Peter Casey • 03:55
Hi there. So, my name is Peter Casey, and this morning's discussion is on the design of the organisation 2030, looking at workforce planning, the skills and optimisation in an AI world. So, we all know what is happening. We all know it's going to be pretty huge. We think there's going to be skills gaps appearing, costs could be rising, and things could be moving, and they could be moving very, very fast, maybe much faster than things have moved in the past. and organizations really need to do better work with planning and optimisation decisions to make sure that they are ready for the future. So we've got a couple of great speakers here. So my job is just really to be the moderator today and have some input. And it's really Helena and Jenna will be our main speakers here and they'll be introducing some in a minute. A quick bit of background about me, because that always makes a difference about the way we think today.
I'm definitely a techie background. I was COBOL programming mainframes, relational databases on Unix, I was client server, networks, cloud, you know, technology, technology, just another shift. And I honestly thought two years ago if you'd asked me, AI, just another technology shift, big deal. But the really big change I think with the technology is in the past, honestly, particularly in the 80s, systems were owned by IT. Now, systems are owned by the users, and that's changing even more, and technology absolutely has to give over all the control, I think, up to point to those users, because we impact them so much. I mean, realistically, when we moved up to various of these technology shifts, the average user honestly didn't know what the cloud was and couldn't care less. This time, everyone is talking about AI, and that's from obviously the executive level, but that goes all the way into the back office people.
That goes down to John and Sarah in the maintenance department, and they do know something, they do have opinions, and my goodness, that is going to change the way that things happen in the future, because the more people talking, the harder it is. So on that, let me also maybe ask Helena to introduce herself.
Helena | GoFIGR • 06:14
Well, thanks so much for joining. I'm Helena. I'm one of the co-founders of a career tech and workforce intelligence platform called GoFIGR based in Australia, but you can probably tell by the accent, I'm originally from the UK. We have been spending a lot more of our time and energy looking at this space. So in addition to doing things like making skills visible, helping companies with internal mobility, we've been focusing on the impact of AI on job skills and tasks. And last week, if you have a phone and this is big enough, you can scan the QR code in the top corner here. We launched an app that helps you get an understanding of how AI might impact your job, your tasks and your skills.
So we'd love you to download that. So I'm here to talk more about the sort of data and workforce side, and I'll pass over to Jenna.
Jenna.Goldstein • 07:03
Thank you and it's a delight to be here so thank you so much for being invited to come join you. So I'm Jenna Goldstein, I'm a partner at the Berkeley Partnership and we're a specialist consulting organisation with a hub here in London but also in New York as well and we are transformation specialists so for the best part of 30 years we've been helping organisations transform in one way or another and that's really across the whole life cycle that kind of transformation so whether that's strategy, operating model work, implementation, a lot of our work is actually underpinned by technology that's a complex transformation work that we do and we're pretty unique in that we are completely independent so we have no alliances or any partnerships with any organisation so we can be completely, think completely about what's best for the client and help make those kind of choices. So lovely to be here. And then I guess me slightly more personally, so my background is really actually started out in people technology. So I joined IBM way back when, and joined their consulting team and have done my fair share, what started with SAP implementations and HR all through collaboration tools, success factors, workday, whole load of workforce planning implementations as well. But what we did there was, and what really piqued my interest is, it's that combination of people and technology together. And then being in an organization like IBM, I grew up in that kind of world of innovation and it was at the time of IBM Watson and so on.
So it really piqued my interest. And then when I joined Barclay, it wasn't long before I wanted to continue that on. And I joined, completed an exec diploma actually, at Saïd Business School on AI business, AI strategy for business. And this was pre-Chat GPT. So it was going back a little bit, or at least it feels that way. So I really tapped into that community as well. So it's really nice, we've got that kind of academic view.
And of course, my cohort is in trying to make AI change happen. So you see that kind of ambition, but also reality. So hopefully today I'll be able to share a bit of stories not just from my own but from others that I'm connected with as well.
Helena | GoFIGR • 09:25
And just a small story, I found Jenna using Claude, so I was doing some research into, we have a client in the UK who wanted some expertise in workforce design as a result of AI transformation, so I turned to Claude and I think what you were, I don't know, your marketing team didn't realise that you were discoverable on a large language model, eh?
Jenna.Goldstein • 09:51
Yeah, so this I think is the first time we've been connected because we've been recommended by an AI normally, and actually like 90% of our work is referrals and word of mouth and, you know, follow on work, so we don't really respond too much to our feeds, so getting a contact through an AI rather than the website is really quite unique, but it just shows to us how different, you know, our way of interacting is changing whether we like it or not.
Peter Casey • 10:18
So, I'll check back with you, I need to start with this. So, I work for APAC AI, we're a consultancy company, relatively small at the moment, I think we're about 10 of us. We're actually very experienced people that over the years, many multiple years experience in IT, and what we're doing is helping people negotiate the maze of AI. But at the same time, we also partner with about three or four main products, one of which is GoFIGR. And so, again, this is how I know Helena. So, moving forward, what we're really doing now is actually thinking about what's going to be happening over the next four years. I mean, I don't know why we chose – I thought, why have we chosen four years?
Why talk about 2030, not 31, 29? But I think back to – those of us who remember the Y2K, the year 2000, where every computer system is going to die at midnight. So, that's what we're doing at the moment. And some companies started planning that in about 95, 96, and they did okay because they planned. Some companies left it late, and those companies then got stuck where, if I don't remember, I had been an IT contractor in my day, and in 1988, 1998, 1999, contract rates tripled. Literally, daily contract rates tripled because there's a staff shortage, it was running out there. And so anybody that's experienced that should not let that happen again with AI.
It's going to be a big, impactful thing, so we need to plan. If you're not doing something today, you should be planning today, that's for certain. And so obviously, there's going to be changes happening. So, you know, what changes in an organisation do we think are going to be inevitable, you know, or could be happening today, are inevitable over the next four years, and what work needs to get done for the organisation to be prepared for that? Jenna, Helena, what would you like to start?
Jenna.Goldstein • 12:12
So, sort of reflecting on your point there, Peter, about, you know, why 2030 strategy? And we are actually working with an organisation, a very large CPG organisation at the moment, designing their 2030 strategy. Because, you know, everything is changing so quickly that they just don't want to or can't think too far ahead, so it's in much smaller chunks now, so it's actually very relevant, the title of this webinar. So, I wonder whether it might help just to… share a little bit about how things have changed over the last few years and in terms of what we're being asked to support with. So it has gone relatively quickly from organizations asking us about how can you help us with our AI strategy? Or how can you help us work out what our AI use cases are?
So quite specific to AI. And more recently, the type of work that we're doing is less focused on the AI piece, but more about how do we reinvent? And part of that is using AI as part of that discussion. So it's really got clients going from thinking about productivity, the AI for productivity, which is where we were a little while ago, through to how do we use AI for growth and for strategic advantage and ambition. Again, so from automation through to invention. And the other clear theme is rather than having requests to help a certain team or a certain business unit, it's actually much more broad now. So how as an organization are we gonna evolve and harness AI for whatever that means for them?
So the shift of what organisations are thinking is changing and I'm sure it's similar in your organisations too. You're moving from that kind of pilot phase and experimentation into how do we actually productionise this and get this out and actually embed it across the organisation and see some real value. I'm sure Helena and Peter have got stats and so on about success of pilots and so on, but that's the shift that we're seeing. It's that kind of evolution, that maturity of now that AI is here and we've had a play with it, how are we actually going to get business value from it?
Helena | GoFIGR • 14:35
and of course they heard us. Do you know what kinds of things are your clients actually automating though? So I mean is it I wonder if we're still in the or a lot of companies are still in a phase of a bit of lack of imagination right is that we can only conceivably automate stuff we already do to make it faster or cheaper but are you seeing anything super cool or interesting that's a bit bigger than just automating tasks?
Jenna.Goldstein • 15:05
So that's where organizations are trying to get to but it's quite difficult to think that way so what we've seen and weren't seeing successfully is really automation of activity so one of the common use cases for those that have customer service, for example, is how do they use AI in customer service situations. So a whole host of, you know, taking the information as calls come in to an agent's telephone, trying to understand about the customer, finding out what they might expect the call to be about or what we would want to sell on, for example, and kind of automating that and providing then the service user with some information that could then… So I got distracted, so I'm desperate to get into that question. Yeah, it's definitely very messy. And so, yeah, so, you know, taking information, how do you support the customer service agent, the human, to deal with that query more appropriately or more quickly? What we're not seeing much of yet is completely reinventing how something could be done. So I was speaking with somebody who runs an internal creative agency in one of the CPG organizations, and they were looking to and had just started using AI for creative content. So Gen AI, what they are now able to do is, in the past, with their marketing strategy, they would follow the customer, has a degree of personalization. So if somebody put something in their cart, they would in the next morning, send an email, asking them if they wanted to buy it, reminder it's in your cart.
So I'm just gonna put that back on. And actually what they're able to do now with Gen AI is what they're working through is in real time, they can see that somebody has put something in their cart that they have not bought. They can then take whatever product that was, and they can create it automatically into a marketing piece of content. So it's a short video from the person's name, what they had, were planning to buy. And then they created a little story. So they would say, imagine the evening you could have had, had you bought this pizza or this beer or whatever it may have been, specific to the individual, and then had that straight out. So it's fun, it's hyper-personalized, and it didn't take much human interaction at all because they thought that working.
So that's an example of reinventing something that they would do, but in a completely different way. They've just never been able to do that before. So that's quite a creative use of AI, but there aren't that many organizations that I've seen who have really taken that and then productionized it. So really make it stand out and have that across the organization.
Peter Casey • 17:54
Tim, am I right, with the Berkeley partnership, you don't get involved at the Feetster level, like what you just described. Did you actually be recommending something like that, or do you just say to an organisation, when you're going to be doing things like this, your organisation has to change this way or be prepared for the impacts of having those new features?
Jenna.Goldstein • 18:14
Yeah, a bit of both. So we would help an organization work through how do they want to, what is their strategy? What are they trying to do? So it's always from that business perspective. What is it that they are trying to achieve in their organization? And the point I was trying to make is previously or earlier, people were coming to us saying, how are we going to use AI? Let's just fit it in.
And now they're taking a step back and thinking, hold on a second, there's this whole new capability that we can use, and we're not quite sure how to. So rather than just trying to dive in and do point solutions, point experiments, which was fine, and that's what we needed to do, they're taking a step back and saying, well, actually, what is it that we are as an organization in this new world that we're finding ourselves in when we've got different competitors, there's a whole host of different needs from customers. What is truly important to us as an organization? Because to use the example around the contact center, we have two organizations that are using AI in contact centers. One, their primary is to be efficient. They want to reduce costs, make efficiency, using AI in that way. And actually the other, which is an insurance organization, they don't have very many interactions with their customers in a human way.
So actually what they'd prefer to do is remove the friction from that experience to make it even more human. So things that they're looking at is how do I, using AI to have the notes of the last conversation that were there, so they're ready at the agent's fingertips, taking in some information around what's going on in the UK market just now that they might want to. or talk about to increase that human interaction of that engagement with their customer. So you've got two organisations where they've got two different priorities using AI to do what they need to do. It really doesn't have to be or certainly isn't a one size fits all. But there's a whole host of learning and explaining and the art of the possible to even to get to that point. And that's the journey that organisations have been on.
Just get started. That was the advice at the beginning. Just start, just try, just experiment. And now a lot of organisations are like, OK, we've done that, but what's next? And it's quite naive, isn't it? Well, what happens if this actually works? Helena, we were talking about this just a second ago. What is that plan? How do you actually get the foundations in place so that you can actually make this part of your core workflow?
Peter Casey • 20:40
isn't it one of those stats that's out there from, I think it's MIT, about only 5% of AI projects are going live. But then you've got to taper that and say, well, actually, how many were intended to go live? Because the proof of concept, yeah, if it works perfectly, we'll put it live. If it doesn't, because of the impact it can have on people, you can't really put it live when it's impacting people so much. So that's, and I think that's one of the changes we're gonna see over the next three years. I think this year, it might be 10% go live, maybe. But I think 2027, I think we jump up to about 30% going live because we'll be getting the hang of it very, very quickly.
And certainly one of the things that we want to do.
Jenna.Goldstein • 21:24
So I think there's a whole host of reasons why it's difficult to productionize something. So one is, you know, suddenly you start thinking, okay, hold on a second. If this is out there, you know, what's our risk profile? Are we compliant? You know, all of those kind of anxiety-inducing points. That's one thing. There's the point you're making around the people.
Are our people internally ready to work in this way or accommodate this new technology or whatever it may be. And then there's another, which is just a bit more physical, which is, can we actually scale this across our infrastructure? Are we actually set up to make this a reality? Because my experience of pilots is, you know, you can carve out a space. You know, you can fudge little bits where you need to. You can get, you know, your nice clean data sets and, you know, you can make it work because you're proving the value. Taking it from that to actually, okay, now in our normal ecosystem, our normal technical environment, does it work as easily, is it as robust, is it as trustworthy as it was in pilot?
There's a whole host of foundational things that you would need to make sure are there to really get that live and running. And I don't know, Helen, if you allow me, but I can see David's comment in the chat here about that initial phase being pretty messy. I don't know if you want to comment on that, David, because I think I would agree.
David Edwards • 22:48
Well, I think there are two things that I think I'm seeing. One is that we're all innovators now, because the cost of innovation has sort of kind of dropped through the floor. And consequently, you've got an awful lot of people who are experimenting quite often on the same thing. I don't see any evidence of the so-called productivity gains or the labor savings really starting to materialize. That sort of, there's a Parkinson's, is it the fourth floor? I can't remember which one. But anyway, we are continuing to be busy without necessarily seeing any dramatic change to how things are. The other thing that I'm seeing now puffing up in conferences is not just how you're going to cope with HR, sorry, with AI, a Freudian slip if ever there was one, but how are you going to sort of humanize, what's the human aspect in AI? And it's almost as though we're sort of kind of tripping over ourselves when surely what the first thing is we ought to be doing is asking ourselves more fundamental questions about exactly how is work changing as a consequence of AI and how are we putting guardrails and governance in place to…not police, but at least to orchestrate somehow the way in which AI is being applied.
Helena | GoFIGR • 24:31
Whose job is that, do you think? Whose responsibility is that, really?
David Edwards • 24:35
Well, that's where the fun begins, isn't it? Because you've got IT will probably be sort of making land grabs left, right and centre. I believe that the responsibility rests with with the business, but guided by HR. HR needs to get on the front foot with this stuff and actually ask certain questions of the business about exactly how the work changes. Because then you've got the opportunity to guide the business through the kind of changes to the workforce that might be needed.
Helena | GoFIGR • 25:13
not necessarily firings. Well, that's so interesting that the very first client we worked with to do a big scale AI impact assessment, well, we really had to do some soul searching to think about the ethics of doing this, right? Is that with the data we provide that say these tasks can be automated or these skills might change, be something of a self-fulfilling prophecy. And so we had to think carefully about once this data leaves our hands, we can't really control how it's being used. And the reason I was really happy to be working with that customer is that they said, success for us or maybe I'll flip it. She said, failure for us is being caught surprised in two to three years that these pilots we know are happening. And we like resulted in two or 3000 people being suddenly redundant when we knew full well that this could be a possibility.
And it's taken a lot of hustle for them to actually go and find out these sort of shadow IT, AI pilots that are going on. It's taken a lot of hustle and relationship to even be invited into the conversation, let's say. It's been quite hard for them to even know what's going on to then be able to have grown up conversations about what might happen in the next two to three years because it isn't the pilot in isolation. It's the, it's sideways as well. So you could have the fastest AI powered coder in the world, but that's no good if, you know, everything that goes in or out of that flow. So all of the quality checks and the way that you deploy technology isn't any faster.
You get no gain if you've just got, you know, one team running at a million miles an hour. So it's those kinds of conversations that I find a bit interesting when IT isn't, sorry, HR isn't necessarily at the strategic table yet.
David Edwards • 27:01
I think there's one, sorry, there's one other thing, if I may, and it doesn't immediately translate, but I think this class action that's now been launched against Eightfold by people who are unhappy about the way the algorithms have characterized them and identified them as being either suitable or not for particular roles has the potential to sort of overspill into this space as well.
Helena | GoFIGR • 27:31
Particularly any- But it's because it's so well legislated for, right? Discrimination is just so neat and boxed up like a bad piece of code isn't. Do you see what I mean? You do wonder if this, I don't know, it's such a clear case, let's say. It's so, I guess, defensible because legislation exists. It doesn't exist elsewhere though yet, or at least not to cover every kind of AI scenario that where a bad outcome could happen.
Hmm.
Jenna.Goldstein • 27:58
Anyway, sorry Jenna I talked right across you. No, no, it's, it's super interesting. Couple of points so I literally had a conversation with the client yesterday, who said yeah yeah everything, but we can't have innovation at the expense of governance controls ethics you know we know we're now in that zone we need to actually, you know, work out how are we going to make this mainstream in our organization. And what they also talked about was that they have not seen the productivity gains or at least translating to FTE that they expected to. Well that you know, a couple years ago, and even Microsoft, I was at an event with Microsoft recently and they said something along the lines of, Yeah, so what we found is, as you know, using Copilot, it's kind of, it's not FTE or half FTE, it's kind of an arm and a leg of a person. And actually what we find is that people do, you know, when they're automating out those, you know, notes and sending summaries and all of that kind of stuff, all they do at the moment is more of the same. So more emails, you know, they're just getting through their to-do list. So that promise of translating that efficiency in your day-to-day into, you know, higher value, we haven't unlocked that yet. So, you know, still debate whether it's there, but it hasn't been unlocked.
So I thought that was really interesting because one of the other things that we would love to think is that AI, it gives us space. You know, it doesn't just give us speed, but it gives us space. So space to think, space to connect, space to do all of those things that we want to do more of in our work. And it's how do we actually make that happen? You know, how do we actually do that? And part of that is around the adoption and the change management and really being quite deliberate about. as we start to implement these type of technologies to support us in our work.
Peter Casey • 30:01
Have you seen specific changes already within the skill set of an organisation that you can almost spot, yeah that organisation is moving ahead with AI compared to maybe one or two years ago? We can certainly see in the data that the demand for AI and AI adjacent skills is rising and that's partly because there's a fear of irrelevance.
Helena | GoFIGR • 30:27
This is purely anecdotal but we're seeing here at least in Australia that some people are leaving organisations where there's no AI opportunities, especially in some tech roles, they can kind of see the writing on the wall, right? Is that if there's no opportunity to do anything in the AI space, people are now starting to walk, which I think is fascinating. But demand for AI content and learning has gone up, but it correlates a little bit with what the senior leadership is saying as well. So I can also say that a couple of years ago, one of our clients brought this really cool Apple exec in who brought this, showcasing process and it was all kind of project, project, project. And I saw, I saw a spike at the same time in the demand for project management skills. So leadership does set the tone somewhat in terms of what's fashionable and desirable and in demand. But it has been interesting to see a bit of a disconnect between, because we can also extract skill content from learning. So we can see the skills that you're learning content is allowing you to acquire through the way that we extract skills from learning content. And then we can see demand and they're not necessarily marrying up. That's quite interesting. And then at least over here, I should have thought to pull the data from the UK before I came on this call. But the most in demand AI skill in the Australian labour market is AI, which just really makes me laugh. Just generic AI, you know, like, just give me some AI, you know, which just, just, it's really makes me chuckle. So we're seeing those kind of changes in the day.
Helena | GoFIGR • 32:08
What's your typical data source for that sort of information? Employees. Well, yes, it's, it's job ads. So we can extract skill content from job ads. We have people and we can extract skills. People either give us their skills or we have technology to kind of mine skills from natural language and infer skills. And then there's learning content and projects. So you kind of get like a skill, I don't know, supply and demand, if that makes sense. But going back to your, Jenna, your marketing use case, right? Yeah. It was, was it the actual marketers that designed that idea? Or was it someone external who came in and gave that idea?
Jenna.Goldstein • 32:47
They did it together, so what they had to do was they said they needed somebody to explain the art of the possible to the marketing team, to the creative agency team. So they had to explain the art of the possible of what could happen now with the technology. That then freed them to say, oh, hold on a second, so you mean that we could, how about if we could do this, you know, what about, how far could we go? Imagine if we could do X, Y, and Z, and then you start to shape it. Well, hold on a second, maybe you could start to do some of that. What would that look like? And then you've got a nice use case and you've got something you can try out. So for a lot of organizations, you need that blend of the art of the possible to get the creative thinking, you know, because it's difficult.
When you're used to working in a certain way, it's difficult to think in a certain way. with, to reinvent, to think of, you know, with clarity and not have the constraints of the current way of working, that takes a little bit of effort, well, it takes a lot of effort. And going back to the question around the skills point, that's one of the skills that we're starting to see is needed, that creative, critical thought, and in particularly in that leadership level, being really important.
Helena | GoFIGR • 33:59
That's what I'm most excited about, is it's leveraging the deep, you know, customer knowledge and sort of topping people up with this extra knowledge so that they, you're upskilling and you're taking advantage of all that institutional knowledge. What makes me nervous is cases that we see where people are being made redundant and then people are hiring, you know, AI this, that and the other off the shelf, like it gives me hope to see and hear examples of companies thoughtfully developing and nurturing that because they value that institutional knowledge, let's say, rather than fire and rehire.
Jenna.Goldstein • 34:38
So the only thing that's, so what organisations need is people who understand their organisation and their customers in their market. That's like the heart of what's going to make you successful in your organisation, is really getting your industry and what your customers want and so on. So, and what we talk about a lot with AI is this is not a siloed thing, it's not an IT thing, it's not an HR thing, it's not a business thing, it's collectively together, so you have to think as an organisation, and it's never been more important to have collective teams. So you don't talk about squads where you've got, you know, people representing different areas, they, you know, that is your team that you need to use with AI because the tech is only going to give you what the business wants if you've got business people in there who understand the data, who understand your customers, you know, this is really collective, bringing together all parts of the business to make sure you're actually getting what you need from it.
Peter Casey • 35:37
One of the things, all these changes, Jenna, one of the things you said you adopted that fantastic course, are you actually seeing within organisations, actually Helena you might as well, are people actually going on within organisations, are they yet sending people on AI courses? I mean actually it's so prolific at the moment, it is happening.
Jenna.Goldstein • 35:57
Yeah it's absolutely happening and what organisations are doing, or certainly did a little while ago whether it's still got quite the same ambition, is creating kind of AI training camps and AI kind of COEs to develop the AI knowledge and the skills. But there's a question here about how, what kind of AI skills do you need? Are you an organisation that wants to build your own tech? In which case that's quite a specific skill set, that's around data science, technology, development, all of that good stuff, that's a thing and that's a skill set. But then there's something which is more kind of broad across all the organisation I think, which is how to use it and understand what it can and can't do. We hear a lot about In the UK, Helena, there was an example recently about a decision being made in the police force based on information that they had used Copilot, I think, to do some analysis and take a decision and so on. So there's two things here for me. One is making sure that people who are given this access to these kinds of technologies understand how it works and therefore how they need to interact and behave with it. Fact checking is an example in that one. The second bit, which is discussed quite as much, is the organisation would have approved that tool for use. So they gave them that tool to use, I'm sure, for productivity gains. So there's a responsibility on the organisation here to really make sure that employees understand what they need to know. and create a culture where experimentation and learning and failure is okay, because that's the only way we're really going to adopt it and move forward, and safely as well, so that these kinds of examples don't happen.
One thing that I talk quite a lot about with organizations, again, because people just wanna get straight into the tool, people just wanna get straight in and start playing around with various things and getting to use cases, which is great. But the thing that we're trying to do now as we're thinking a bit more strategically is there's an order of events here. There's a mindset piece in change management. So what is that mindset shift that needs to happen amongst leadership, organization, and employees, so that they're thinking AI first, if you want that to be the case. Then you've got something around the skillset. Then it's teaching people how to interact and use AI in the way in which you want it to be used, so they can put trust and they understand and they've got confidence and so on. And only then do you worry about the tools that you're gonna use, because the tools are changing so quickly that you kind of need the mindset and the skillset, and then the tooling can come after.
Don't be driven by what the tool can do.
Peter Casey • 38:52
I think some of the questions that came from Adam is about, do we need a new type of HR practitioner who can actually build a tech solutions? So in the old days, the HR department were HR people, the tech people were over there. Should we now actually have a tech person inside HR, and HR starts looking out for its own solutions? Because the idea of, I must say, building your own AI tech is great as an old techie, I'd love to do that, but realistically, risk-wise, isn't a much better way you can, is to go and get something external. And then the same thing, would you start having tech people inside the accounts department, inside the maintenance department?
Jenna.Goldstein • 39:35
Well, to be real philosophical, is there going to be a tech person anymore, right? Because with a lot of these ways of using these kind of technologies, the intent, the reason why AI is so cool is because you can speak in natural language to it. You can say, I want to do X, Y and Z and it can work out. So, so, so do you need a tech person in HR? I'm not sure if you need a one tech person, but you certainly need to be thinking about HR, you know, how technology is used in HR in the same way you think about finance, in the same way you think about in supply chain, for sure. And what we see is that companies like Workday and SuccessFactors, you know, there's AI being integrated and the ability to create agents and so on in the core product. So do you need to be technical to do that? Or do you need to know your business processes in your organisation to be able to do that? Still to be decided, you know, but that's the way they want it to be, to be, to behave. But then the other part for HR, and this is where I think is really, really, really important, is that, you know, this is a digital, this is about digitising the organisation and the workforce to some extent. Previously, you know, in old money, you'd go to the CIO, you know, this is the CIO's bag, this is the tech piece here. Actually, I think that the chief people officers, the chief HR officers, they're the ones who are really gonna be at the forefront of making it happen and actually getting the workforce enabled and ready to take on and use this new, this future way of work. So the HR organization has got two mindsets. It's got, how do we embrace this?
And then how do we support the rest of the organization to embrace it too, in a way that protects employees, that gives them this leverage, they can super power and supercharge the work they do. Oh, is it breaking up? My back? Yep. Oh, I was on, I was in Flow then as well. No, no, we heard you fine. Okay, good.
Jenna.Goldstein • 41:30
We heard you fine. So, yeah, so, so, so should HR hire a tech person? Yes, but it's probably not a person, it's probably a capability. You know, how do we do, you know, how, how do we, how do we embrace this ourselves and how do we support others to do it? Interestingly, so I hosted a panel back in November and our panel was, was about how do you get, you know, how do you move from pilot to production? And we had the best panelists. We had somebody from WPP, somebody from IAG, which is the owner of British Airways, British Standards Institute, and Belron as well.
And they, they independently said that one of the skills that they're finding that their managers need, they haven't ever had to think about before, is product management. So they're in a world now where they've got people, you know, they're managing humans, doing their tasks, and then they've got agents that are working alongside them. Now, they didn't talk about humanising the agents. It wasn't like I've got a digital co-worker. That wasn't the route they were going. They wanted to make sure that there was a tool, not another human that was competing with the current staff. But they were saying, you know, for the first time, they're having, the managers are managing people and they're having to think about product management, which is a skill they've never had to develop before.
You know, that's a capability in its own right. So they're now thinking, how do you manage this work when you've got people doing some things, you've got machines doing some things, and then you've got machines and humans doing things together and that is a different mindset and a different skillset for managers, you know, outside of HR, but just in the business.
Helena | GoFIGR • 43:11
And also- I think that's happening to jobs all over though, right? Is that we can see when these little scans come in, we can see it in the data, right? Is that we provide an impact score, right? So to what degree are the tasks that make up your job going to be impacted by AI? And we'll see the same two jobs come in and they're vastly different because, you know, a marketer in a startup is completely different to a marketer in a big corporate. And it makes me wonder about like, jobs are kind of unbundled.
You know, if I think about my past life in HR, I was more of a project manager and a quality and a process and a technologist. I was a bit of a weirdo. And I need new skills in my bag of Legos now, right? Is that I think I'm a designer because I can clawed up a nice user interface, if that makes sense. But I'm a bit ambit, I'm not really great at anything, but I'm good at a load of stuff that I wasn't before. And my job has morphed quite significantly in the last couple of years, thanks to AI. And I see that happening to the jobs is that it'll be kind of unbundled and re-bundled.
And Adam, you know this really well, is that, you know, the capabilities that you would have likely had in a couple of jobs ago in an HR team look vastly different now. You're all supposed to be marketers and data analysts and you have to have a great group of technology. That wouldn't have been the case, you know, 15 years ago, 10 years ago in HR. Like our jobs are all a bit murky and blurry and job titles aren't really, kind of don't cut it anymore.
Jenna.Goldstein • 44:40
Yeah, we need to take a few questions don't we? Can I just add one little thing before we go to the questions, just to pick up on Helen's point because when the Global Talent and Innovation Lead at WPP was on our panel, she talked about Exactly this, which is, it's not now about the functional skills that they need to look for and to develop across the organisation, it's the competencies, the behavioural competencies that they're needing to focus more on. So that ability to adapt, to shift, to connect with others as well, so bringing various parts together in order to get something done. Whereas before you were an expert and you knew how to do that, now you want to be a developer, you know, develop a website and you're actually in HR, how do you find the information that's going to allow you to do that, or the people or the tech that allow you to do that? And then the other thing that one of the other panellists talked about was resiliency. So the need for employees to develop resiliency, because they're continually learning new things. So he was talking about in the old days, say old days, not long ago, you were given a new product or you had some new technology and you would learn it and then you would use it and then you'd be in your happy place. And that, you became competent in that. What's happening now, he's seeing in his organization is, a new tool or technology is coming and then you're starting to learn it. And then by the point that you're starting to feel competent, something else comes.
And it's not just a new tool that comes that does the same thing. It's a completely new capability. So then you're back at the bottom again, and then now you're learning it. So you've got this continual emotional rollercoaster of anxiety, competence, and so it's that shift of being able to embrace that change and having the humility to say, I knew something last week and I don't know it again now, but that's okay. We're not great at that, are we? And particularly for leaders as well, to stand up in front of an organization and say, we're doing this, but actually. six months later it's changed. Anyway, I'll leave it there. You're right, it's good questions.
Peter Casey • 46:50
I should point out, if you go onto the Barclay Partnerships website, they actually do have some really, really useful cases and knowledge bases. So I would have a look at that afterwards. Right, so the question I really want to throw out there really is, and this is like any good course, it's like, right, what are you going to do tomorrow after having taken this course differently? So the question is, if a leader wants to be ready for 2030, what is the one thing that they absolutely must be doing today? You know, and if they're not, well, make sure you're doing it tomorrow, no later. So, yeah, maybe to start with that. I'll start with Jenna and then go for it. Honestly, go.
Jenna.Goldstein • 47:36
Well, when Helen and I just spoke just briefly before, I said there were four things, but I'll rank them now. So my four, super quick, leadership qualities. So what are what are the leaders of the future need to be? So thinking about transparency, trust, being able to have empathy with people as they change. And what are the new what are the leadership qualities are going to need to get this landed? I would say bringing the tech ops people, all of that together. So that is now the mindset that you need is a collective as opposed to siloed thinking.
If you're in the technology space, start thinking about what does that technical landscape look like? How am I how are we going to productionize this? What are those foundational things we need to do to get ready? Because it's suddenly going to come. But if I can say one thing, it would be invest in the change management capability. So how do you manage change across the organization? And maybe it's just the organizations that I work with. But I don't think I've ever gone to one and they say, oh, yeah, you know, we really now change management. But great. It's more like, yeah, we don't really know. That's the last thing that drops or we haven't invested in that or, you know, it's OK, but we need to bring in specialists.
Peter Casey • 48:45
I think there's a statistic yesterday about, I think it's McKinsey, were saying that actually where a project includes change management, it's 35% more likely to be successful than if you don't think about the change of management. And that data is probably based more on old classic systems. I think with AI, I think it's way more than 35% chance of improving the chance of success.
Jenna.Goldstein • 49:13
I think organisations will also need to update their change framework as well, because traditional change, it's almost been like, we've made a transformation, we've implemented something, whether that's process or technology, and we've trained the users, and they are the recipient of this change, they've received it. I think what's going to happen, what is happening in change management now, is that the end users, the organisation, are now participants in the change. It's no more like we've done it and we've handed it over. They are now participants in that. So as you think through your change management strategy, how are you going to make that a reality? How are you going to get that feedback? How do you get people to feel ownership? Not just for its starting, but to make it better and to make it work. So yeah, change management is the one.
Peter Casey • 49:59
I don't know, something that you could maybe know about. The first thing you think about when you're about to do change is you've got to understand where you are today. Do you think most organisations actually even know their skill sets, where they are today and what the roles are? Because I think like the tool you talked about is if you've got an organisation, there's a whole group of roles. Those roles are more likely to be replaced.
Helena | GoFIGR • 50:28
I think that's Peter Frozen for everyone or just me. Okay, I think I got the gist of the question. I, it's probably not shocking coming from the company I do and the, you know, the fact that I left a corporate job to go and start a startup in the sort of people analytics and career development and skill space, you know, I'm that obsessed. I don't think people have much visibility on what people are doing. No, I think at line manager level, most people have a pretty good grip of what they're humans do. But it's really hard, right? You know, some companies have good quality position descriptions and documentation.
Others don't. Even if you do, it's not like that's a sort of static thing. You know, that person you hired two or three years ago is probably doing something vastly different now than you hired them to do. And I think. It boggles my mind that our most expensive and valuable asset, which is our human capital asset, is such a big black box. I think if you're going to be making change and automating things, or bringing people on a journey, or trying to leverage all that unbelievable domain expertise and knowledge and upskill, I do think you need a bit of a grip on that people data asset. I think it's a huge opportunity.
I think for so many companies, what people do and how they're skilled and what they want to do and all of these kinds of things, it's such a big, big black box. I think it could be a really good, you know, an interesting competitive advantage for people. So, especially if you want to do anything with your people data, you need data, right?
Peter Casey • 52:04
So can I open it up to the rest of the people? I mean, do any other people think what they believe people should absolutely be doing today or tomorrow at the latest?
Helena | GoFIGR • 52:18
Well, what's anyone doing? I'm sure everyone joined because they have some kind of AI interest or pilot or something. Yeah, what's everyone up to if you're comfortable sharing?
Peter Casey • 52:28
Yes, yes, put away your secrets, tell us.
eddie.lawrance • 52:32
I can't see how to raise my hand. Maybe AI could help with that. For us, so I lead a architecture team from a technology point of view, and we've started using Copilot because we can trust it because of what data it's got access to, etc. And we started using it for impact assessments. So as you get a change in, actually say, okay, this is the requirements, get it nicely worded. What's that look like it's going to impact? Can we understand the areas it's going to impact from the business from a technology point of view? But as I mentioned in the chat, it only works if you've got that documented somewhere. So where a business process is only in someone's head, or a technology is not written down or somewhere you've got access to, the AI is clueless. So I think of it as a highly skilled, but junior new employee, that you have to sort of guide. And when they come back with a response, go, that's great, but you didn't think about this. And then you're like, why? Oh, we've not given you that info. And you see that like with a new business analyst, they can run with stuff. if they don't have the data there to work with, they can't do their role. And so that's how I'm trying to lean on this at the moment. And really, as I mentioned, I've just got my team going out, trying to gain data and have it available. And even if that's just interviewing the business, but you record it so you get the transcript because it's still available to the co-pilot. And then it can be sort of referred to and actually used as fact.
And before going on too much, the only other bit is you have to be careful of what information's lying around in your organization because you put a proposal for a project forward, but then never did it. For AI, that could be seen as real and it happened. So actually understanding the status of those pieces as well to sort of go, no, no, ignore that, ignore that because you put five proposals together, but only one is true is also a risk for AI. It's not necessarily always got the context.
Helena | GoFIGR • 54:39
Oh, the tech debt, the documentation debt, the debt we're all in now that we're all kind of like regretting, eh? Yeah.
Jenna.Goldstein • 54:47
This is it, isn't it? The organisations are only going to be able to change as quickly as they are capable to. It's not tech holding anyone back, you know, it's both from a people and, to your point, Eddie, you know, the infrastructure and the information that we have, the data, that's what's going to hold people back, not the technology itself.
Helena | GoFIGR • 55:08
We had a question submitted earlier, in advance actually, about whether it's, well, the question was role replacement or skills change. So I actually, Warwick, are you on the call? I think I saw Warwick join. No, okay. Oh, no, Warwick's there. Well, let's interpret that to mean, are we talking about role replacements or skills changes? I think both. Thanks, David.
Jenna.Goldstein • 55:47
I think a bit of both and new as well. So I think there's a lot of anxiety because we talk about it in, we talk a lot about replacing tasks, replacing skills, replacing jobs. And there might be some of that and there probably will be, but there's also what's going to be new, you know, what else is coming? What's going to emerge as a result of this? And I think the narrative that you help create in your organisations around the opportunity and developing that trust that we're doing this in the right way is super, super important. So again, goes back to that change management narrative of what is it that you're really trying to do? What is sacred and you're not going to let go? What can change without impact? But I think it's a bit of everything.
Peter Casey • 56:41
Ideally, it's training the skills first. So, what, skill people first before we start maybe hopefully changing out the roles too much, but some roles will absolutely change and change very quickly. I think I did like the tour that you've got there, Helena, for about where your job role is going to be. The email you get back doesn't just say, oh, these parts of your role, the role might be disappear or at risk, but actually encourages people to think, but these parts of your skill base are going to be needed more. So, IE, concentrate on that. So, if you can get each individual to think like that, then the department will think like that and maybe the whole organisation will think like that. It's to work more on the stuff that's going to be important.
Helena | GoFIGR • 57:28
Are there any other questions? We've got a couple of minutes left and I know people are needing to get on with their day. Is there anything else we didn't cover from the questions? I don't know if Alison's on the call. I don't think she is at the moment, so we can take Alison's question separately. Was there anything else anyone felt okay about unmuting and asking? Adam, you've been surprisingly quiet. I expected a punishing question from you. I'm sure I'll get it via email.
David Edwards • 57:55
That's all good. Thank you, though.
Helena | GoFIGR • 57:59
All right, well, maybe we should wrap up then and let everyone get on with their day. I'm going to go to bed. Other end of the day for me. We will make sure everyone gets a follow-up with a link to the recording if you would like to share it with anyone, some other resources from Jenna, Peter and I as well that we think might interest you, amuse you or support you in this endeavour because we're all quite avid content creators in this space as well. And if you haven't already connected on LinkedIn with us, please do. Peter, is there anything else you wanted to say or Jenna before we close?
Peter Casey • 58:31
No, I think the thing, I think we really have talked and got some things. I mean, there's a lot to be done about AI and we just do have to get, we must get on with it.
Helena | GoFIGR • 58:39
Crack on. There you go. There's our key message for 2030. Chop, chop. All right, thanks for joining everyone. Good to see some familiar faces. Thanks so much. I really enjoyed it.
