7 Strategies HR Leaders Use to Close the AI Adoption Gap

The AI adoption gap refers to the disconnect between deploying AI tools in the workplace and achieving meaningful, sustained usage across an organization. Deploying an AI tool does not guarantee employees will use it — and it especially does not guarantee they will use it well. At Valence's 2025 virtual summit, AI & the Workforce: The Adoption Gap, HR leaders from global enterprises shared the specific strategies they used to move from hesitant pilots to widespread, high-value AI adoption.

The following seven strategies are drawn directly from their experience — as told by the HR leaders who implemented them.

1. Find Internal Champions Before You Launch

Getting buy-in from executives, senior leaders, and cross-functional partners lends credibility to AI tools before the broader workforce encounters them. Internal champions increase visibility, reduce skepticism, and signal that leadership sees the tool as a strategic asset — not another mandate.

"After we had done our pilot, I gave Nadia to our exec team and our CEO, and said, try it out and see what you think. It gave it a lot of credibility when we did introduce it because we had our CEO introduce it as a strategic asset for people rather than something mandated, and I think that overcame a lot of that potential skepticism." — Maree Prendergast, Global Chief People Officer, VML

"Find your team, find your partners because they matter. When we implemented Nadia to coach managers based on feedback from our employee engagement surveys, that was a direct partnership with my peer in that space. We worked together, and we said: Here are the survey results. What would we want a coach to talk about? And then how can Valence partner with us to customize that?" — Colleen Sugrue, Head of Global Learning and Organizational Capability, AGCO

2. Frame AI Tools as an Invitation, Not a Requirement

Employees respond differently to an invitation than to a mandate. When the framing shifts from "you are required to use this" to "you are invited to try this," employees approach AI tools as an opportunity rather than an obligation. This distinction consistently produces higher engagement in early rollouts.

"Start with an invitation instead of an expectation that someone will be required to use a tool that's new and different for them. We found that when we invited people to participate, we had much greater engagement." — Jennifer Carpenter, Vice President, Global Head of Talent, Analog Devices

3. Embed AI Tools Into Existing Workflows

At any given moment, employees are toggling between multiple programs to find information and complete tasks. An AI tool that lives outside those existing workflows is easy to forget. Embedding AI directly into the tools employees already use — rather than asking them to navigate to a separate platform — removes the friction that kills adoption.

"We have a bespoke tool that sits within Microsoft Teams, and we embedded Nadia into that app within Teams. So it's right in the middle of the workflow. We didn't say, 'Here's a link that you can go and check out and get some coaching.'" — Maree Prendergast, VML

"We have a tool called QuickView, which brings employee and operational data together. We were able to create an icon for Nadia in that tool so all of our first level managers have access to it in the same tool that they use to determine if there is a flight interruption. It's a place where we get a lot of important traffic, so we position Nadia right there." — Tim Gregory, Managing Director of HR Innovation & Workforce Technology, Delta Air Lines

4. Deploy AI at Key Moments in the Talent Cycle

HR communicates some of the most sensitive and complex information in any organization — policy changes, performance expectations, return-to-office mandates, personnel transitions. AI coaching can reinforce these messages with nuance and consistency that a single email or all-hands cannot achieve. Embedding AI support at high-stakes moments in the talent cycle creates a direct path for employees to get guidance when they need it most.

"We had a mandated RTO of four days a week, and we had three months to get people back and comfortable. We loaded Nadia with all of our RTO policies and FAQs. She was able to coach that and frame it in the way that we messaged it, which was RTO with significant flexibility. Nadia really helped give the perspective that, if you need flexibility, it's there. This is how you get it in a constructive way. This is how you help people understand your particular circumstances. It really helped people with sensitive transitions, which we hadn't anticipated originally." — Maree Prendergast, VML

"We have a monthly drumbeat of workshops that are timely and relevant to what employees and managers need to be doing. That might be performance discussions that are already happening. We say, 'By the way, come to our workshop. We can show you how AI coaching can support you through that.'" — Jennifer Carpenter, Analog Devices

Watch: How Analog Devices uses AI coaching at key talent moments →

5. Use Senior Leader Success Stories to Reduce Hesitation

Employees are often unsure where to start with AI tools. Success stories — especially from senior leaders who share what they tried and what they got out of it — reduce hesitation and provide concrete use cases. Creating a regular channel for sharing these stories empowers both the person sharing and the people listening to engage more confidently.

"Our senior leaders are using Nadia, and they're sharing what they've got out of it, and they're sharing how they're using it with their direct reports. It's giving others permission to try. We're also lifting up the real voices of our employees, real examples, and not shying away from the parts that may need adjusting as we move forward." — Lisette Danesi, Global Corporate People Lead, WPP

"There were about 50 of us in that trial that we did. We gave them some prompts: Here are some conversation starters to test with Nadia and see how this goes. Then we would meet monthly and check in. We said, 'How is it going? What are you learning? What are you hearing?'" — Colleen Sugrue, AGCO

6. Track Adoption Metrics to Identify Where AI Is Driving Value

Every interaction an employee has with an AI coach produces data. Tracking adoption metrics and usage patterns gives HR leaders a leading indicator of where AI is creating value — and where to focus learning and development curriculum. According to Valence data from enterprise deployments, this anonymized usage data also reveals workforce-wide patterns that were previously invisible to HR leaders.

"Because of the way Nadia works, we now have anonymized data on what our people are actively working to improve. And what comes through loud and clear? It's not the technical skills. It's setting clear and measurable goals, communicating with clarity, and active listening. These are foundational human skills, but they're also critical leadership skills in an AI-enabled workplace. We're using this insight to fine tune our R&D focus and support leaders where it counts." — Lisette Danesi, WPP

"In the last six months, I've just seen adoption do a little bit of a hockey stick. We're tracking sentiment within ADI, and in the last six months, we've seen a 10% increase in positivity and agency — that personal belief in one's ability to navigate the tools." — Jennifer Carpenter, Analog Devices

7. Build for Inclusivity to Drive Trust Across the Workforce

A workforce is diverse — and AI programs need to reflect that. Inclusive design builds trust, which drives authentic engagement. It also addresses a specific risk: early data suggests that certain groups, including women, are less likely to adopt AI tools, creating potential new divides if adoption programs do not actively address them.

"There's a kind of fairness and consistency in the approach that the tool can be used for, which I think really helps to drive trust in the technology, rather than a human who is naturally going to have some biases and inconsistencies in the way that they operate. We've got the message across to people that this is actually a way of reducing bias. People were worried AI was going to create some bias, and actually we've demonstrated to people that this is a way of reducing that level of bias." — Jonathan Crookall, Chief People Officer, Costa Coffee

"One of our future work experts highlighted a growing gender gap of AI adoption in a recent conference. In early data, women already are less likely to be using AI tools, and that's concerning, often because they see it as cheating or they feel unsure how to engage with it. So we're really now focusing our work in our employee communities to address that: building confidence, breaking down myths, and ensuring we don't allow another digital divide to emerge." — Lisette Danesi, WPP

What These 7 Strategies Have in Common

AI is not only changing how people work — it is changing how they work together. But that change only becomes visible when AI is adopted at scale. In a matter of months, the HR leaders at these organizations went from running cautious experiments to discovering and scaling new use cases across their workforces. The strategies above — champions, invitations, workflow integration, talent cycle timing, success stories, metrics, and inclusivity — are the common thread across all of them.

Frequently Asked Questions

What is the AI adoption gap in the workplace?

The AI adoption gap is the disconnect between deploying AI tools in an organization and achieving meaningful, sustained usage across the workforce. Companies frequently deploy AI tools that employees either don't use consistently or don't use effectively. Closing the gap requires intentional strategies around culture, workflow integration, and leadership modeling — not just access to the technology.

What is the most effective strategy for increasing AI tool adoption among employees?

Based on the experiences of HR leaders at VML, Analog Devices, WPP, Delta Air Lines, AGCO, and Costa Coffee, the most consistently effective strategy is embedding AI tools directly into existing workflows rather than asking employees to navigate to a separate platform. Pairing this with internal champions who model usage — especially at the senior leader level — drives the credibility and visibility needed for broader adoption.

How do you get senior leaders to support AI adoption?

Include senior leaders and executives in early pilots before the broader workforce rollout. When leaders experience the value themselves, they are more likely to introduce the tool as a strategic asset rather than a requirement. At VML, having the CEO introduce Nadia as a strategic tool — rather than a mandate — was identified as a key factor in overcoming employee skepticism.

How can HR leaders use AI adoption data to improve learning and development?

AI coaching platforms generate anonymized data on what employees are actively working to improve. At WPP, this data revealed that employees were primarily focused on foundational human skills — goal-setting, clear communication, and active listening — not technical skills. HR leaders used this insight to refocus their L&D curriculum on where the actual development need was, rather than where they assumed it was.

How do you address the gender gap in AI adoption?

Early data from enterprise deployments shows that women are less likely to adopt AI tools, often because they perceive it as cheating or feel uncertain about how to engage. HR leaders at WPP have responded by building employee community programs specifically focused on building confidence, addressing myths, and ensuring AI adoption programs reach all parts of the workforce — not just those who self-select into early adoption.