Turning AI Momentum into Workforce Advantage

Turning AI Momentum into Workforce Advantage
June 16, 2026 17 mins

Turning AI Momentum into Workforce Advantage

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Aon’s Human Capital leaders outline a clear leadership challenge: AI is scaling fast, but the value it delivers is determined by how effectively organizations prepare their people to use it.

Key Takeaways
  1. AI investment is ahead of workforce readiness, leaving unrealized value.
  2. Delivering value from AI requires shifting focus from activity to outcomes.
  3. Advantage comes from redesigning work, not just scaling tools.

Intro
Hello and welcome to another episode of On Aon. 

This week Aon’s Byron Beebe, Amanda Scott and Marinus van Driel discuss that while AI adoption is accelerating for many organizations AI readiness has not matched that pace. Drawing on findings from Aon’s Human Capital Trends Study, Byron and the team explain that, by focusing on people as well as technology, leaders can transform AI ambition into real value. 

Byron Beebe
Welcome to On Aon. I'm Byron Beebe, CEO of Aon's Human Capital Solutions business. In this miniseries, we're taking a deeper dive into the findings of our 2026 Human Capital Trends Study, exploring what's shaping the future of work and what it means for leaders navigating today's evolving workforce. 

In this first episode, we unpack one of the main findings of the study: AI implementation has gone mainstream, but AI readiness has not. I'm joined by Amanda Scott who leads Aon's North America Talent Solutions business, and Marinus van Driel, a partner in our workforce transformation business. 
Together, we'll look at how organizations can translate AI momentum into meaningful enterprise-wide value. 

Amanda, I'm gonna start with you. I'm just gonna ask you a few questions. Marinus, I'll just ask you to jump in on these as well. Maybe let me start with this. Over the past 12 to 18 months, AI has move from experimentation to everyday use in many organizations. Almost every organization I talk to is talking about this in some way, shape, form.

So, what are you seeing in the market right now and what's changed most in how companies are approaching AI today?

Amanda Scott
Thank you, Byron. This is absolutely the hottest topic in the market at the moment. So really excited to be here, grateful to be here with Marinus as well, one of our top experts in this space. So, we look forward to going through some of the questions with you. I guess just to start, what I'd say is that organizations have moved very quickly from experimenting with AI to deploying it at scale. But where organizations are struggling is they're trying to figure out what that measurable shift is in impact.

So we recently did some research and we found that three-quarters of organizations are now piloting or deploying AI. But only about 18% have had the majority of their workforce actually participate in re-skilling. 

So what's happened is that we've scaled the technology, but we've not scaled the capability. We haven't equipped the humans.

And at the same time, success is still just being measured through activity, so usage and prompts, rather than actual outcomes. 

So for me, the defining shift is really that AI is no longer a technology story, it's a people story. And right now, those two are actually moving at very different speeds. 

But, Marinus, as you are seeing this day to day, you're working with top organizations on this topic. Love to hear your perspectives as well.

Marinus van Driel
Absolutely, Amanda. I think what you shared there is absolutely spot-on. What we're hearing from leaders in just about every organization that we're talking to is that they've already deployed AI, but they're still struggling with how work actually gets done in their organizations. 

And to your point, it really is more of a people opportunity than it is a technology opportunity. There are a couple of different patterns that we've seen emerge in the discussions that we've had.

And those patterns are that the availability of AI doesn't necessarily mean adoption. And then in addition to that, all of this amazing activity that organizations are engaging in doesn't necessarily result in transformation. And from my perspective, making sense of those two patterns is that this really now is like a, it's a clarity problem around how to enable people to truly realize the promise of AI. It's not an access problem. The technology is more readily available today than it has ever been before.

It's really critical to start anchoring into where the technology will provide value and then equipping the people and every organization to then realize that value.

Byron Beebe
Yeah, I think as I listen to you guys talk and you said a lot of organizations are saying we've deployed AI. I think a nice follow-up question that is who? When you say we've deployed AI, who's deployed it right? Because just giving access to tools doesn't mean people are using them doesn't mean people know how to use them and it is the people inside of the organization that need to do this. I know we've talked to organizations who said I want to recruit people who have AI skills and there's limited number of those people out there. 

I think we have a point of view that: yeah, that might be helpful, but you also need to teach the people in your organization today how to do their jobs differently and use AI for that. So this research is highlighting a big gap, right, between the implementation and actually the usage in the field, which we would call workforce readiness. 

So what's at stake if organizations don't close that gap and what are the real risks of moving too fast with the technology before your people have a chance to catch up? So Amanda, maybe you have thoughts on that?

Amanda Scott
Yeah, absolutely. And I think we've already hit a little bit on this. There's spending a lot of money. There's a huge investment in this right now. But organizations just aren't seeing the return yet. So, they're deploying these tools, but they are not quite yet seeing those improvements in productivity or decision making or innovation.

And to your point, the risks are real. So you have that underutilized investment. Outcomes are not aligned to business priorities. So you mentioned, let's make sure that the employees within the organization know how their roles will evolve, how they can use these tools to really have a bigger impact. 

And I think the other interesting thing about this is that you start to have a pacing issue. So, if you move too fast on the technology without building the capability around it, what you're doing is you're creating noise and you're not creating value.

And then what happens is that adoption slows down, ROI stalls and resistance does start to increase. So, it's not about slowing AI down, but it's really about how does the organization and how do the people absorb it? How do they activate around it?

Byron Beebe
So, thank you for that. I know we've been talking to a lot of organizations about how to do this better. And I think sometimes what helps, and I don't want you to give names here of organizations, but sometimes I think what helps is just for people to hear what's it look like when somebody's doing it well, and maybe share some stories around organizations that seem to be struggling with this and what have they gotten wrong? Maybe share a little bit about that, Marinus.

Marinus van Driel
Yeah, absolutely. I think the organizations that are doing this really well, Byron, are organizations that focus on the work that actually matters to be addressed by AI. So what we know from our work is that AI can pretty much accelerate any work that exists in an organization.  But then the key question is, well, does that acceleration actually tie to work that creates value or not? So, we recently worked with a very large life sciences organization. And they asked us to take a peek at what work in their organization could potentially be augmented or automated by AI. And we looked at that work at a task level and then very specifically identified where the key opportunities existed within the organization and then unlocked the conversation with their entire executive leadership team around what their priority should be. And what that leadership team then did, which I think was absolutely exemplary, was they then identified where AI was currently being deployed, where it was creating value, and then how strategically all of those efforts could be stitched together to create something that's greater than the sum of its parts. 

And on the basis of us providing insight and informing choices, that leadership team then took the action to then go and identify five different investment areas that they could then anchor to and deploy their resources to further embed and scale the use of AI in their organization. And for me, that was a very clear business-rooted strategy, rather just a plan that was based on intuition.

Amanda Scott
And Marinus, you know I love data, so I'm going to jump in with a couple stats because I think that it's so true. We've seen that some of the basics aren't there yet, so organizations have a long way to go. I think it was 28% have fully operational AI governance in place. That's a lot of organizations that don't. And 15% have AI expectations and performance criteria. And only 6% have actually trained more than 80% of their workforce. So to your point, what's happening is they're just pulling levers one at a time. So they're training people, but they're not changing the work. They're deploying the tools, but they're not linking it to performance. And then they're putting governance in place, but they don't make it usable. So, there's a lot of readiness that has to go into this.

Byron Beebe
I get this question sometimes, and frankly, I think we see this here at Aon a little bit too. I think sometimes we are in rooms talking about how to deploy the technology, and the fact of the matter is the people in the room who are talking about how to deploy the technology probably aren't the people who are going to best actually use the technology to improve these jobs. 

So, I think part of the job of leadership is to provide that governance structure that you get as you're talking about but then also to allow innovation to happen. So, you deploy the technology, watch how it's used, and then take that, use that, and create governance processes and sharing across communities to help people who know how to use it better. I think that sometimes that's the role of the leader here is to sort of grab that, corral all that, and turn that into something that can be leveraged across the entire business. So that's great. 

So you had a couple good examples there. What about...if you talk to organizations that are really struggling with this and you have any sense for what those organizations could have done differently or what they do wrong, what are the slip-ups to watch for here? Marinus, I'll start with you there too.

Marinus van Driel
Yeah, maybe what I'll start with, Byron, is some remarks from a journey that we have recently taken with a chief operating officer and her team. In their organization, they've deployed AI in a number of different ways. The first way was to provide AI that was mainly deployed to enable personal efficiency of employees in the workplace. And the second way were through embedded systems. And as these embedded systems were built and scaled, they were incredibly powerful. But then there was a question that then arose from internal stakeholders, as well as the board around what's the value that's being derived from this. And the lesson that we learned in that journey is that it really, does serve an organization well to start anchoring to the why, as to why they want to deploy AI, and then have a very clear perspective on what the return on investment should look like.

Whether it's using traditional economic metrics that organizations tend to gravitate towards like net present value or internal rates of return, which are terms that are quite familiar to those who buy technology within organizations or whether there are other ROI metrics like capacity unlock or other metrics that may be operationally relevant. And I think for all leaders that are going down this path, knowing what it is that you would like to attain is absolutely critical.

I think that might sound like a platitude, but because AI just offers an ocean of possibilities and so many different pathways to go down, I think having that sense of parity around what the impact is that you have to create is really critical.

Amanda Scott
I know we were just talking with an organization, a health care organization, and they had actually thought about reducing the headcount of a team offshore and replacing it with AI thinking it might be cheaper, but actually it's not less expensive. Where the value was is actually they were getting better-quality outputs. The speed to output was faster. The insights that they could get was better. So changing how you define value is going to be absolutely critical throughout this.

Byron Beebe
Yeah, that last example is a great one in terms of not just figuring out where work gets done, but how work gets done. And what we're trying to do is are we trying to reduce the cost of the work? Are we trying to improve the quality of work? You got to find those things to think about how to use all of this. So, thinking about that, if you looked out two to three years, this is probably not fair, but just two to three years, organizations can bed-in AI in the workforce. How do you see the workforce itself changing and what can organizations do right now to stay ahead of that shift?

Amanda Scott
I think that work is going to be much more fluid, going to be much more skills-based and much more integrated with AI. So jobs are going to move away from being static and continually evolve. So we're going to see organizations organized more around skills-based deployment of talent, more project-based work, and then embedding AI across an entire core workflow. So rather than just project by project or piece by piece, really thinking holistically about how work gets done and how organizations have an impact. I'd love to hear your perspective, Marinus.

Marinus van Driel
Couldn't agree more, I think you're absolutely thinking about how work will change and how it become so fluid in the future. 
I think one of the other key things that I think will continue to happen is as organizations are learning and going on this journey, they will start to make more nuanced decisions. And they will have to start thinking through things like how to build the HR scaffolding to support how work is actually changing. 
So you reference the conversation that we had a couple of weeks ago. And had another candid conversation with the leader of a large healthcare organization. And she shared this example of nurses using this automated tool that can transcribe voice-driven conversations into patient notes and even craft scripts. And I was absolutely amazed at the foresight that exists within the medical community to provide these kinds of tools because typically, takes a lot of time to write notes and write scripts for patients. 

And so just bringing that full circle to my earlier comment, that's what I mean by the need to build the HR scaffolding to support how the work is translating. And as we're thinking about this, we're seeing sort of four major stages that are occurring in organization. The first one is that foundational stage. So it's that early exploration that's fairly informal. It's fragmented. Folks are learning. They're rolling up their sleeves. They're getting into things and all very organic.

And then the next stage is this developing stage where there are appreciable pilots that are being put into place. And there's a little bit of structure that's emerging around how AI is being put to work, whether it be through attaching it to broader work patterns or if there are very specific tools that are being implemented.

The next phase is like this integrated phase where AI is being truly embedded into jobs and into performance expectations and into pay and incentives. 

And then the fourth one is where organizations truly become AI-native, where their workforces are designed around humans and AI by default, not just its human work or AI work, but truly it's a collaboration between humans and the technology.

What we're seeing is most organizations are scaling their tools, but very few are redesigning their work. So most of them are in that foundation or that developing stage. And then I think that the question that's emerging from all of this that I think all leaders will have to grapple with in the near future is we can have AI do this work, but should we have AI do this work? And the point that you made there around economics, I think is really a critical one for organizations to grapple with because we're also seeing that some of the subsidies tied to tokens are going away. So a lot of AI has been subsidized by private equity. And now that cost of tokens or the use of AI is actually increasing and organizations are going to have to think about that.

Byron Beebe
Anything else you would share there, Amanda, just in terms of like leaders and how they should think about how to deploy this?

Amanda Scott
Yeah, I think one major takeaway I'd say is that the differentiator won't be access to AI. It's not going to be AI at all. It's actually for me whether or not people know how to use AI to drive real outcomes. And that's when AI goes from just being a tool to a competitive advantage. It's when it's in the hands of the right people.

Byron Beebe
Yeah, I've seen a lot of people for various different job classes say something like, your job won't be replaced by AI, but you might be replaced by a person who could do your job with AI, right? 

So, I really think it's the people using AI to do jobs better or to enhance what they can accomplish for customers of a business. Those are the people that are going to win. And I think leaders want to empower those people to be able to use AI to serve customers better. I really think that's a lot of what this is all about. 

So, thank you both for joining me today. I really appreciate your time. Really appreciate everybody who's been listening in. 

I would encourage you all to listen in. Like I said before, this is a mini series on what we found in our 2026 Human Capital Trend Study. We'll have a couple more podcasts coming. I would encourage everybody to listen into those as well. Thank you for your time. Have a great day.

Outro
Thanks for tuning into the latest episode of On Aon. If you enjoyed this episode, don’t forget to subscribe wherever you get your podcasts and be sure to visit Aon.com to learn more about Aon. 

We’ll be back next week with another episode — our Industry Insight — when we’ll be talking about the impact of climate risk on the Food, Agribusiness and Beverage industry. 

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