AI investment is accelerating, but many organisations still haven't agreed on who is responsible for making sure their people can use it effectively.
Kaplan's ‘From AI to ROI: Who owns the problem?’ report found a significant difference in how C-suite and HR and L&D leaders view responsibility for AI capability.
Almost half of C-suite leaders (44%) say IT or technology teams are primarily responsible, compared with 23% of HR and L&D leaders. Meanwhile, 26% of HR and L&D leaders identify HR as the primary owner, while 18% point to Learning & Development. Among C-suite leaders, those figures fall to just 11% and 6% respectively.
It's a finding that raises an important question: if different parts of the organisation have different views of who owns AI capability, who is ultimately responsible for making sure the workforce is ready?
Why AI ownership is becoming more complicated
AI is no longer something that sits solely within the technology function. As organisations adopt AI across different areas of the business, its impact and implementation increasingly involve multiple parts of the organisation.
Different decisions sit across different parts of the organisation. Someone needs to determine which tools are appropriate, someone needs to consider how AI will change the workforce, and someone needs to make sure employees have the skills to use it effectively. Senior leaders also need to understand how these decisions support the wider business strategy.
The difficulty is that when these responsibilities are spread across multiple teams, it can become unclear who is ultimately accountable for making sure the organisation has the capability to use AI effectively. That’s not necessarily a problem if responsibility is genuinely shared. The bigger issue is whether the business agrees on who is accountable.
This creates an ownership gap. AI may be introduced, discussed and invested in across the business, while no one has clear accountability for making sure employees are equipped to use it successfully.
AI ambition isn't always matched by capability priorities
The ownership challenge becomes more significant when there is also a difference in how urgently teams see AI.
Kaplan's research found that 74% of C-suite leaders rate AI as a high or top organisational priority. Among HR and L&D leaders, only 39% say the same.
This creates a potential disconnect between strategic ambition and workforce development. Senior leaders may already be thinking about how quickly the organisation can adopt AI, where it can create competitive advantage and what investment is required, while developing the skills needed to support that ambition can feel like a longer-term priority.
For HR and L&D, this gap also highlights the importance of building their own understanding of AI and its implications for the workforce. As AI becomes a more significant organisational priority, being able to engage confidently in those conversations can help ensure workforce capability remains part of strategic decision-making.
The result is a risk that technology adoption moves faster than workforce capability.
Employees may be given access to new tools before organisations have fully considered how those tools should be used within different roles. Learning may then become reactive, with teams trying to close capability gaps after adoption has already begun rather than preparing people in advance.
For organisations serious about AI, capability therefore needs to be considered as part of the adoption strategy, not as a separate activity that follows it.
The teams closest to capability need the ability to act
There is another issue behind the ownership gap: accountability only works when the people responsible have the resources to deliver it.
The research found that 94% of HR and L&D leaders say they understand the workforce capability needed to deliver their organisation's AI strategy.
That suggests the challenge isn't necessarily a lack of understanding about what employees need. Instead, the barrier can be turning that understanding into action.
More than a third of HR and L&D leaders (36%) say they lack either the authority or budget to act fully on their responsibility, while 27% specifically identify insufficient budget as a limiting factor.
Organisations need to be able to invest in appropriate learning, give employees time to develop and practise new skills, align development with changing roles, and adapt their approach as AI continues to evolve.
If the function responsible for workforce capability cannot influence those decisions, responsibility becomes difficult to translate into results.
What should different functions actually own?
Clear ownership doesn't mean putting everything related to AI into one department. Instead, organisations need to establish clear areas of responsibility and make sure different functions work together.
Depending on the organisation, IT, HR, L&D and leadership may each have a role to play in areas such as technology, workforce planning, capability development and strategic direction.
The important thing is that these responsibilities are connected, with clear accountability for identifying capability gaps and ensuring they are addressed.
Capability needs to evolve alongside AI
AI capability isn't something organisations can build once and then consider complete. As tools develop and become embedded in more areas of work, the skills employees need will change too.
An employee might initially need to understand how AI can support their everyday tasks. As adoption develops, they may need to become more confident evaluating outputs, applying AI to more complex problems, understanding governance requirements or identifying new opportunities for automation and productivity.
This means organisations need an approach to capability that can evolve alongside their technology strategy.
Learning should be practical and relevant to the work employees actually do, rather than treating AI as a generic skill that can be addressed through a single training intervention.
The overall goal is to create a workforce that can adapt as AI changes, rather than simply preparing employees for the tools an organisation happens to be using today.
Making accountability part of AI strategy
The findings from Kaplan's research suggest that organisations have made faster progress defining their AI ambitions than agreeing who is responsible for delivering them.
Closing that gap means making accountability clear, connecting the teams involved, and giving those responsible the authority and resources to act.
As AI becomes more embedded in the workplace, organisations that treat workforce capability as part of their AI strategy, rather than a separate consideration, will be better placed to turn investment into meaningful results.
Because AI capability may be a shared responsibility, but someone still needs to own the outcome.
Explore these findings and more in Kaplan's ‘From AI to ROI: Who owns the problem?’ report.
FAQs
Who is responsible for building AI capability?
There isn't one function that can develop AI capability in isolation. Technology teams, HR, L&D, line managers, operational managers and senior leadership all have different responsibilities, but organisations should make it clear who is accountable for coordinating these efforts and ensuring they support the wider AI strategy.
Why can AI capability fall between different functions?
AI sits across technology, people and business strategy, so responsibility can become fragmented. If IT focuses on implementing tools, HR focuses on workforce change and L&D focuses on training without a shared plan, important capability requirements can be missed or addressed too late.
What happens when organisations don't have clear ownership of AI capability?
Without clear accountability, organisations may struggle to connect AI investment with workforce development. Employees can receive access to new tools without the appropriate skills, while teams responsible for capability may lack the influence or resources needed to address gaps.
What role should senior leaders play in AI capability?
Senior leaders should set the direction for AI and make sure workforce capability is considered alongside technology investment. They also need to ensure that the people responsible for developing AI skills have the authority, budget and organisational support to deliver against those priorities.
How can organisations build AI capability effectively?
Organisations should start by identifying the capabilities needed to support their AI strategy, assessing current gaps and assigning clear responsibility for addressing them. Learning should then be practical, role-specific and continually updated as AI tools, roles and business requirements evolve. Apprenticeships and structured development programmes can provide a practical way to build these capabilities over time, combining learning with the opportunity to apply new skills in the workplace.
Methodology
The research was conducted by Censuswide, among three samples of:
- 1000 UK employees within transformation-heavy sectors and functions in companies with 50+ employees where AI deployment is active (excludes Business owners and C-Level Execs) between 10.07.2026 - 21.07.2026
- 600 UK HR and L&D decision makers (HR directors, L&D managers, People and Talent leads) with 50+ employees, whose organisation is using AI between 10.07.2026 – 22.07.2026
- 600 (Aged 25+) C-Suite and Director level; in specific sectors; whose organisations use AI; and at companies of 50+ employees between 10.07.2026 – 22.07.2026
Censuswide is a member of the Market Research Society (MRS) and the British Polling Council (BPC), and a signatory of the Global Data Quality Pledge. We adhere to the MRS Code of Conduct and ESOMAR principles