Right now, most organizations face a crucial moment in their AI development. The technology is maturing, and systems are in place. The key decisions now are strategic ones: how to balance people, processes and technology in a way that will deliver future success.
Every company is tackling these decisions in different ways. Helios HR's extensive survey of AI adoption reveals that AI ownership is often split between teams, with the C-suite and IT generally leading the initiative.
Our research has also revealed that HR plays an enormous role in AI adoption. When HR is involved in AI strategy, there's a better chance of employee adoption, often thanks to depth in change management, communications, learning and development, and workforce planning.
Unfortunately, fewer than 1 in 5 companies include HR in their transformation process. Without HR leaders involved at the strategic level, those companies face AI challenges.
The gap between AI adoption and HR involvement
In Helios HR's 2026 Mid-Market AI Workforce Trend Report , we asked organizations to name the teams involved in leading AI initiatives. Respondents could select up to three answers, and they said:
- C-suite executives: 31%
- Technical teams: 30%
- HR teams: 17%
- No clear ownership: 13%
This means that HR is not involved at a strategic level in 83% of organizations. The cost of that gap shows up in outcomes. Of those companies reporting success with their AI strategies, 72% said that HR was involved in strategy. Among those who are still just beginning their AI journey, only 31% had HR at the table. The pattern is consistent across the mid-market: HR involvement and AI success move together.
AI adoption involves several challenges that are classic HR issues: change management, workforce preparation, governance design, and measurement of human outcomes. When HR leaders take part in strategy meetings, they can help the team navigate those challenges and see real benefits from AI.
5 ways HR leaders can drive AI strategy
While the numbers tell a clear story, the question remains: what can HR leaders actually contribute to AI strategy sessions? Here are five steps that every HR leader should be acting on right now.
1. Know where your organization actually stands
Before HR can shape AI strategy, it needs a clear picture of the current state of play. Employee use of AI might differ significantly from officially recognized activities, with an estimated 80% of employees already using unauthorized AI software for work tasks.
A useful assessment covers which tools are in use across departments (including informal and self-directed use), whether governance exists and whether employees know about it, which functions carry the most risk, and what training, if any, has already taken place. If AI usage is already widespread, then the team may have a stronger skills base than you thought.
2. Link talent strategy to business outcomes
Digital transformation will have a significant impact on the team's makeup. This will immediately prompt consideration of upskilling programs and development opportunities for existing staff. Providing such support will also help make the team feel more excited about AI opportunities.
In the long term, it's important to consider how AI will affect your future talent needs. Automation might reduce entry-level opportunities, which could affect the talent pipeline. It could also change the type of employee you need to hire: not just AI-literate, but also with irreplaceable human skills such as creativity, empathy, and teamwork.
3. Build governance that enables, not just restricts
One of the most tangible contributions HR can make is helping develop an AI governance framework that employees will actually use. Most mid-market organizations have no policy in place. Helios HR's research found that only 12% of organizations have a finalized AI policy, yet those with a formal governance framework are more than four times as confident in their ability to manage AI risk (71% vs. 16% without one).
Good governance is fundamentally about people's behavior, not just technical controls. That makes it HR's work as much as IT's. A useful framework addresses which tools are approved, what data should never be entered into AI systems, who is accountable for AI-assisted decisions, and how errors or bias will be identified and corrected. Hiring and performance decisions deserve particular attention, where regulatory exposure is growing quickly, and the consequences of getting it wrong are significant.
4. Lead the workforce preparation effort
Even in organizations where AI adoption is accelerating, formal workforce preparation is lagging. Our report found that only 5% of organizations offer structured AI training programs, with the vast majority relying on self-directed learning. Only 16% have updated job descriptions to reflect AI responsibilities, and 42% have no plans to do so.
Training design, job architecture, performance expectations, and change communication are functions HR already owns. The task is applying them deliberately to AI readiness. Prioritize manager enablement first; managers who understand and model responsible AI use accelerate adoption far more effectively than top-down mandates. Design learning pathways that are role-specific, not generic, and allow each team to build productive AI processes.
5. Define what success looks like (and measure it)
Most organizations say they want AI to drive efficiency, but without defined metrics, that's neither measurable nor inspectable. HR can contribute something neither IT nor finance typically provides: a data framework that captures both operational outcomes and workforce health.
Success looks like workforce confidence, engagement, retention, and the quality of decisions made by people working alongside AI tools. Set baselines before rolling out new tools. Track AI adoption rates by department to identify where support is needed, not just where adoption is high. Connect AI outcomes to business KPIs that C-suite leaders already care about: time-to-hire, client satisfaction, retention, and error rates.
Ready to take a more strategic role in AI?
AI strategy is a workforce question as much as a technology question. The organizations getting the most from AI are those where HR is actively involved in planning, governance, and workforce preparation. Those that aren't are running AI as an IT initiative while everyone else plays catch-up.
HR leaders who move now, even if the organization is still in the early stages, will shape strategy rather than react to it. That difference in positioning produces measurably better outcomes, and it starts with an honest assessment of where things stand today.
Helios HR can help you build the strategy, governance, and workforce preparation needed to make AI work for your organization:
- AI consulting to assess your organization's AI maturity and build a practical roadmap
- Strategic HR consulting to connect AI planning with your broader people strategy
- Training and development to build AI fluency across your workforce with role-specific learning programs
- HR Information Systems consulting for guidance on selecting, implementing, and governing AI-enabled HR tools
- Employee engagement services to track workforce sentiment and readiness through periods of change
