Corporate investments in AI are soaring, and with it, a heightened demand for a return on investment (ROI) in AI is growing throughout boardrooms worldwide. It’s anticipated that investments in genAI will increase 60% by 2027 (BCG).

Despite their eagerness to sink millions of dollars into the next best enterprise AI tool, for many businesses, any real return on value remains out of reach. Just 25% of C-suite executives say they’ve seen significant value from AI, according to Boston Consulting Group, while less than half of businesses say they’re yet to see any positive ROI.

This doesn’t stem from the shortcomings of any one AI tool. The issue is that too many businesses are viewing corporate AI strategies through the narrow lens of tech investment, and the capabilities of the tech that’s been invested in. Meanwhile, the other core driver of ROI goes forgotten: their people.

People power

Investing in AI without investing in your people first is like trying to build a skyscraper without laying a solid foundation. The building might look shiny and impressive at first but, if it is built on shaky ground, it will soon crumple.

It’s time for company culture to be brought to the forefront of discussions around AI in the workplace. AI must be embedded into company operations, and enabling people—equipping staff with the skills, knowledge and support they need to use AI—must become a strategic priority. Otherwise, AI uptake among employees will remain low, results will be limited, and ROI will remain a distant and unattainable goal.

Change starts from the top down, so boards have a critical role to play in achieving this. They must become champions of an AI-first company culture. And as part of the process, I want to see boards make AI training and adoption metrics a core part of their oversight.

This will equip them with the insight needed to push for targeted AI upskilling initiatives, identify areas where AI is best serving employees and divert investment accordingly, ensuring that senior leaders take on a leading role in building AI usership into the company culture.

ROI and adoption of AI go hand in hand. It might sound obvious, but unless employees are actually using AI on a regular basis, the AI tools will never fully prove their worth—and cost savings, revenue increases, and increased customer satisfaction will remain out of reach.

Measure for measure

One of the most crucial metrics boards need sight of is the rate of AI adoption and usage across the business. Boards must push for regular, organisation-wide reporting on AI adoption metrics, and this must span beyond surface-level insight into which employees and departments have access to tools.

The most useful adoption metrics will provide insight on who is using AI on a role, department, and seniority basis, and how regularly it’s used. But they will also shine a light on how effectively AI is being used—whether it’s being incorporated into the decision-making process, and whether it’s improving results or reducing the time taken. Tracking AI usage through workplace analytics tools is a quick and simple way to gain oversight on the rate of adoption and usage.

But employees can’t just be expected to use AI—they must feel able and empowered to do so. That means ensuring all employees, across all departments, receive foundational AI training.

Boards must push for clear metrics on AI training, including who has been trained, how recently, and to what depth. They should also track employee confidence, attitudes toward AI, and how effectively it is being used across the organisation.

Combining this data with adoption metrics will give boards a clear view of whether upskilling and training initiatives are increasing the rate of AI adoption throughout the business. And understanding how employees feel about AI—whether they’re confident using it, and whether they think it is improving their work or not—will also help boards to identify where extra support or training is needed.

Lead by example

This focus on confidence and capability must also extend to management and senior leadership. Company-wide AI rollout will be most successful if managers and executives can lead by example, confidently and actively building AI into their own workflows. But to achieve this, boards should push for C-suite executives and leaders to receive the same level of training as their teams.

Boards can’t afford to treat AI as just another tech spend. Boards must push for AI to be embedded into the foundations of the business, but that can only happen with proper training, support and visible leadership.

A successful, value-driving AI strategy will involve clear oversight of who is using AI, how often, and how confidently. Without these metrics, businesses risk letting their expensive tools gather dust. AI success can’t be built on shaky ground. Boards must first lay the foundation of an AI-literate workforce—or risk seeing their investment collapse around them.

Raoul-Gabriel Urma is an edtech entrepreneur, author and founder of education technology company Cambridge Spark.