AI: Perception and Reality with Author and Analyst Geoff Webb

[00:00:00] Welcome to PeopleTech, the podcast of WorkforceAI.News. I'm Mark Feffer.

[00:00:17] It's a pleasure today to welcome Jeff Webb. He's an author and contributing analyst to 360 Insights,

[00:00:23] and he's got an impressive resume in technology and product development.

[00:00:27] Among other things, he was iSolve's vice president of solutions, products and marketing strategy.

[00:00:33] Of course, we're going to talk about AI today, especially about the messaging and marketing of it.

[00:00:39] We'll talk about reskilling too, and some of the challenges there you may not have thought of.

[00:00:44] All of that and more on this edition of PeopleTech.

[00:00:49] Hey Jeff, welcome.

[00:00:51] Thanks for having me, Mark. Always good to see you.

[00:00:53] So I wanted to talk not necessarily about AI so much as its impact on solutions providers and HR technology vendors.

[00:01:03] What's the impact then for vendors in their messaging, how they get their messages across to people?

[00:01:10] Yeah, I think there's a couple of things going on here.

[00:01:13] You know, you've got an awful lot of conversation about AI.

[00:01:17] You can't look anywhere without seeing AI sort of popping up.

[00:01:21] And obviously that's driven by some huge tech organizations who have got a huge investment in AI.

[00:01:27] You know, Microsoft and Google and Apple and so on are investing in mentionments,

[00:01:31] not to mention the dedicated AI technologists.

[00:01:33] What's happening is that it's sort of diffusing out into the rest of the technology conversations

[00:01:40] where people are asking, well, what is the AI?

[00:01:43] What are you doing? Is there AI in this?

[00:01:44] And I think even more than the question being asked,

[00:01:48] I think vendors feel the need to answer the question.

[00:01:51] Even if their customers aren't explicitly asking it,

[00:01:54] they feel the need to start to stake out a position on, well, yes, we're investing in AI.

[00:01:59] Yes, we have AI embedded in this.

[00:02:01] Yes, we're building AI into everything that we do because it will be better.

[00:02:05] It'll be smarter.

[00:02:06] It's become the sort of the pixie dust that we're going to be able to get out of.

[00:02:10] And so AI, at least as a messaging platform, is becoming very, very pervasive.

[00:02:15] The extent to which AI is becoming real in the way it's being built into technology,

[00:02:21] I think we're in very, very early days yet.

[00:02:24] And I think we're even in earlier days in the extent to which AI is being actively used

[00:02:31] to drive business process, to improve outcomes, to make it more accessible.

[00:02:37] There are areas, I think, where we're already moving down that path.

[00:02:40] I think the use of things like Chatbox, for example,

[00:02:42] to provide better interaction and access to information and sort of consume stuff

[00:02:48] and regurgitate it back in ways that are more interesting and easy to use.

[00:02:52] That's accelerating, I think, because of some developments in AI anyway.

[00:02:56] But I think we're also seeing just a feeling that they have to carry on

[00:03:01] with the way that AI is being used.

[00:03:03] But I think we're also seeing just a feeling that they have to kind of say,

[00:03:08] oh, we're investing in AI. We're building AI.

[00:03:10] We're using some kind of AI technology.

[00:03:13] We've got a large language model and we're going to use it for something.

[00:03:16] We haven't quite figured out what yet.

[00:03:18] And that's driving the conversation.

[00:03:19] And I think the problem we'll see is, to be blunt,

[00:03:22] that everyone will get rather tired of talking about it just at the point

[00:03:25] where we really should be having meaningful conversations about the way

[00:03:28] which it actually is being implemented in the industry now.

[00:03:32] It kind of reminds me a little bit. I'm giving you a really long answer, Mark.

[00:03:35] But it reminds me such a lot of the blockchain conversations back,

[00:03:41] I don't know, six, seven, eight years ago when blockchain became a kind of technology.

[00:03:48] You know, the awareness of it was driven by Bitcoin.

[00:03:51] And suddenly blockchain became the answer to every single technology question.

[00:03:56] Oh, we're building a blockchain model that will solve that problem.

[00:03:59] And the reality was it kind of went away and is used in a few areas where,

[00:04:04] you know, it makes a lot of sense.

[00:04:05] But the pressure to sort of talk about why we have a blockchain strategy receded.

[00:04:10] And I suspect AI will be quite like that.

[00:04:13] I think there'll continue pressure for AI strategies to be sort of surfaced by vendors.

[00:04:18] But right now, goodness, it is AI everywhere with everything.

[00:04:23] Well, and it seems like people are saying the same thing.

[00:04:26] Everybody's talking about increased efficiency, increased productivity, you know, better workflows.

[00:04:34] I don't really hear anybody coming up with any messages that are appreciably different from that.

[00:04:41] Am I missing something?

[00:04:43] No, I don't think so.

[00:04:44] I think the reality is whenever you're telling these kinds of stories, right,

[00:04:49] and ultimately what a vendor has to do, what a technologist has to do

[00:04:54] is tell a story to their audience about how things are going to be better for them.

[00:04:59] And so what you want to do when you're telling that kind of story is you tie it to outcomes that, you know, your audience cares about.

[00:05:04] They care about improving the profitability, better profitability.

[00:05:07] They care about things that lead to those like, you know, better staff retention,

[00:05:12] more better skilled employees, better vendor relationships and so on.

[00:05:16] So ultimately what happens is you sort of start with the thing that you're trying to sell,

[00:05:19] which is, hey, things are going to be better for you when you work with us.

[00:05:22] And then you work your way back into how do we deliver that.

[00:05:25] And right now what people are looking at is, well, AI can make you more efficient.

[00:05:30] It seems to be smart.

[00:05:31] It seems to be able to learn stuff.

[00:05:32] It seems to be able to automate processes better, we think.

[00:05:35] So as a result, that'll probably make you run more quickly.

[00:05:38] It will reduce your costs.

[00:05:39] It will make you more profitable.

[00:05:41] And as a result, that's fundamentally the story that everyone sort of starting to tell.

[00:05:46] And it's because the reality is that you think about all those technology vendors out there,

[00:05:50] they are not inherently AI technologists.

[00:05:53] They're people who have spent their life in, I don't know, supply chain management or HR,

[00:05:59] you know, HCM technology or pricing technology or, you know, collaboration technology,

[00:06:04] any number of other areas where they are domain experts.

[00:06:07] And now they're essentially attempting to infuse some degree of AI-ness into that area.

[00:06:14] So as a result, they're sort of tending to cleave to the same sets of messages,

[00:06:18] which is, oh, it'll just, it'll be better.

[00:06:19] It'll run faster.

[00:06:20] It'll be smoother.

[00:06:21] It'll be easier.

[00:06:22] Until we get more what I would think of as organic AI expertise in those organizations,

[00:06:28] we'll tend to see more of the same kind of messaging bubbling up because they're

[00:06:31] essentially using the same tools and the same background and the same technologies.

[00:06:34] And you know, you hear more users and more customers saying that they're just getting snowed,

[00:06:41] that, you know, all they're hearing about is AI, that AI is getting jammed into sort of every nook and cranny

[00:06:49] of HR tech, whether it's really there or not and whether it should be there or not.

[00:06:55] And it makes me wonder, it's like, you know, how much information from vendors is too much?

[00:07:02] Are we reaching a point or is there a danger that, you know, people are just going to kind of tune it out

[00:07:10] and just, just not pay that much attention to the whole AI angle?

[00:07:16] I think we've passed that point sometime about 30 years ago, to be honest, Mark.

[00:07:21] I don't think there's a lot you can blame on AI.

[00:07:24] I don't think you can blame that on AI.

[00:07:26] The challenge when you're a vendor is you're competing in a market in which there are other people essentially selling very similar things.

[00:07:33] And this is especially through technology vendors is, you know, it's really difficult to differentiate on the basis of the things you're selling.

[00:07:39] Technology, software is essentially an act of will.

[00:07:42] If you want to go build one, you can go build all the tools are all out there.

[00:07:45] And so it's difficult to differentiate on that.

[00:07:48] So as a result, you know, you want to quickly capture the conversation.

[00:07:52] And this is what good marketing is about.

[00:07:54] Good marketing is about capturing a conversation with an audience in a way and talk about things that they care about in ways that they understand

[00:08:02] and accept and keep them talking so that somebody else can't.

[00:08:07] It's kind of like, you know, you go to a bar and you sort of try to monopolize the conversation with an interesting person so that nobody else can get a word in

[00:08:14] because you don't want your competitors also talking about the same things.

[00:08:19] As a result, vendors quite naturally and, you know, I don't blame them for this.

[00:08:24] I've certainly my background comes from the world of marketing.

[00:08:28] You want to pump out a lot of meaningful good content in order to capture that conversation and keep it.

[00:08:33] As a result, the poor people on the receiving end of this are inundated.

[00:08:37] You know, it's one tsunami of content after another just rolling in and they're desperately sort of flailing around trying to figure out what should I read?

[00:08:46] What matters? What does it matter?

[00:08:48] Most of it doesn't get used.

[00:08:50] And the result of that, you know, marketing departments know that most things don't get used as a result.

[00:08:55] They create more things because if I just if I can double the amount, then at least twice the amount of stuff will get ready.

[00:09:00] Even if it's only a fraction of what I'm creating.

[00:09:03] AI is just another topic of conversation in which you can push out something that you hope will capture the attention of your audience.

[00:09:11] So, yeah, I think any any organization that's on the receiving end of this is going to feel pretty much inundated with noise.

[00:09:20] And the trick for good marketing is to kind of go well, we actually good marketing is really less.

[00:09:26] Less is so much more when it comes to good marketing.

[00:09:29] Just be much more focused and clear.

[00:09:32] That's that's brings up a great point.

[00:09:35] I was I was talking to the CEO of a vendor last week and I asked him about this.

[00:09:41] How how do you stand out from all of the buzz that's out there?

[00:09:45] And he said, well, you know, it really all comes down to good marketing.

[00:09:49] And. OK, I mean, sure, but that doesn't really tell you anything about the message.

[00:09:57] I mean, what is what does the message have to be?

[00:10:00] That's going to get people's attention. Yeah.

[00:10:02] Again, I go back to the thing that most organizations struggle with.

[00:10:07] And I spend the last it's funny. I said the last two years.

[00:10:10] No, goodness, not four or five months doing two things.

[00:10:13] I've been talking to a lot of CMOs in marketing organizations and I've been talking to a lot of HR people.

[00:10:20] And it's just been a sort of weird confluence of conversations I've been having on the marketing side.

[00:10:25] I can tell you that the the pressure, the sort of the gap that they're trying to close is consistently.

[00:10:34] How do we tell a good story? Right.

[00:10:36] Right. They I think most marketing organizations understand that they've got stuff

[00:10:41] they want to talk about technology and products and services and so on.

[00:10:44] But talking about them doesn't really move the conversation forward because everybody's talking about their stuff.

[00:10:49] What they want to do is tell a good story that resonates with that audience.

[00:10:53] And they struggle to get it. How do we tell the story of who we are?

[00:10:56] How do we tell the story of what we do?

[00:10:59] That's an area that I feel very passionate about myself is business storytelling is such an underrated skill.

[00:11:05] And yet it's so critical to engage in the audience.

[00:11:08] If you can tell a good story, you'll get people's attention.

[00:11:10] There's nothing like starting a conversation with, well, let me tell you a story because people go, oh, I'm going to listen to that.

[00:11:16] You can do that through marketing too. Right.

[00:11:19] You have to tell a good story and understanding how to bring the elements together to tell a story is so critical.

[00:11:24] On the other side of that, in the conversations with HR folks and HR leaders, they also struggle to tell a good story.

[00:11:32] And the story that they're trying to make sure they can tell is how are the things that we're doing going to benefit the business in terms that the rest of their audience understands?

[00:11:44] And that's been the key thing is I ask this question a lot.

[00:11:47] How did you get someone to say yes to this project?

[00:11:51] Right. You want to do this. You want to deliver more training.

[00:11:55] You want to streamline recruitment process.

[00:11:57] You want to deliver more, you know, better goal planning through the course of the year and tracking performance.

[00:12:04] How did you get the people who need to say yes, that project is important enough to divert funds and time and energy to over all the others that we could?

[00:12:12] How do you get them to say yes?

[00:12:14] And again, it comes back to the ability to tell a story of where you are and what's got to change and how that's going to change and what the results will be in terms that the audience understand and care about.

[00:12:29] And really, a scenario that's so fascinating right now is I think HR leaders are going, how do we tell this story so that we can compete with everybody else that wants the money and the time and the resources in order to make these really critical changes?

[00:12:43] Let me step back from AI for a minute because I keep thinking the conversation has been so focused on AI for so long at this point.

[00:12:56] You know, you watch the industry, the whole industry.

[00:12:59] So is there anything else going on?

[00:13:01] I mean, what else is interesting is going on in the space that people just aren't paying attention to?

[00:13:09] Oh, you know, well, I'm going to give a plug for your excellent newsletter, by the way, since I read it.

[00:13:14] So if you don't read it, you should. It's actually exceptional.

[00:13:18] It's probably one of the best ones I've seen. Well, it is the best one I've seen actually.

[00:13:22] Can I just interject to say to people that I did not pay you to say that?

[00:13:28] You didn't know that's true. I mean, if you want to pay me afterwards, that's fine.

[00:13:32] I think that's called extortion, actually. No, you did not. It's a great newsletter.

[00:13:36] It's a great newsletter. What do I have to say? Yeah, I mean, there's a lot going on right now. Goodness.

[00:13:41] So I think I've seen from the HR side of things, and this includes HGM technology as well,

[00:13:47] that there's been a sort of a shift away from hiring, hiring, hiring.

[00:13:53] You know, you're bringing people in, bringing people into the organization.

[00:13:56] There's kind of a market shift around a lot more thinking about development and sort of retention of existing people.

[00:14:06] So I think there's a shift around we're not just sort of desperately bringing people into the organization.

[00:14:11] We're actually slowing down on that.

[00:14:13] We're actually spending a lot more time thinking about building the people we have.

[00:14:17] And as a result, we're seeing more, you know, and I think you've written about this yourself,

[00:14:21] more investment on an HR processes, in HR projects and in HGM technology around skill development,

[00:14:30] training and sort of the development of your existing workforce into building, you know,

[00:14:36] sort of leadership paths and so on, which I think is on the one hand, it's very laudable.

[00:14:43] And it's a good thing. I do think we need to be careful of having a very simplistic view of what that looks like in businesses.

[00:14:54] In other words, we can simply say, well, we have, you know, we've got 800 people.

[00:14:59] We'll just train them all up or we'll train this block of people up into being doing all the things that we would have had to recruit.

[00:15:05] I think it's great to do it. But I think there are there are barriers that exist inside the way people operate that need to also be overcome.

[00:15:14] And I think HR leaders need to be very careful in thinking through that process or else they set unrealistic expectations.

[00:15:20] There's a lot of companies involved in HR technology right now.

[00:15:25] I think I saw somebody had counted them and there's something like 5000 HR tech globally.

[00:15:31] And people are always talking about consolidation or that there might be a shakeout in that space.

[00:15:37] And as you were talking, I got to wondering, it couldn't be that AI might actually lead to some kind of shakeout because because there are these other things that people are interested in, but people are only talking about AI or, you know, do you think there might be a cause and effect here?

[00:15:56] Well, I think it's inevitable that a couple of things always happen when you get these very disruptive technologies.

[00:16:03] You find that there's this sort of technological spring of things popping up all over the place.

[00:16:11] There'll be a lot of small organizations that step into the ring with a piece of technology or an approach that's pretty cool because they can go really quickly.

[00:16:20] We know that small organizations can innovate really fast compared to the bigger, heavier organizations that have a lot of technology debt and a lot of existing customers.

[00:16:30] So small organizations will pop up. They will inevitably become consumed by the larger organizations that are looking to acquire that technology and integrate it.

[00:16:38] I mean, this happens over and over again. We've seen this so many times during the course of our own careers.

[00:16:43] I think AI will inevitably cause that to happen simply because, again, that pressure on the big organizations, the big vendors to have an AI strategy.

[00:16:55] And here I'm not talking about the pure technology people like Microsoft and so when I'm talking about, you know, the industry vendors, the people that are selling HM technologies that are selling other kinds of technologies,

[00:17:06] the pressure on them to have differentiated technology that may well be defined by AI capabilities will inevitably drive them to become, you know, they'll be like some kind of whale harvesting plankton as they sort of swim through the technological sea,

[00:17:23] swallowing up small businesses in the hope that some of the stuff they buy in will actually stick and become useful and enable them to differentiate themselves.

[00:17:31] So yes, I think it will do a couple of things. I think it will push acquisitions, but I also think it will at the same time feed growth of small organizations and pop up with, hey, I've built something cool.

[00:17:43] Come find me and buy me because it's a great path to go make money.

[00:17:48] Now, if there's another, you know, buzzword or theme that's going on out there, it's skills and re-skilling, up-skilling.

[00:17:59] And people were talking about that before they were talking about AI.

[00:18:04] Now, now they've, every time I see someone talk about re-skilling, they're bringing AI into the conversation.

[00:18:10] But what do you see going on with re-skilling? Has it continued to grow in importance? It feels like it's becoming more of a foundational thing in this space.

[00:18:25] Yeah, again, I think going back to that point earlier on, I think there's a lot of pressure, a lot of focus right now on training and skills development and re-skilling and so on within organizations.

[00:18:39] The two parts of this, one is can AI help that? The answer is, you know, to a degree, yes, of course, right. You can do things like use AI to build, to identify learning paths, to sort of manufacture more and create more personalized learning paths that people can follow.

[00:18:57] So, you know, you're in this kind of role. You should learn this, this and this and this. This is your skills path. Obviously people can do that too, but AI can do it based on looking across industries, looking across people that have been successful in the organization in order to recommend.

[00:19:12] So you can use AI in one of the things it's actually, we know it's good at, which is a recommender tool. Netflix kind of, if you did, if you watched this and enjoyed it, you should probably like this too.

[00:19:22] You can do that with skilling and re-skilling. If you're doing this job, you should probably also learn this set of skills. Again, as the shift has occurred away from focused on hiring, hiring, hiring to retention and upskilling, I think that will play a bigger part in that.

[00:19:39] Again, I think the other point I want to make though is, you know, the assumption that people are just sort of sitting around hoping that people would, you know, somehow skills will be poured into them, that they are vessels simply waiting to be filled with new skills is a risky assumption.

[00:19:54] And I think, you know, we need to understand going into those kinds of projects to set realistic expectations and goals around upskilling and re-skilling.

[00:20:03] The simple fact is not everybody wants to learn new things. Learning new things is actually quite painful at times. And one of the key things that learning does, that I think, you know, we need to be very cognizant of, is it takes people that were good at something and it turns them into people that are not good at something.

[00:20:22] You have to be not good at something in order to learn it. I know this from personal experience because I have been the last couple of years learning to play the guitar and I'm very, very not good at it.

[00:20:32] And it's actually quite painful, right? I mean physically and mentally. And while I enjoy the process of learning, the process of really sucking at something is not something you get used to.

[00:20:42] And you know, when you're a kid, yeah sure, but as an adult and as a professional, I'm used to being good at the things I do. When we ask people to re-skill, we ask them to stop doing something they're good at and start to do something they're not good at.

[00:20:57] And that is a difficult transition for many, many people to go through. And so I think we shouldn't expect, you know, the sort of the workforce to act like sponges. They just want to soak up new skills and off we go and do something different.

[00:21:12] You have to invest the time and energy to provide safety and security and a path and reinforcement of the upskilling and the re-skilling process. And so yeah, I think it's great that upskilling is great.

[00:21:28] We should be investing in people, but we should do so in a way that is very aware of the foibles and the quirks of human nature, which is you're going to have to lead them along this path. You can't just say stop doing what you're doing. Go learn this and then you know two years from now you'll have a great job because it won't work.

[00:21:44] Which feels like sometimes that's what people are saying right now. That's what the employers and the observers, the people like us, you know, are basically saying is well, you got to get re-skilled.

[00:21:56] Yeah. But that's as far as we go.

[00:21:59] Yeah, it is right. And I, you know, it's easy to say like go learn a new skill. Go learn to be a software. Learn to be a programmer. You'll have a great job. You know, yeah, you were, you know, you were coal miner five years ago. Now you should be a software engineer. Yes, I don't doubt you can, right? I absolutely no doubt that that can happen.

[00:22:15] But building a path that people want to do that and that they're comfortable doing that, especially when they're already inside an organization where they have a job, that requires time, energy and focus and support.

[00:22:27] And that has to be part of the process of upskilling and re-skilling. And you know maybe AI will teach us how to do that too. Maybe AI will be able to show us how to build great, you know, supportive learning paths.

[00:22:38] But for now we shouldn't just assume that you can just re-skill your entire organization. So they want to do that. Even really highly skilled people, especially really highly skilled people will push back on upskilling and re-skilling. I'm great at my job. Why do I want to do something different?

[00:22:55] Jeff, thank you. It's great to talk to you and I know you'll come back. So I look forward to it.

[00:23:02] I look forward to it too, Mike. Always happy to chat. I always love talking to you. Thanks so much.

[00:23:08] My guest today has been Jeff Webb, an author and contributing analyst to 360 Insights. And this has been PeopleTech, the podcast of WorkforceAI.News.

[00:23:29] To keep up with AI technology and HR, subscribe to Workforce AI Today. We're the most trusted source of news covering AI in the HR tech industry.

[00:23:39] Find us at www.workforceai.news. I'm Mark Feffer.