How AI Is Changing Talent, Not Just Tasks: Rethinking Where Human Judgment Matters Most

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16:39Paula Goldman:How do organizations need to be redesigned? How should they redesign themselves now, given what we know about, you know, AI's capabilities, this sort of, you know, human plus agent workforce? I would imagine the design of work is lagging some of these things. So how do we think about redesigning our offices?

17:01Adrian Wooldridge:Well, I'll tell you how we think about it at Salesforce, and which is that we have this really cool division within our HR team that sits down with different organizations in our company and is actually using it to map the tasks that get done to different skill sets and looking at how some of those different tasks are rising as human tasks and some of them are changing and then looking at and redesigning roles of the future. I may have a biased vantage point on this, but like most of the roles on my team didn't exist a couple of years ago, like a responsible AI architect, for example. So part of the answer is like really actually creating those roles that are the kind of rising cresting need.

17:43Adrian Wooldridge:Second part of the answer is actually giving one's own team a seat at the table in that discussion, right? Not only because there's a lot of uncertainty and sometimes anxiety about what the future looks like, but because people that are closest to the work itself often have like really good insights about where things work or where things are needed and actually even where AI can play a role. And then I think it's really like using AI to give people a map towards that future. The kind of extreme version of it, I don't know if you saw the book Flash Teams by Melissa Valentine, but like that I think is becoming possible where people, their skills are legible and we're kind of bringing people together and changing it as the needs evolve really, really quickly.

18:30Adrian Wooldridge:we're seeing a slower version of that that is like a more kind of here's where strategically re-architecting around how I is changing the needs function by function.

18:40Paula Goldman:And talk about how this actually works in practice.

18:43Adrian Wooldridge:I talked with a number of HR leaders that are in charge of this sort of internal mobility, this workforce reinvention. I talked to someone at Seagate and I talked to folks at MasterCard And elsewhere, examples of people in government affairs that wanted to learn about security and they use their internal AI talent marketplace and identified like a little gig project that they could use on the security team and then ended up in a role there. Or people that ended up taking AI skills workshops and classes and participating in internal hackathons and ended up becoming forward deployed engineers. And there's a lot of technology that's actually quite mature that helps with this.

19:23Adrian Wooldridge:The interesting part of it, though, I mean, I found all of that really inspiring because these are stories that don't get told very often. But the interesting part of it actually was the cultural piece that people brought up, which is, you know, we think about bias. We're used to thinking about it as sort of like demographic bias, right? We think about bias in AI. but they were bringing up a different type of bias. And that was this notion that when people manage their own teams, they're generally looking for people with a particular pedigree, have worked at a particular type of company. And I think we're in this moment where no one has 10 years of experience with all of these different skills.

20:03Adrian Wooldridge:And we're going to have to be thinking about a bias towards the future and not the past if we're really going to have the kind of mobility that we want, but it requires a mindset shift, a cultural shift where people are actually validating and orienting around these types of skills and open to it in a way that I think has typically been kind of difficult for companies to manage.

20:27Paula Goldman:What do you mean exactly by a bias toward the future?

20:30Adrian Wooldridge:If we're talking about creating jobs and roles that have never existed before, that no one has decades of experience with. Like, I mean, yes, you can use a proxy for that. Like, yes, it's probably true that if I'm hiring a responsible AI architect, that like someone that has worked at a big tech company may have relevant experience. But it's also likely that people are going to come from unexpected backgrounds and that the more material piece of it is like, what are they able to create? And how do we assess that? And AI can help us with that, but we have to be asking the right questions first and not just defaulting to these kind of shortcuts.

21:13Adrian Wooldridge:And so that's, I think, the shift is like, the world of work is opening up. That's exciting. It's scary. But we have to be orienting ourselves to an openness to like what these skills really look like versus what we've typically hired for in the past.

21:29Paula Goldman:Well, okay. So if you were advising a CEO who accepts the idea that AI will fundamentally reshape their business in the coming years, you know, what are a couple of organizational decisions that they should make now before it's too late or whatever, before they're in a hole, whether it's creating new jobs or creating new departments or creating a new approach to work that we're seeing, you know, as effective in some places, that can help people think about sort of planning for this transformation?

21:58Adrian Wooldridge:I think it's going to be different for Salesforce than it is going to be for a pharma company, for example. But in all cases, there's like some very clear places where AI is actually, I guess it's kind of a horizontal where I think there are very few knowledge jobs that are not augmented by AI. And that part we've already seen. What we're starting to see then is the strategic identification of the places where AI is literally changing roles. So for Salesforce, it's not just customer service. It's actually like our engineering department is completely transformed by AI, right? That's like one of the hero use cases of this wave of AI.

22:36Adrian Wooldridge:And that means every single function that is supporting engineering, including mine, right? Like we're trying to make sure that all the products that go out the door are trustworthy, have to then use AI to accelerate all of their processes, but it's that identification of those new systems that need to be created. That's going to be different in pharma where AI is not only, you know, you've got the sort of base standard use cases like customer service or marketing or whatnot, but then you've got the AI and science part of it as well. And I think it's very, very important that CEOs or executives pick a few very big bets to focus on in terms of that transformation organizationally and not just rely on what has been common wisdom these last few years, which is like, give everyone a budget.

23:22Adrian Wooldridge:Yes, give everyone a budget. But it is that intentional strategic transformation of these roles that makes the biggest difference.

23:31Paula Goldman:Well, and I think we all blew through that budget.

23:34Adrian Wooldridge:Exactly, exactly.

23:36Paula Goldman:But I feel like there are a couple of narratives. There's a narrative that AI is transforming business in remarkable ways. It's flawed, but it is doing incredible things. But another narrative that I think a lot of intelligent experience people have is it produces a lot of slop. It is frustrating to employees. And we maybe have overestimated its value, at least in the short term. And whichever is correct, I do think that sense that AI is producing slop is a thing that exists in your workforce that either has to be proven to be untrue or has to be accommodated in some ways. I'm really interested in how you think about that, because I view you as essentially a realist, but positive about AI's potential impact.

24:17Paula Goldman:But there is this, I'd say, very vocal strain of skepticism. And how do you think about that balance?

24:25Adrian Wooldridge:Well, I think there's kind of two questions. There's sort of the general AI slop question of like, you get a message on Slack and like, Like, did someone write this or did AI write this? And I actually think our norms are readjusting around that, where it's become, I think, a little bit more acceptable that like, you know, that AI is being used to help with certain work outputs or whatnot. But the important thing, and again, this is, I think, the cusp of where we are, is that we're really reinforcing that your work product as an individual is your work product. And you need to take accountability for it.

25:02Adrian Wooldridge:And AI is very powerful, but it's not a magic bullet. Like it's not going to solve every single problem. And so in some cases, we're actually introducing what I was talking about before, like a little bit of friction before you hand this in. Like you want to make sure that like you really stand behind every word. It doesn't matter whether you used AI to do it or not. I think the other piece of it though is really how do you decide actually where not to use AI? And that's a question we're not talking about a lot. How do you decide what to reserve for people and why? And some of that might be like what we talked about before, like the customer preferences and whatnot.

25:43Adrian Wooldridge:And some of it might be the moments that hard management conversation, the time like your innovation team may want to really go deep on a particular idea before it brings in AI because you're going to get a better outcome. And there's a whole chapter in the book that's about AI and innovation. What's the role of AI and innovation? So IKEA, their innovation team wants to design a new prototype for a couch that breaks all the sort of stereotypes of a boxy, cushiony thing. And they use AI, and it just keeps reverting to the mean. Why is that? Because that's generally what AI does if it's not given enough direction.

26:22Adrian Wooldridge:And so they basically created space for themselves. It's called front-loading the brief before they gave AI its next set of instructions. And they started brainstorming things like campfire or gathering space and got really clear on these kind of breakthrough ideas before they gave AI new direction to co-ideate with them. And then they got this prototype called couch in a box, which was this lightweight 10 pound thing that someone could carry around and ended up being exhibited in a museum exhibit in Copenhagen. So why do I bring up this example? It's because just defaulting to AI can make for a worse outcome for whatever the task is that you're trying to do.

27:08Adrian Wooldridge:And some of the goal is not to just leverage AI strengths. It's to know where to preserve human judgment or to preserve human creativity. And that's, I think, the learning cusp that we are on right now in the AI journey. And that's a big piece of this question around so-called AI slop is it's bringing together the strengths of AI with the strengths of people. It's about designing human AI collaboration.

27:33Paula Goldman:So maybe, you know, further on this, you talked a little bit about the front lines and consumer interaction. This is areas, obviously, where trust is paramount, where you're really, you know, connecting directly with either customer service or more kind of frontline sales. Do you have any rules of thumb as to where AI is a benefit where you want to be careful? Yeah.

27:56Adrian Wooldridge:So we talked about the rules of thumb for customer service in terms of like either the goal of the customer or their emotions, anger, fear or anger, embarrassment and so on. I think for sales, it's also really interesting, right? Because, you know, all of a sudden you can use AI to do all the cold calling, right? Effectively. Or you can use AI to help all the inbound triaging, all the inquiries that you could never get to before. And we hear from all of our customers that are using AI for this purpose is like there are thousands of inbound leads that they could never get to. And so AI can personalize that outreach, right?

28:31Adrian Wooldridge:Whereas a human was limited to kind of the ones that they perceived as the highest value. And then it also has its limits, right? So yes, AI can help make a pitch. It can help understand what the customer is asking about. It can give a lot of information about the product. But when you're talking about a complex B2B deal and you're talking about stakeholders within the company that may not be aligned, maybe there was an org reshuffle, maybe someone's under a lot of political pressure, you're actually helping that customer reinterpret what their problem is, right? And understand it in the context that they're operating in.

29:12Adrian Wooldridge:And sometimes they won't even reveal that information unless they trust you, right? It's a relationship question. And so what we're seeing on these sales teams is that it's just transforming. There was a study I saw that said like salespeople experience depression at like 3x the rate of normal professionals because they're constantly hearing no, no, no, no, no, no, no, no. Well, cold calling is probably no longer such a thing, right? So hopefully the no's are less and it's a more focused, more human experience of sales. And that's one example of this balance of kind of the human side and the AI side.

29:50Paula Goldman:Yeah. What does all this mean for people management? How it is evolving? Obviously, we don't know exactly how it will change, but it's already changing pretty dramatically. So people in the people management business, you know, how do they stay up to speed with everything that's happening?

30:04Adrian Wooldridge:I actually think that people in the people management business are the linchpin for AI, right? And again, for all the reasons we talked about, the AI transformation is not just a technological transformation. It's a people transformation because you really, your human talent is still your most valuable resource. And then how you bring those things together is incredibly important. I will tell you my hope, and I see all these kind of green shoots of it, is that empowered HR functions use AI to make the people side of things better. And it's what we already talked about. It's like the nudges that make managers engage more.

30:44Adrian Wooldridge:It's the bringing evidence using AI to bring more data to performance management as opposed to like my recent impression of my employee. It's even like the AI systems that help really identify people's skills and new opportunities, like that new project that they could take on or the new class that they could take on that gives them a bridge to the thing of the future. I think there's all these super positive ways that HR can leverage AI to transform the company. And it requires intentionality, right? Because we all know those stories of AI gone wrong. people that were otherwise qualified for a job that got screened out or there are lots of ways that can go wrong but leveraged intentionally it's completely transformative for the human

31:33Paula Goldman:side of the business all right paula well thank you for uh for being on hbr idea cast thank you so much thanks for having me that was paula goldman salesforce's chief ethical and humane use officer and author of Manage the Machine, How to Harness Human-AI Collaboration at Work. Next time, Allison speaks with Nithin Noria about the biggest surprises new CEOs face. Plus, on Thursday, we'll present the next episode in our AI series, How the Technology Is and Isn't Changing Communication. If you found this episode helpful, share it with a colleague and be sure to subscribe and rate IdeaCast in Apple Podcasts, Spotify, or wherever you listen.

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33:14Paula Goldman:Thank you. into AI success. Visit dataiku.com slash HBR. That's D-A-T-A-I-K-U dot com slash HBR.