The ROI Was Never in the Tool

AI tools are live, people are using them, and adoption dashboards are running. Only 29% of organizations are seeing actual ROI. The gap isn't a technology problem — it's a sequencing one. The work that would close it was never done.

Jackson Lynch and Scott Morris break down why "deploy the tool, get the result" is structurally false — and what the organizations earning returns are doing differently. If your board is asking what changed, this episode is where to start.

What You'll Learn

• The 45%/7% Gartner gap: AI is delivering, but the freed capacity has nowhere to go — and that's the whole problem.
• Why treating launch as the outcome guarantees the proof gap, and why work redesign is a separate, harder project than deployment.
• The four-play post-launch playbook: deployment audit, forward baseline, workflow redesign, and vendor accountability.
• Why the CHRO is the only person in the enterprise positioned to own both the technology side and the workforce side simultaneously.
• How to establish a forward baseline today — even if you didn't capture one before launch — and what to measure going forward.

Key Quotes

• "The tool is working and the freed capacity is going nowhere."
• "We deployed the technology, so now the business will benefit — that's just a false assumption."
• "Post-launch isn't a failure state, it's just a different starting point."

Sources for Statistics Cited

• 45% of managers say AI is delivering as expected; 7% of HR leaders provide guidance on redeploying freed time — Gartner, March 2026
• 87% of CHROs forecasting greater AI integration in HR in the next 12 months — SHRM State of AI in HR 2026
• 29% of organizations seeing significant ROI from generative AI (attributed to McKinsey) — Source not directly verified; closest McKinsey finding: 39% attribute any EBIT impact to AI (McKinsey State of AI 2025)
• 51 work days per employee per year lost to technology friction — WalkMe study, cited by Futurum Group
• Organizations earning $1.50 for every dollar invested in AI — Source not verified; closest published figure: $1.41 per dollar (Snowflake/ESG Research, 2025)

Transcript

Scott

Forty-five percent of managers say their AI tools are delivering as expected. Seven percent of organizations are providing any guidance on what to do with the time that those tools are freeing up. And the gap between those two numbers is where most of the AI investment went.

Jackson

I'm your host, Jackson Lynch, and today I am joined by my co-host, Scott Morris — a friend of mine, a former CHRO with all the scar tissue to prove it, a person who was once called emotionally unavailable in an AI pilot post-mortem, and the founder of Propulsion AI. That was a pretty good one. I like that one.

Yeah, Scott, the last time we did an episode together last week, we laid out the constraint-first framework on the show. And the argument was: stop asking which AI tool you should buy, and instead start naming what's actually holding the business back, build a business case around that constraint, and then select the tool. We called it "the order is the ROI." And the response since then has pointed us directly toward a couple of follow-up questions. The most important one that we didn't answer is: what if you're already past all that? What if the tool is live? What if the rollout happened, people are using it, and you're now sitting in a world where the board is asking what changed — and you don't have an answer that connects to anything material?

Scott

Yeah, and I think one of the reasons that question lands so hard is that it's the actual situation a lot of CHROs are in right now. The constraint-first framework that you and I named in the last episode — I believe in it deeply, I'm running a company that helps people with it — but the room that's hardest to walk into is the one where the vendor is already building, the adoption numbers are coming in, and the CEO is telling you to move faster. The pilot phase of enterprise AI is over. Most organizations already launched, and the board isn't asking whether you're invested — they're asking what's changing.

Jackson

Yeah, and that gap between the promise that justified the original investment and now the proof that the board is requesting — that's where this episode is going to live. The question today is not "how do we get AI right from the start?" — we did that episode last week. The question is: if you're already on the other side of the launch, what the heck do you do now?

Scott

Right. And before we actually get into it, let's do a shout-out. This week we want to shout out to Jordan from Atlanta, Georgia — my old stomping ground. Jordan, thank you so much for being a part of this community. It genuinely means something that you're here. And to everybody else who's joining us today, whether you're joining us from Kuala Lumpur, Malaysia — believe it or not — or Melbourne, Florida, we're really glad you showed up.

Jackson

Jordan used to work for me a long time ago — a decade ago now — and he still listens to the podcast. We got a chance to connect this week. It was wonderful.

Scott

Another thing before we get going, Jackson — let's talk about the CHRO Ascent Academy, because you're doing some really good work to help CHROs. Take 30 seconds, everyone. Think about something useful that you've learned about the CHRO role that you hold or the one you're aspiring to be in. The kind of thing that's actually changed how you show up in a conversation. Chances are it came from somebody in the same seat at a different company. One graduate of your program, Jackson, said that the program gave them tools to work through in their own organization, to apply the learning, and bring it back to the group in the following session. And I think that's the mark of a great program — you can apply the material almost immediately. Ten CHROs, twelve weeks. That's the CHRO Ascent Academy. Seats are limited. Head on over to mytalentsherpa.com. And if any of that landed, don't wait until the cohort is full — those cohorts fill up fast.

Jackson

They do. Okay, let's dive in. Here's where we are. And the numbers change from week to week, so some of these are going to sound different from what we talked about last week — that's just the world we're living in right now. You get more data, we're going to bring you the most recent stuff we can find.

What I read in SHRM's 2026 State of AI report is that 87% of CHROs are forecasting greater AI integration inside of HR in the next 12 months. That number isn't really surprising. But what sits underneath it — I think — is that only 29% of organizations are saying they are seeing significant ROI from generative AI, despite wide deployment, despite surging investment, and despite the fact that most of those tools are doing exactly what the vendor said they were going to do. That number comes from McKinsey. That 29%, by the way, is the highest I've seen — I've seen that number in the middle single digits, too. The key takeaway is it's not paying off. And the gap between deployment and results has never been larger. Organizations sitting inside that gap are not early-stage experimenters anymore. These are 12 to 18 months post-launch with adoption dashboards and almost no proof architecture.

Scott

And you and I both know why — it's because we're measuring the wrong thing. Let's be specific about what it looks like in practice, because it's not always obvious from the outside. Tools are live, as you said. People are using them. The vendor is tracking logins — if that means anything. The CHRO is pulling adoption reports. All the activity is real. The problem is that nobody connects it to the business outcome that the investment in the tool was supposed to move.

There's a specific number that hit me when I saw it. It's from Gartner research, and they found that 45% of managers say that AI is delivering as expected. But only 7% of HR leaders are providing any guidance on what to do with the time that those tools are supposed to free up. So the tool is working — and the freed capacity is going nowhere. And nobody in the organization is asking what should happen to it.

Jackson

Yeah, that second number is the one that explains the first, in my view. When AI delivers efficiency at the manager level and no one has designed where that capacity goes, the efficiency gain gets absorbed into existing work patterns. You might save five minutes on an email, but chances are you're now going to write ten more emails. You have a faster organization, but it's doing the same things. And the proof that the board is asking for — the P&L impact, the structural change, the business outcome — it doesn't materialize in any visible way, because the conversation around redeployment never really happened. So the promise from the original idea is real. The deployment closed the loop before the most important question not only got asked — it certainly didn't get answered.

Scott

And part of it is just work redesign — and that's what's not going on. There's research from the Futurum Group that puts technology friction, as they phrase it, at 51 work days per employee per year. That's the productivity that gets absorbed when the AI tool goes live without adequate design around how humans are actually supposed to use it. Which is what makes artificial intelligence as a technology so different from past technologies. The spend is up, adoption is up, and operating results aren't moving in proportion to either one. And the CEO is asking you why, and the CFO has started to frame the AI investment you made as a liability. And you, as CHRO, are walking into that conversation with an adoption dashboard.

Jackson

Yeah. And by the way, this is not new — it's not tied to AI. In any HRIS implementation I've ever done, the real costs aren't in the implementation of the tool, but in all of the wraparound processes around it. But here's one way to think about this: the organizations that are already getting ROI from their deployed AI — I'm going to guess that they made a different decision. I think they probably treated the launch as the beginning of an accountability conversation, not the end of it. And that's again not different from any other technology we've talked about. The change continues until people stop talking about it. The ones who are still searching for proof treated that launch as the thing that proved it was working and celebrated it. Mission accomplished. And that distinction — by the way — is what this episode is all about.

Now, usually at this stage of the podcast we talk about three or four different assumptions. But this week is going to be different. I think there's one assumption underneath almost every post-launch AI conversation that's not producing results. It's the hardest one to name because it's shared by literally everyone in the room, including the board. And here it is, ready?

We deployed the technology, so now the business will benefit.

The tool is live. People are using it. The work is done. What actually has to happen next — redesigning how the business operates around the technology — is a completely separate project. It's a harder project. And almost nobody told the board that it even exists.

Scott

Yeah, and that's the difference between the tool as the end and the tool as a means to the end. We need to be thinking about the second one. Let's sit with this for just a second, because it's structurally more important than it might sound.

When the investment in the technology — AI or otherwise — got approved, it was the approval of a technology project. The approver — the board, the CEO — understood the investment as: we're going to buy a tool, the tool gets deployed, and the tool produces some efficiency gains, and those gains somehow show up in the P&L. That's a logical model. But it's also the model that explains why every major technology investment for the last 30 years hasn't always produced results. Spreadsheets, CRMs, ERP systems. You deploy the tool, people use it, the organization moves faster.

Jackson

I think AI breaks that model because the tools are fundamentally different. Prior technology investments were about making humans faster at the work they were already doing. AI allows you — and candidly forces you — to fundamentally redistribute what work belongs to the tool and what requires a person. And that labor model redistribution doesn't happen automatically at deployment. It requires a deliberate design decision. You have to talk about it. Someone has to ask: okay, now that this tool exists, how should the work around it be structured differently?

And Scott, I think that question is organizational design. It's not a technology question. We're treating it as a technology question. It's never part — and probably was never part — of the board-approved work up front, because the board doesn't know enough to approve anything at that point.

Scott

Because we didn't describe it as such. We weren't thinking about it as such. We were thinking about buying a technology — and that's just the wrong frame. So the board is sitting in a conversation where they approved a technology project, the technology gets deployed, the expected business result doesn't materialize, and from where they sit, the logical conclusion is that the tech somehow failed, or the implementation was mismanaged, or the timeline just needs to be extended. What they don't know — because nobody told them up front, because we weren't thinking about it up front — is that a second and harder project was required to capture the ROI, and that second project hasn't started yet. That's about to become a big problem.

Jackson

Yeah. Look, this is hard. I don't want to underestimate that. And CHROs may not be in a position to name it clearly, because if you name it, it surfaces a problem and it feels like resistance to change. If I were to sit there and say, hey, we're deploying AI but we didn't redesign the work around it — I'm also saying that the business case we presented at the very beginning was incomplete. No one really wants to lean into that chin-first. Because in most cases, they told the board here's what the tool is going to be able to do. And the people I'm talking to these days — they're not thinking three steps ahead, because everything is coming at them so fast. They're not having the conversation about work redesign. They're not having the conversation about the scope required to do it. And they're now placed in this really uncomfortable conversation. You have to lean into the courage, and that doesn't always happen naturally. So what happens? The gap persists.

Scott

Well, and this is where I differ with you maybe a little bit. Artificial intelligence is a fundamentally different system, because previous tech deployments had you doing basically the same job — just with a better, faster tool set. Here, the right move is to say: your job is going to change. It's going to morph. That job may not exist anymore because we're going to break it up and do it differently because the tech allows us to. I've been in that room on both sides. I've been a CHRO applying past tech deployments. And I run a tech company, and I watch deployments land — and the pattern is pretty consistent.

Vendors demo capabilities. We try not to do that. We try to demo the result you're going to get and help organizations capitalize on the capacity that's created. But the capability of the tool is real, the purchase gets made, the tool gets deployed, and the question of how work should be designed differently because of that tool gets treated as something somebody else is going to figure out. The vendor isn't going to participate in it — that's a big can of worms for them. And leadership isn't always thinking about it. And it doesn't figure itself out. It requires exactly the kind of thinking that takes time, senior attention. It can't be delegated to frontline managers, and definitely not to individual contributors — they're just trying to get through the work week. It has to be done at the senior level.

Jackson

Yeah. And you talked about it last week — so if you haven't listened to that podcast, I encourage you to go back. Because one of the things Scott goes into is the importance of how to investigate and interview the vendors you bring in, and the kind of questions to ask and the kind of answers you should expect — because there is now a bifurcated vendor market. There are vendors who think in outcomes and vendors who think in products. Those are not the same conversation.

But bringing it back here: you mentioned the 7% number — the percentage of organizations actually guiding their teams on what to do with newfound capacity. I think it reflects a systemic absence of the work design conversation, because no one really owns that work today. I think ultimately we're going to have to own it, because if we don't, the different lenses across the organization are going to make it much more challenging.

But think about this as a measure — I'm coming up with this right now: should we be tracking redeployed time as one of the outcomes from an AI implementation? I haven't seen that happen, but sitting here right now, it makes sense. Today what we're doing is talking P&L and talking about investments. We might be talking about ROI, but we haven't defined it very well. And ultimately I think we will find ourselves in a position — and the right CHRO who can do this will be extremely valuable to the organization — to lean into the discomfort, have that broader conversation, and say: here's what was assumed, here's what we hadn't thought about before, here's what we're going to do now with it, and here's how we can measure these outcomes. I just think that's a conversation that needs to happen. It's going to be really uncomfortable. I wouldn't want to have it, because it feels like you screwed up.

Scott

You know what, all of this ground is new for all of us — you, me, every sitting CHRO out there. Nobody has perfect answers yet. But I think one key to success is: we shouldn't be thinking about work redesign as a one-and-done. I bring in a tool, I redesign the work around it, I'm done — now we're in measurement phase. Because it doesn't always happen that way.

The CHRO who can walk in with a diagnosis to the CEO or to the board and say: here was our hypothesis coming in about what this tool was going to do to this set of results; here's what we deployed; here's what we expected to prove; here's what has happened; here's what has not happened; here's why we think that hasn't happened; and here's where we're going to do further redesigns to tweak the things that weren't caught in the first redesign — that's what we're going to have to start sitting with.

We've come from a world where work was very static. You had a job description nobody needed to update for five years because it was basically the same job. And where we're headed, your job continues to morph and change — not only as new tools come in, but as the existing tools get new releases, get better, and allow you to do different things with your time. That's an ongoing process, and we're all going to have to get used to it.

Jackson

I agree with you. But we're also stuck in a loop. And what makes the loop so durable is that in the current state, everyone is doing their job correctly. IT deployed the tool. HR is tracking adoption. Finance is capturing the financials. No one is careless. No one is doing anything wrong in isolation. We just have a loop that runs because the accountability structure that would break it was never built. That structure is the entirety of the work design conversation.

And in my view — in the conversations I'm having — unless you're in the top 50 companies with entire armies going after it, we just never stop to have that conversation because the urgency to push things forward was at such a pace that we were focused on understanding what was hitting us, not what comes after it. But what comes after it comes at an accelerated pace than anything we've seen before.

Scott

There's a proof gap, too. Every month that passes without a measurement framework, the distance between what was promised initially and what can be proven gets wider. The original demo language the vendor was using becomes some kind of anchor. The vendor said it was going to reduce time-to-fill — if we're talking about recruitment — by, say, 40%. That number is now in somebody's slide deck from 18 months ago. The board has seen it. The board is now asking whether time-to-fill actually moved. And without a baseline measurement and a current measurement, it's genuinely difficult to know a reliable answer. And "unknowable" is not an answer the board is going to accept.

Jackson

Yeah, so let's think about the frame shift that changes what's available to a CHRO post-launch. We've hit it — we don't need to hit it again. The dominant model for deployment treats launch as the outcome. Don't do that. The implicit assumption is the proof will follow automatically — the tool is live, people are using it, and that should be evidence enough. That model produces the gap we've been talking about.

Because the proof doesn't follow from deployment, you have got to decide what business outcome the tool is supposed to move and how the organization will know it's moved. And if you haven't done it up to this point — what's the line? The best time to plant a tree is 20 years ago, but the second best time is today. It's time to grab your shovel.

Scott

Right. And the reframe here is: post-launch isn't a failure state, it's just a different starting point. The constraint-first framework that you and I talked about in the previous episode doesn't require going back to the very beginning. It runs from wherever you are. The CHRO who treats today — whatever day it is in the deployment timeline — as day one for the measurement conversation is doing something fundamentally different from the one who is managing the gap between the demo promise and the board's expectation.

Jackson

So here's what I think day one actually looks like, whatever day that is. You can't go back and establish a baseline you didn't capture — that's a loss. I get it. But you can do two things right now to change what's available going forward.

The first is to name the constraint retroactively. What were you trying to solve? Look at every active AI tool in your stack and ask: what specific business constraint was this tool supposed to relax? If you can name it, you have a framework for forward measurement. If you can't — by the way, if you can't do that, you've identified why the ROI story doesn't exist. You have more work to do.

Scott

The second thing — and it goes hand-in-hand with what you just said — is to ask the work design question that never seems to get asked before launch. Given that this tool is live today and people are using it, how should the work around that tool be structured differently?

Remember, the tool is supposed to be removing a constraint. The question is: what are your people going to do with the time that gets created when that constraint is gone? What does the tool handle? Where does human judgment go — because AI does many things well, but it's not doing the reasoning and judgment tasks. Those are still human-based. Who is going to consciously direct the freed capacity? Those are organizational design questions. And the CHRO is the person in the enterprise best positioned to both ask those questions and act on the answers.

Jackson

One hundred percent. And there are organizations doing this really well right now. They're earning $1.50 for every dollar they've invested. They're not necessarily doing it because the tools are better — in some cases the same vendor is in both rooms. The difference is that one organization designed the work around the tool and the other deployed the tool into the existing work design. That's a major gap.

As we mentioned before, previously we were in that same work universe — but where we are today is that you can redesign everything inside of it. And that forces you to think through things that you had the latitude to get away with last time. You don't anymore. So I think the CHRO is in a really uniquely important place here, because you can close it post-launch — it's harder, but it's available. And the CHRO who claims it now owns the accountability conversation for the entire enterprise.

Scott

And AI accountability is a different frame of thought. Accountability isn't: did I get the tool deployed on schedule? It's: did I get a result after we deployed the tool? That's the strategic reposition that's available to every CHRO right now — not as a defense mechanism, not as an explanation for why the ROI isn't there yet, but as the person in the enterprise who understands the technology and the workforce well enough to design a connection between them. That's the new mandate for any of us as CHROs. And it's a mandate that is available to any CHRO willing to do the work that defines it.

Jackson

So let's transition to what we do about this starting Monday, because I'm sure there are people listening who are thinking: okay, this is really great, we've identified all the stuff that's happening — here I am, what do I do?

Let me lean into one of my favorite ideas: run your own deployment audit. What does that look like? Pull every active AI tool in your tech stack. Probably start small — just look at your HR world for now. Next to each one, write the specific business constraint it was purchased to relax. Not the feature, not what the vendor promised — the constraint. If you can fill in that column for most of your tools, you have a starting point for forward measurement. And if you can't, it's okay — you've now found the root cause. The constraint was never named, which means the work design conversation was never even possible. If you can complete that diagnosis this week, I think it's worth more than another adoption report, because it tells you exactly where the work needs to start.

Scott

Take 30 minutes. Time-box it. Take 30 minutes and do that audit. It's probably the hardest part because it's not going to feel like forward progress. Once you've done that, the next move is to establish a forward baseline — and you need to do it today. If you're already in the midst of a deployment, you're not going to call a reset. Just set the baseline here: take a picture of where you are today. Pick one active AI tool — ideally something with a renewal coming up in the next six to nine months — identify the business outcome it was supposed to move, and then measure where that outcome stands right now with data attached to it. Now you've got a forward baseline. Now you understand where you are, so that in 12 months you'll know what the data is telling you about how that number has moved. It's not a perfect proof architecture, but it's a pretty good one. And it's available to any CHRO who's willing to do it today.

Jackson

Yeah. And let me double down on the perfection thing. This is where I see a lot of our peers get really stuck. The math isn't the important thing. That you have math — that's what matters. Get it close enough, have a baseline with some analytical rigor around it, and call it good. You don't need to figure it out to five decimal places. You need a starting place, and then you can use the same methodology to measure forward.

If you do that well, I think it then allows you to move to the third play: pick an active deployment where adoption is solid but you can't point to a change in business outcomes. Go back and ask the work design question. Get people in the room. Figure out: given what we now know about this tool, what work should change? What is high-value activity, what is low-value activity? Is the low-value activity able to be consolidated into an agentic solution that's either in the tool or right next to it? And you need to make sure the human is in or above the loop — the judgment and discretion I mentioned earlier — identify who owns those decision rights and what they should be solving for. Then figure out what to do with the freed capacity. Because if you create the capacity and don't tell people what to do with it, you will not get any of the benefit. In fact, you're going to have people who might sabotage what you're trying to get done in the worst case — or at least be confused about what they're supposed to accomplish in the best case. Neither of those conditions is going to help.

Scott

Let me give you the fourth play. It helps if you've got a renewal coming up — but don't wait for the vendor to schedule it with you. Start scheduling it yourself, and do it in possession of the knowledge that came from the other three moves. Focus first on the constraints. What are you trying to get rid of? Don't let the vendor come in and give you a demo of their system's features. Start engaging them in a conversation around your constraints. The questions you want to get them ready to answer: what business outcomes have your best-performing clients measured from this deployment? How did they define it? What were their before-and-after numbers? They are obviously there to sell technology. You should get them into the business of selling a solution — because the solution is what you need. Their tech is just a means to the end. Vendors who can't answer those questions are optimizing to get dollars out of your wallet and hoping you aren't paying attention. The vendors who can are partners who are going to go on that journey with you toward a different business result — not just a technology deployment. That's a relationship worth having.

Jackson

That's the four-step playbook. All right, senior leaders — here is your favorite part of the pod: the Talent Sherpa summary. Or, as I think I heard Scott say in the pre-pod call: the best post-launch AI strategy is to give the board an adoption dashboard, call it the business case, and hope no one from finance is in the room to ask a follow-up. Get it? No, he never said that.

Scott

And don't do that — because that is not, in fact, what you want. All right, here's your summary.

One: 29% of organizations are seeing actual ROI from AI despite widespread deployment and surging spend. The gap isn't a technology problem — it's a sequencing problem that has already happened. The tool went live, the constraints weren't named before launch, and the proof architecture got built around the only thing available: adoption metrics. That's not the right one.

Two: The assumption running underneath almost every post-launch gap is "we deployed tech, so some kind of business benefit is going to follow." That's a false assumption. What it misses is that redesigning work around technology is a separate project. It's actually the one that leads the technology project. It requires deliberate design, senior attention, and real invested time. But it didn't get scoped, it wasn't funded, it wasn't assigned. That's where the problem started.

Three: The CHRO is the best person in the enterprise to hold both sides of the conversation simultaneously — the tech side and the workforce side, the deployment and the work redesign, the adoption metric and the business outcome. CHROs need to start claiming that responsibility and claiming the AI accountability conversation — not from a position of defense, but as a strategic mandate.

Four: The four plays. The deployment audit names the constraint each tool is supposed to relax. The forward baseline starts the measurement clock today. Redesigning one workflow turns an adoption number into a proof story. And managing the vendor conversation before renewals — setting up for strategic partnerships rather than vendor demos — is the key to having a long-term partner who is going to sell you a solution.

Jackson

How did I do? You sound so smart in the summary. I don't know how you do it.

Scott

I wish you could do it the rest of the time.

Jackson

Well, we've gotten feedback from the audience on that one too. Look, what I keep coming back to from this conversation — honestly — is the work design piece. Because organizations that are getting post-launch ROI are asking different questions than the ones who aren't. Not "how do I get more adoption?" Not "how quickly can we get the tool in?" The question needs to be: given the tool is live and people are using it, how should the work around it be designed differently? And what do I do with the capacity that frees up, so that I'm reallocating it toward the highest-value work available?

I think the CHROs who are asking those questions and building the proof in that context are the ones boards are going to recognize and reward. I just can't reinforce this enough: this is the moment the CHRO has been living for for the last 30 years. It's time for us to lean into discomfort and figure out a way to make a material impact on work design inside of businesses — because we're the only ones who have the ability to do it. Thank you so much for tuning into the Talent Sherpa Podcast. This is where senior leaders come to rethink how human capital really works. So much fun to do with everybody — especially you, Scott.

Scott

Thank you, my brother. Same to you. And if you like the podcast, do us a favor and hit the subscribe button. It's what delivers episodes to you, and it's also the way the algorithms activate. That shares the pod with other senior leaders — so not only are you doing something good for us and something good for yourself, you're doing it for somebody else. You can check us out on Apple Podcasts or Spotify or YouTube. We're across all of them. Take a moment and leave us a review — those help too. Again, it's free, it helps us, and it helps us reach other senior leaders.

Jackson

And if you're listening on Apple, they're going to start doing video. And if you had video today instead of listening, you could see Scott Morris's black eye. And we're not going to talk about how that happened.

Scott

No, no.

Scott

It's a 175-pound dog that slammed into me. I guarantee you it was not a bar fight. So yeah.

Jackson

Now, unfortunately, if you are watching on Apple Podcasts going forward, you will have to see me. And as I've been told, I have a face made for radio.

But I do want to talk a little bit about Scott's company, Propulsion AI. It's a workforce intelligence company for private equity. Their AI teammates are surfacing workforce risk before they close — and that helps leadership teams drive execution afterward. One of the cool things is they can translate strategy into individual accountability. They can coach managers to define roles by outcomes — something we talk about on the pod all the time. And they can give every employee a clear line of sight into what actually matters. It's all really good stuff, and it's all driven through artificial intelligence. You can learn more at the very cleverly named getpropulsion.ai.

Scott

If you're a new CHRO, an aspiring CHRO, or if you're preparing to step into the role — Jackson has built a bunch of tools that are going to help you operate at the altitude that role demands. Personal coaching, the CHRO Ascent Academy as I mentioned at the top of the episode, even his best-selling Substack — everything you need is at mytalentsherpa.com.

Jackson

Hey, thank you, Scott, and thanks to everyone who is listening. Until next time: keep raising the bar, keep designing the work before the adoption dashboard becomes your only evidence, and keep on climbing.