into onboarding, training, and everyday workflows so employees understand not only what responsible AI looks like, but why it reflects the company’s values.

• Adopt governance and compliance as a strategic advantage. Position AI governance as a differentiator, showing that the company leads with accountability, builds trust with clients and regulators, and fosters a culture where ethical innovation is the norm.

• Tie projects to visible impact, to show how AI work shapes company direction. Regularly share success stories, the ROI of AI, and outcomes from AI initiatives to connect technical efforts with business growth, customer value, and the company’s broader mission.

• Share the human impact of AI in your organization. For example, encourage teams to share how automating rote work removes tasks they didn’t enjoy from their to-do list or lessens stress. This can be just as impactful and motivating as an ROI report, if not more.

Putting it all together

While fair and attractive compensation packages are a must-have for attracting top AI talent in a competitive market, you need much more to retain talent. Innovative professionals aren’t interested in pay and perks alone.

As more organizations move beyond AI pilots and into maturity, it’s time to put less pressure on hiring and more attention on building resilient, motivated teams. Hiring is how innovation gets its start, but retention is the only way to build momentum.