What Top AI and Data Leaders Really Want

What motivates the people leading AI and data initiatives? What frustrations keep them up at night, and what do they aspire to achieve? To answer this, Lucent Search conducted a survey of over 90 AI and data leaders (CAIOs, CDOs, heads of AI, etc.) across industries. The findings offer a candid glimpse into the minds of these leaders. For CEOs and boards, understanding what your AI/Data executives want can help you empower them to deliver greater value – and avoid losing them to competitors. Here are the key motivators, frustrations, and aspirations that emerged:

They Want to Make an Impact (and Have the Support to Do So): Above all, AI and data leaders are driven by the desire to solve big problems and drive business value through data-driven innovation. They are passionate about leveraging data and AI to improve products, streamline operations, and inform strategy. In our survey, many leaders cited emerging technologies like generative AI and “AI agents” as game-changers they’re eager to implement. This signals an aspirational mindset – these leaders want to be at the cutting edge, applying the latest AI advancements to create competitive advantage. However, to turn these ambitions into reality, they crave organizational support: clear sponsorship from the top, sufficient budget, and a seat at the decision-making table. One frustration often voiced is when AI initiatives are treated as low-priority R&D experiments rather than strategic programs. These leaders want executives and boards to believe in the vision and invest accordingly. When asked about critical needs, respondents highlighted executive buy-in and cross-department collaboration as essential. In short, your AI leader wants to transform the business – and they want the mandate and resources to do it.

Biggest Frustration: Talent – Hiring and Keeping the Right People: When we asked about the most challenging aspects of their role, the talent issue loomed largest. Over half of AI/data leaders surveyed said “securing top talent” is very challenging in their organization, making it the #1 pain point. Nearly as many (around 45%) said retaining that talent is equally difficult. This aligns with what we hear anecdotally: AI and data teams are understaffed or constantly battling turnover in a hot job market. These leaders are frustrated by how hard it is to find people with the right mix of technical skills and business acumen – especially given the competition with tech giants for AI experts. Retention is tough because skilled data scientists and ML engineers have no shortage of suitors. What do they want? Help in attracting and keeping talent. They seek support from HR and leadership to build an attractive employer brand for AI professionals (more on that in Article 6) and to offer compelling career paths. They also want realistic expectations – a recognition that building a high-performing AI team takes time. When boards ask “why haven’t we delivered X project yet?”, often the honest answer is “we’ve been trying to hire the people we need.” Alleviating talent bottlenecks (through competitive compensation, contractor support, upskilling programs, etc.) would address one of their top frustrations.

Organizational Barriers: Silos and Buy-In Issues: The survey also revealed that many AI leaders struggle with organizational barriers. Nearly 50% labeled “cross-departmental collaboration” as very challenging. This indicates frustration with siloed structures – for example, the AI team might have difficulty getting data or cooperation from another department, or business units might resist integrating AI solutions developed elsewhere. Similarly, a significant number cited “integration challenges” and “scaling AI solutions” as very hard. This suggests that pilot projects often get stuck and don’t roll out enterprise-wide due to integration complexities or lack of process change. Another pain point: measuring ROI. Over 40% find it very challenging to quantify the return on AI initiatives, which can make it harder to justify further investment and get buy-in. And while “getting organizational buy-in for AI projects” was not the top issue overall, roughly one in four still find it very challenging (and more likely find it moderately challenging). So, many AI leaders feel they are pushing against inertia or skepticism. They want other executives and managers to understand the value of what they’re doing and to actively partner in AI efforts, rather than leaving the “AI team” to work in a vacuum.

Aspirations: Influence, Growth, and a Seat at the Table: When we look at career plans, an eye-opening statistic emerged: over 60% of the AI/data leaders surveyed plan to change jobs within the next year. This is an extraordinarily high mobility rate, far above many other functions. Why? Partly because their skills are in high demand – they have many opportunities. But it also signals some dissatisfaction or unfulfilled ambition in their current roles. Many of these leaders are likely seeking greater responsibility, a bigger platform, or a company that more fully embraces data-driven strategy. For example, someone titled “Head of AI” at a traditional company might jump to a tech company that will give them a VP or C-level title and more scope. Or a CDO might move from one firm to another if they feel they can make a bigger impact there. What do they really want in their careers? Common themes include:

• A Strategic Voice: They don’t want to be confined to back-office analytics; they aspire to be part of setting business strategy. Indeed, some data leaders aim to become CEO or general managers eventually. At minimum, they want their insights to influence key decisions. Being invited to board meetings or executive strategy offsites is validating.

• Continuous Learning and Innovation: This group thrives on innovation. Many respondents mentioned excitement about emerging tech (e.g., “quantum computing,” “agentic AI frameworks”). They want to be in environments where they can experiment with new techniques and keep learning. If their current company is too conservative or slow-moving, they may feel stifled. They seek a culture that encourages creativity and stays on the cutting edge.

• Clear Impact and Recognition: AI and data work can sometimes feel abstract. These leaders are highly motivated by seeing tangible impact of their work – whether that’s revenue growth, cost savings, or a product improvement. They also appreciate recognition for those wins (as anyone would). If their team’s achievements are celebrated internally and externally, it fuels their sense of purpose. Conversely, if they toil on an AI model that never gets deployed, it’s demoralizing.

• Resources and Autonomy: They aspire to lead larger programs with appropriate budgets. Many likely want the challenge of building a team and an AI capability essentially from the ground up (that’s why so many are open to new positions – the opportunity to build is attractive). Along with that, they desire a degree of autonomy to execute their vision without constant second-guessing. This doesn’t mean they want to go rogue, but rather that they want executives to trust their expertise.

  
  

What Can CEOs/Boards Do? Based on these insights, here are a few actions to ensure your AI and data leaders are empowered and engaged:

• Make Them Part of the Strategic Conversation: Involve your AI/data leader in high-level discussions about company direction, not just in execution plans. If you’re exploring a new market or product line, ask how data and AI could play a role. When they feel their perspective is valued on core business issues, their job satisfaction increases and so does their effectiveness. One respondent in a leadership role mentioned that AI will increasingly require “knowing how best to apply” solutions, not just implement – implying they want to advise on strategy, not just be handed requirements.

• Support Talent Acquisition and Development: Address their number one frustration by prioritizing hiring and retention of their team. This might mean improving offers for key hires, engaging specialized recruiters (possibly partnering with firms like Lucent Search), or providing budget for contractors or outsourcing to fill gaps. Also, invest in developing internal talent – for example, allow them to upskill some keen internal employees into data/AI roles to alleviate talent shortages. Show your AI leader that you have their back in building the A-team.

• Break the Silos: Encourage and even mandate cross-functional collaboration on AI projects. If your AI leader is trying to implement an AI solution in, say, marketing, make it clear to the CMO and marketing team that this is a priority and they need to actively participate. Some organizations establish multi-department AI task forces for key initiatives, co-led by the AI leader and a business leader. This sends a message that AI is a team sport. Also, help clear roadblocks – if data access is an issue, align on data-sharing agreements between departments.

• Define Success and Recognize It: Work with the AI/data leader to set clear metrics for success (ROI, adoption rates, etc.), but ensure they’re realistic. Given the challenge of measuring ROI, maybe consider proxy metrics like number of processes improved by AI, or user satisfaction improvements, to capture impact. When goals are met, highlight these wins in company-wide forums. This not only motivates the leader and their team but also educates the rest of the organization on the value being delivered.

• Provide Growth Opportunities: If you want to retain these highly marketable leaders, think about their growth within your company. Could you expand their remit after early successes (e.g., give the CDO oversight of another strategic area, or elevate a “Head of AI” to a VP level)? Discuss career paths: some may desire P&L responsibility eventually or a pathway to general management. It might seem counterintuitive, but grooming your technical leaders for broader roles can keep them engaged (and you benefit from their analytical mindset in other areas of the business). Moreover, offering things like participation in leadership development programs or sending them to represent the company at major conferences can satisfy that desire for learning and recognition.

• Cultivate an AI-First Culture: Many AI/data leaders aspire to build an “AI-first culture” in their organizations – one where data-driven decision-making is the norm and AI is woven into the fabric of operations. They can’t do this alone. Executives must champion data-driven thinking and demand that decisions be backed by analytics. Celebrate managers who successfully use data/AI in their projects. Encourage experimentation (and be tolerant of the fact that not every experiment will pan out). If the culture becomes more receptive to AI, your AI leader’s job transforms from uphill advocacy to momentum-guided execution. That’s exactly what they want – to spend less time convincing, and more time creating value.

  
  

In the words of one of our survey respondents: “I want to move from fighting for attention on AI, to focusing on delivering results with AI.” Summing up, top AI and data leaders are passionate change agents who want to drive impact, but they need the right environment. They’re frustrated by talent shortages and silos, and they’ll gravitate to places where they can fulfill their vision. By understanding and addressing what they really want – meaningful impact, support, growth, and recognition – organizations can not only get more value from these roles but also keep these valuable leaders happily on board, steering your company through the data-driven future.

If you're serious about supporting and retaining top AI and data leaders, we’ve compiled the complete findings into a practical guide—full of actionable insights and recommendations based on our survey of 90+ industry experts.

👉 Interested in receiving the guide or discussing how these insights apply to your team?

Contact Rebecca Hastings directly at rebecca@lucent-search.com or connect with her on LinkedIn to learn more.

Let’s make sure your AI leaders have what they really need to drive lasting impact.