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Lucent Search research | AI & Data Leadership Report 2025–2026
AI ownership, accountability and executive sponsorship
How clearly does your organisation assign responsibility for turning AI investment into business results?
AI delivery often requires several functions to make decisions together. Technology and data teams may develop a solution, while operations changes the workflow, finance assesses the value and risk teams establish the conditions for use.
Each function brings legitimate priorities. Progress depends on how those priorities are reconciled, who has authority to make decisions and who remains accountable for the business outcome.
Lucent’s research identifies cross-departmental collaboration and organisational buy-in as significant challenges for AI and data leaders. For executive teams, the findings raise a practical question: does responsibility for delivery match the way decisions are actually made?
RESEARCH FINDINGS
What the research found
87% found cross-departmental collaboration challenging
Just over half of respondents, 51.1%, rated cross-departmental collaboration as very challenging. A further 35.9% found it moderately challenging.
This makes collaboration a substantial concern within the surveyed group. It warrants attention to the working relationships between functions, alongside the capability of the AI or data team itself.
71% found organisational buy-in challenging
23.7% rated securing organisational buy-in for AI projects as very challenging, while 47.3% found it moderately challenging.
The survey asked about organisational buy-in broadly. This can involve support from several stakeholders and should not be interpreted solely as a measure of CEO or board sponsorship.
Taken together, the findings suggest that leaders can face two connected tasks: securing agreement that a project matters and obtaining the cooperation required to deliver it.
BUSINESS IMPLICATIONS
What this means for the business
An AI initiative can have a named leader while leaving important decisions unresolved.
Who decides which business problem takes priority? Who commits operational time? Who can approve access to data? Who accepts responsibility for changing a process? Who decides whether the result is ready to use?
When these responsibilities are unclear, delivery relies on repeated negotiation. The appointed leader may spend considerable time securing cooperation without having the authority to resolve competing demands.
For the business, this can make timelines less dependable, obscure the true cost of delivery and weaken accountability for results. It can also make the leadership requirement harder to assess: an apparent capability gap may partly reflect the conditions in which the leader is working.
DEFINING OWNERSHIP
Rebecca’s perspective: make ownership specific
Executive sponsorship becomes useful when it changes what happens at a difficult decision.
A sponsor needs to be able to resolve competing priorities, secure commitments from other functions and establish which outcomes matter most. Their involvement should provide a clear route through decisions that the AI or data leader cannot settle alone.
Ownership also needs to be specific. Responsibility for technical delivery, business adoption, investment and risk may sit with different people. Those responsibilities need to connect.
Before defining or replacing a leadership role, I would examine four areas.
The business outcome
Identify the result the organisation expects and the executive accountable for achieving it. For example, an AI team may be responsible for developing a forecasting capability, while an operational leader owns how it is used to improve planning. Both contributions need to be explicit.
The authority of the AI or data leader
Define the decisions the leader can make, the resources they control and the commitments they need from others. Where accountability extends beyond their authority, establish how the gap will be addressed.
Commitments across functions
Specify what each participating function must contribute: people, data, process knowledge, assurance, implementation capacity or changes to working practices. These commitments need to be reflected in priorities and capacity planning.
Escalation and executive sponsorship
Agree who resolves disagreements, which decisions require escalation and how quickly they need to be made. A governance meeting is useful when it enables decisions and follows through on commitments. Its purpose and authority should be clear to everyone involved.
LEADERSHIP QUESTIONS
Questions for your leadership team
Use these questions to examine a current initiative or a proposed leadership appointment.
Who owns the business result?
Can the organisation name the executive accountable for the outcome beyond technical delivery?
Does the leader have sufficient authority?
Which commitments depend on people or budgets outside their control?
Have other functions committed capacity?
Is their contribution reflected in plans and priorities?
Who owns adoption and operational use?
Has responsibility been assigned for changing the workflow and sustaining the capability?
Who owns adoption and operational use?
Has responsibility been assigned for changing the workflow and sustaining the capability?
What happens when priorities conflict?
Is there a clear decision-maker and escalation route?
HIRING IMPLICATIONS
What this means for a leadership appointment
The answers should shape the role before the search begins.
They may confirm the need for a senior AI or data leader with stronger experience in enterprise delivery. They may point to a broader remit, different reporting relationships or clearer commitments from the existing executive team.
They may also show that the organisation needs to resolve ownership before it can specify the appointment
properly.
Lucent’s Leadership Requirement Diagnostic examines the business outcomes, existing capability, role scope, decision rights and conditions for success. It establishes what the leader must deliver and what the organisation must put in place to support that delivery.
EXPLORE RESEARCH
Explore related findings
Structuring AI and data teams for delivery
How team design and capability connect to the wider organisation.
Scaling AI from pilot to production
The integration and delivery challenges involved in moving AI into operational use.
AI investment and return on investment
Funding constraints and the difficulty of demonstrating business value.
ABOUT
About this research
This page draws on the organisational challenges section of Lucent Search’s AI & Data Leadership Survey Results 2025–2026, including questions about cross-departmental collaboration and organisational buy-in.
The findings reflect the participating leaders’ experiences at the time of the survey. They should be read alongside the respondent profile, question wording and methodology.
Research and interpretation by Rebecca Hastings, Founder of Lucent Search.
CONNECT
Deciding where AI or data responsibility should sit?
If you are reviewing an existing role or considering a senior appointment, the starting point is a clear view of what needs to change and who needs the authority to change it.
Speak to Rebecca about the outcomes you need, the capability already in place and the decisions holding progress back.
Lucent Search · AI & Data Leadership Report 2025–2026