AI-Powered HR: Expert Strategies for Workforce Transformation

Helena  00:00

It's wonderful to speak to you today, and we've had a couple of conversations in the past, but maybe you could start by introducing yourself. Kind of how you came to be where you are today and what it is that you're doing right now.

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Fanni   00:13

Yeah. Well, first of all, thanks for having me. It's wonderful to be here and as always, it's wonderful to chat with you. So just a quick introduction. I come from a typical corporate finance background. I have almost 20 years of corporate finance leadership experience. From an education perspective, I studied economics.

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Fanni   00:36

I have a degree in economics as well as in psychology and various certifications in coaching and data analytics. So even from an education background perspective, I have a dual. It's clear that I have a dual interest in hard data as well as in people. I started my career at PwC as an auditor and consultant and I left roughly after four years. And I said to myself, I really enjoy consulting, but I need to learn the hard stuff on the client side because I didn't feel that it's very authentic to give advice without experiencing the other side. So I went to work for Xerox in various finance roles, and then most of my career I spent at Microsoft. I was the local CFO and then regional controlling director. I have three kids and I had quite an extensive maternity leave and after that I didn't really want to go back to corporate finance.

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Fanni   01:40

And so I started thinking my interests were clear, it's data and people. And I started thinking where I could add value. Where is my sweet spot? Why was I high potential in my previous roles and. Because I don't think I'm the best data analyst ever. And I'm not the best, I don't know, data scientist. I'm not the best coach.

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Fanni 02:08

I definitely am not the best therapist. But where I'm good at, I think, is connecting the dots, connecting the two, building a bridge between data strategy and selling this to people. So why is, that's why I was successful, I think, in the finance transition that we just talked about before recording in Microsoft. When I arrived at Microsoft as a CFO, the finance team was a typical admin finance team. So focusing on operational tasks like accounting, payroll. Admin stuff, and my main task was to drive the finance team and lead this transition to becoming a real strategic business partner. And that not only meant outsourcing the core finance operations, but also building up a controlling team and upskilling the controlling team to become impactful.

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Fanni   03:10

So not only doing the number crunching for all the rhythm of the business reviews and the budget cycles, but also delivering actionable business insights and selling that to a business. It was a huge change management process that not only meant change within the finance team, but also meant change within the stakeholders or managing the stakeholders expectations. We sat down with Esther, who happens to be my friend and ex colleague. She used to be the HR director and then regional HR director at Microsoft. She also has an OD consulting background and she really, I think it's not an exaggeration to say that she is really an HR AI expert. So we sat down like one and a half year ago and started this discussion, how we could team up and bring value to companies, how hybrid was founded a year ago. And just recently we had our first anniversary and we did a quick review about our past year and what we want to do differently in the next coming year.

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Fanni   04:27

And we were discussing if somebody looks at our company or looks at us. How would somebody be able to summarize what we do? And we agreed that we need to be better in explaining why we have the three, let's say solutions or departments people analytics, HR strategy, alignment and HR AI technology as Microsoft partners. And we came up with the idea that we are like augmenters, augmentors in a sense that mentors we are like business consultants, helping HR teams to be successful in the AI age and tackling this opportunity to become a real strategic partner. And Augmentor in a sense that we don't only work on a project basis, so we offer a subscription type of expertise to our clients because we think that upskilling does not necessarily mean that you have to become a. Full blown data analyst, for example, as an HR expert, in order to become data literate as an HR team, it can mean that you outsource this. And I think, by the way, it's also a little bit more beneficial from a bias management perspective as well, because we have this outsider view on everything that is happening within a company.

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Fanni   06:00

So this is how we define ourselves. We are augmenters and we are hybrids. So building a bridge between data and the present to the future, and helping HR teams to be successful.

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Helena  06:18

That's fascinating. And we met over a specific piece of work that you were working on at the time. And I know that this is a concept that you're still exploring, and this is about the continued interest in understanding the risk of automation on occupations. Could you expand a bit more about what you've been doing there?

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Fanni   06:40

Yeah, absolutely. So the whole idea came from a tender that we were invited to where the main task would have been to assess the impact of generative AI on two specific tasks, roles, sorry, on the task level and give an assessment of the HR strategy implications was pretty much it. How clear the tender was. But. In order to participate in the tender, we had to work out the whole concept. So we put together basically a framework of how to tackle this buzz around AI from a job role level and as an HR professional. So the idea really is to first of all, I think it's not rocket science, as I said many times, it's not boiling the ocean, it's not an intergalactic war plan that you need to put together.

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Fanni   07:46

It's only a very structured approach that really helps HR teams and HR professionals to find a way in the jungle, information jungle and the hype that's around AI today. So the idea that we start with the job analysis, it's a typical job analysis, deconstructing the critical jobs into tasks and then defining or identifying the most important AI use cases on the task level. Based on that, we would also give an estimation of the potential efficiency gain if that use case is implemented, as well as an assessment on the primary skill change. So just to give you an example, for example, in a data analyst role, one use case could be that Excel is doing or Data IQ is doing predictive modeling. So it's not the routine and very well structured tasks would be done by Excel or. Power Bi or let it be whatever it is. What is remaining is really what you do with these insights that are delivered automatically by excel or whichever tool it is.

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Fanni   09:12

How do you sell that to the business? How do you make it actionable and insightful? So the primary skill from being able to clean the data, structure the data, doing all the arithmetics and the statistics behind it, it turns to being able to strategically position the findings that come out from this analytics. That's just a very simple, let's say, example, but there are hundreds of these like that. So on the use case, on the task level, we define the primary skill, and then, of course, we're going to aggregate that on the role level. As an aggregation, it would be clear how to reprofile the job. Whether we are looking for a more senior person than today or a less senior person than today.

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Fanni   10:09

What would be the efficiency gain on the toll role level? To what extent generative AI is impacting that role? Is it more than 20%, or is it within that 20% scope, that magic 20% that HR leaders usually use? As a rule of thumb, if it's below, then you don't need to recontract. For example, So. And then, of course, we would do a summary summarization on the organizational level, which would give us an indication to upskilling priorities on the organization level.

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Fanni   10:47

Also the impact on diversity, for example. That's, I think, a very interesting thing that has not been addressed widely. There has been a great study from ILO, the international labor Organization, I think, last year, and they were researching the impact on the society level. I'm not able to say this right in english society, impact of generative AI. And they have said that since. Those roles are going to be impacted mostly by automation that are, let's say, highly routine and repetitive and data driven, the so called clerical roles where women in general are overrepresented. So on the society level, women are gonna be hit hard, not again, but by AI and automation.

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Fanni   11:47

Exactly. And, and that's true for the organizational. Can be true on the organizational level as well. And what does the company do with that? And by the way, what does the company do with the overall efficiency gain? Because I think it's a strategical, HR strategic question, how do we want to position ourselves as an employer? What is the safety net that we are providing to our employees?

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Fanni   12:16

What is the upskilling that we are providing to our employees? It should not only be a money question, and this is where HR, it's not only an opportunity for HR, but it's a responsibility to HR to get a grip around this AI hype and really start moving, getting out there and becoming part of these discussions, because there are very heavy questions that need to be decided. I'm not going into details with how you are going to measure performance? What do you do with the pay compression that may arise? Simply due to the fact that more junior people will be able to do more senior tasks with the help of AI. So that's going to result in pay compression unless you're going to pay after seniority, which is a big no no in compensation. Right.

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Fanni   13:11

So today we are saying in compensation as a rule of thumb, don't pay after seniority because you know you have to pay the value of the job, of the task. But what will be the value of the job? Well, you've raised so.

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Helena  13:28

Many things I want to ask you questions on now. And my next question was going to be the motivation, like the primary motivation that you're seeing out there for applying this framework that you've built. Right. So what are you seeing that is driving organizations to want to answer this question? Because I would hazard, I guess it's not all driven by a social responsibility to the workforce. What are you seeing out there?

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Fanni  13:54

Yeah, well, from a boardroom perspective, as I said, it's in every boardroom. I'm 100% sure that there's not one CEO on earth today that is not talking about AI and how AI could, and not considering whether to invest in AI now or wait a little bit. And what are the pros and cons, what is the efficiency gain? So I'm 100% sure it's in every boardroom. Whether the HR is in that same boardroom, that's a question, of course. So why go down that route? I think, first of all, it's top of mind for every company.

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Fanni   14:38

Second, it's definitely a competitive edge, and whoever figures it out first. Will win as a business and win as an employer because there is so much research out there. So starting from the one I really like is the Microsoft Word Trend Index report, which has been published a couple of weeks ago. And they researched 33,000 employees throughout the world and found that more than 40, I think it was 54%. So the majority of people would prefer an employer where AI is allowed, and it's supported not only as a tool, but also as an upskilling opportunity. So it became part of the EVP. It's a must.

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Fanni   15:34

You need to do something with it. Second, that also came from the Microsoft Word Trend index report, and this is a freaky, freaky statistics in my opinion. But 75% of the 33,000 employees studied said that they use. Their own AI. So a non company AI tool for their work.

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Helena  16:03

BYO AIi it's called, isn't it?

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Fanni   16:06

Exactly. Bring your own AI. Exactly. And that's. That's one thing. The other thing is that 50% of these people are too afraid to admit that they are using it for their work, which is. Oh, my God.

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Fanni   16:22

I mean, think of the potential data security issue it poses. Second, it completely kills the psychological safety at work. It's called, by the way, we used to call it the Tiebridge AI anxiety. Now it's called Phobo, the fear of becoming obsolete. Yeah. Fobo and I think it's such a huge red flag. It should be such a huge red flag for HR teams because it's killing psychological safety, it's killing trust, it's killing productivity plus, it's such a huge leakage in terms of data, security, privacy, ethics, and you name it.

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Fanni   17:11

So it's there. You have to get a grip around it because people are using it. People want employers to allow them to work with AI and figure it out. There's another study I want to call into our discussion is a McKinsey study that came out a couple of weeks ago, and they were talking about. What is AI talent? If you ask people what AI talent is? I think the majority will say it's technical skill.

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Fanni   17:43

It comes up to a technical skill. Whether you're able to prompt the chatGPT, well, whether you're able to build the chatbot, whichever. And it's absolutely not true. So the AI talent is the people who are able to figure out the most important use cases within their role, within their work, everyday work, and are able to use AI effectively because. Efficiency or productivity opportunity does not equal productivity. There has been this Harvard Business school experience with Boston consulting. I'm sure you heard of that, where they did it last year, I think.

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Fanni   18:30

And they were measuring the efficiency and productivity gain driven by AI, generative AI, and they found that for tasks which were routine, repetitive, data driven, well structured AI not only produced more within less time or with the help of AI, these teams produced more within less time, but also of higher quality. But for tasks not like that. So where creativity, interaction, complex thinking, and strategic thinking were more important, the output was much, much, much worse, so that the num, the quantity of the output was higher, but the quality of the output deteriorated. So, as I said, productivity opportunities do not equal productivity. So you need to figure that out, too. And one more thing from the McKinsey study that they said that they were studying these so-called AI talents.

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Fanni   19:38

What would be, because what you see on LinkedIn and in every job posting is that these types of skills are so hot today on the job market that basically the price of these skills is going up exponentially. What McKinsey is saying, that the most important retention factor for these AI talents is absolutely not compensation. We all know compensation is binary. If you screw it up, people will leave. If you do it well, it's not a guarantee that people will stay. That's true for AI talent as well. So the most important thing, how you are able to give them a meaningful job.

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Fanni   20:23

And that's, I think it's a big, big. Should be a big top of mind for every team to rethink how we are providing added value as humans. And how do you measure the added human value once you use the machine? So generative AI tools.

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Helena  20:47

And we were talking before we started recording as well about a recent use case going back to the sort of motives and drivers. The Klarna chief executive who made the news, he's made the news a couple of times in the last two months. Firstly, talking about the avoidance of needing to hire. I think it was 700 people in his contact centre thanks to the use of AI. So they'd automated the. Create an amazing conversational AI to be able to deal with first line customer service tasks. And then the second announcement that came onto their website this week was about how they'd been able to reduce their marketing headcount by something like 25%, but significantly increase the output.

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Helena  21:28

Why do you think. And he got berated for this, right. It really triggered people. And this is the Phobo you talked about, it really triggered, I think, people's fear about irrelevance. Why do you think that triggered that kind of immune response? Because it's surely the responsibility of the CEO to reduce costs, increase productivity, increase shareholder value. What do you think about that?

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Fanni   21:59

Well, nothing. So let's start. Let's take a step back. So I think it's quite obvious that due to geopolitical insecurity, the post pandemic era, the productivity pressure on companies is huge, not only because of the disrupted supply chains, but really, it's a huge productivity pressure on every budget, also on the HR budget, by the way. So basically. Inflation was driving that, etcetera. So being able to become more productive is very compelling to every CEO and CFO.

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Fanni   22:47

Plus, there are so many uncertainties, not only about AI, but in terms of sustainability, in terms of geopolitical pressures, in terms of the many elections that are going on throughout the world that, being able to run more productively is super compelling. It's more compelling than ever. That's one thing. The second, as an employer, I think what we discussed prior to the recording is you have the responsibility to provide some kind of a safety net to your employees. What kind of a safety net? That's up to you to decide.

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Fanni   23:34

That should be part of your employer brand. And as, for example, we talked about the quote, how you need to renegotiate the operational contract with your employers.

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Helena  23:49

Psychological, right? We talked about the psychological contract.

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Fanni   23:52

Yeah, exactly. It's how, for example, during the pandemic, people didn't lose their jobs. They were allowed to work from home. It's a very similar discussion today. How do you want to position yourself as an employer for this transitional period? And transitional is another, I think, key factor in this discussion that I usually say that it's like storming, norming, forming, performing phases of every change management. And we are in the storming phase. So there are so many things.

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Fanni   24:33

There's such a big hype and, and you shouldn't overreact to either extent. However, I think being overprotective is also not a very good approach. Yesterday I saw Max Bloomberg posting about that on LinkedIn, and I really like that. The other extreme that I'm seeing within HR teams or companies that they say, oh yeah, I will not take your job. It's just a tool. It's going to make you more effective. It's augmentation, not automation.

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Fanni   25:10

Let's not mix the two and blah, blah, blah. But that's really bullshit, to be honest. That's not true. It's going to take many jobs for sure. We don't know how many. We don't know which jobs. But we need to start this discussion and be open about it.

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Fanni   25:28

That you need to upskill. You need to take ownership of your own job security. We're going to secure your job to some extent, but for that, and that's the operational contract that needs to be renegotiated. In order for you to be able to keep your job, you need to upskill. Reskilling is something that should be top of mind for everyone today. So it's not a happy Friday or learning Friday. I'm happy every day or learning every day because the information is coming out so rapidly that it's hard to keep up.

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Fanni   26:08

But this is where who will stay on the bus and who will need to get off is going to be the deciding factor. I don't know if you have seen the movie hidden figures.

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Helena  26:19

I have. I love it. It's one of my favorites.

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Fanni   26:22

Me too. I love it. And there's a part when. Is showing the team the new IBM 7360 data processing machine. Huge. Yeah, exactly. In the mainframe.

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Fanni   26:37

And then she says it's capable of doing 24,000 multiplications per second. And then the team, the mathematician. Yeah, exactly. Who are doing the computing, they are saying, holy Moses, that's a lot. That's lightning fast. We're never going to make it work. What she says is important.

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Fanni   26:59

Well, it will run eventually, and when it does, we have to know how to program it. Unless you better be out of the job. And then the team says, no, no, no, I don't want to be out of the job. So I think that's the go do for everyone today. That upskilling should be your top priority. And where HR or companies need to help people is to provide them with upskilling or reskilling opportunities. And in the storming phase, you know, doing a heavy downsizing, you know, it's your call, but a responsible employer might wait a little bit with the heavy downsizing and, you know, see who is able to really upskill and who is able to reskill himself.

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Fanni   27:49

And let's see how the new value added jobs will look like. So.

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Helena  27:54

Here's the perfect storm, though, right? The cost of capital has increased, inflation's increased, productivity's decreased, and then suddenly enter chatGPT it's like the perfect storm of any moment in the world. It could happen. I think it kind of proliferating so rapidly in the last twelve months. It's like a bit of a gift, I suppose, to CEO's, but it is, I think, the perfect storm of automation. And I guess to some degree. Offshoring may have been the precursor to this.

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Helena  28:25

Right? So you take repetitive tasks, you sort of centralize them. You move them to a lower cost market. Let's say it's kind of the precursor to alteration maybe. One of the things that scares me about this is the impact on entry level jobs where those foundational skills are built. Now I don't know about you, but my first, some of my first jobs were like waitressing and I worked in this British retail store, you know, like in my hometown where I had rude customers and all of those kinds of things. And, you know, if the contact center is now automated and, you know, we buy everything online, like, what happens to young people's ability to just gain foundational skills and experiences that will set them up for, you know, the possibilities?

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Helena  29:13

I mean, I don't know if you have an opinion on that, but that's one of the things I think that scares me about the future of work.

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Fanni   29:19

Really, for me, it's the other way around. I think for young people, it's a great opportunity simply because I don't think that the productivity gain will be the highest driven by downsizing, but downgrading. Exactly. So I think there will be much more opportunity to enter the job market and create more value with less skills. McKinsey, another McKinsey study was, or not Stanford study was about that, that it's even measurable today. And I hear from clients as well that they are downgrading many roles where AI could be used efficiently. So I think for them, it's a great opportunity to, let's say, to pursue more responsibility, responsible tasks earlier.

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Fanni   30:23

My fear is rather on the older and more senior, less flexible generation and more senior in terms of experience, because part of the value of their seniority will be automated like this by ChatPt, and they would need to, you know, upskill. Very rapidly, which they might or might not be able to do. So I think for younger generations, the big question mark, I agree with you, is how it impacts the career tracks. So how is it? So that's great that they are able to enter rapidly into a more responsible role on the entry level. But how are they going to proceed? But I think that's up to the future to decide.

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Fanni   31:19

But I'm more, let's say, concerned about our age generation who are far from being retired and have quite a big seniority, like 20 years in the labor market. That's something. And part of these 20 years can be made obsolete like this by ChatGPT.

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Helena  31:44

Cordine in our team has a theory about this as well. And her hypothesis is that in some companies, some of these leaders are the blockers to things like AI adoption or tool adoption because suddenly their irrelevance is accelerated. Right. And her hypothesis is that there are sort of senior people making very self protective decisions? It's all anecdotal. Right? But you can imagine your empire being eroded overnight because imagine in your own role, right, in your past role in a senior finance role suddenly being, having half of your team automated.

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Helena  32:22

It's not going to have an insurmountable impact on your ego as well.

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Fanni   32:26

Yeah, I agree that this might be the fear of the unknown. It's always there and it's big, let's say. Blocker in every sense. It's a big blocker in people analytics for HR because it's independent from AI, but going down the data route, it's very similar as marketing did a couple of years ago. Who cares about CEO SEO analytics? And that's bullshit. Let's be creative and that's our most important task.

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Fanni   33:05

And boom, it changed like from one day to another. This will happen with HR as well, by the way, but they look at it today as an exotic animal. So it's like, oh, nice. But no, no, it might bite.

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Helena  33:19

It might bite. It's true. It really might bite because there's some other research coming out looking at the risk of automation to the HR profession. So it's kind of ready to bite us by the looks of things. Maybe I would love to ask you now some of your predictions or maybe hopes, let's say so on the optimistic side, what are your predictions and hopes? And then we'll maybe go to the more pessimistic side in just a second.

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Fanni   33:43

Yeah. Well, first of all, I'm fascinated by technology. So one of my high hopes is that it will help to solve so many problems of humanity faster, starting from the climate issues to healthcare. My mom, unfortunately, suffers from cancer, and unfortunately, I don't think she's going to be able to. Harness the benefits of AI for her curing. But, for example, when she was diagnosed in Hungary, there's a company who's doing AI based diagnostics using the tumor cells. So they are diagnosing the genetics of the tumor cells and using AI, connecting the global, all the global experiments that are going on, all the globally available cures and medications and chemos, generating a totally personalized cure profile for her using AI.

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Fanni   35:05

I think that's just like ground zero for healthcare. So, first of all, I'm very, very optimistic. I have always said. To some extent. I used to have some climate anxiety, especially when I was having the kids. I was like, oh my God, is it responsible to have three kids with this terrible outlook in terms of climate change and climate catastrophe? And I always said that, you know, it's people, we are not going to solve it because we are.

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Fanni   35:42

The basic motivation for people is simply different and it's so egoistic and we would need to collaborate and it's not going to work. I mean, it's got that the situation is going to be so severe when collaboration will be a better option that it's the point of no return.

There's only one thing that can save us from becoming dinosaurs is technology. So I'm 100% sure that it's going to be a technical invention and a technical leap forward that will save the world and humanity. So that's on the optimistic side, but let's not be so visionary on the company level. I think the biggest benefit is really to get rid of the routine and these **** jobs, totally boring, ****** things that need to be done. At least for me, those are absolutely non motivational.

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Fanni   36:46

And so I have a slight adhd and for me having to do this kind of stuff is like, okay, tomorrow maybe, but I'm always trying to get rid of this kind of stuff, so that's great. So for me that's a fantastic opportunity. The other as it frees up time and if the employers are responsible, it might open the opportunity to give back time because people are so much under time pressure and having to juggle with 10,000 tasks at a time. And, you know, it's not necessarily the four day workweek because that might not be the holy grail. But the work flexibility or how I am using my time because I wouldn't care if Friday was off probably I would be working Fridays but being able to work until 02:00 every day and not later or being able to take ownership of my time schedule to let's say 30% at least because 70% I'm doing interactive staff so I'm dependent on others. That would be absolutely super. Plus in every change there is the opportunity to come out better as it was.

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Fanni   38:12

So if we figure out how this would be and it's up to every individual I think how it can make my life easier, my life better, my work better, then it must be better. So it's like there's no other option that's on me. That's me on the optimistic side. I have the pessimistic side as well so I'm a realist so to say more on the optimistic. But I know that many people will lose their jobs and. And it's gonna be hard for the older generation, as I said, because we're older. I don't like to call myself old, but, you know, our generation.

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Fanni   38:54

So those that have been younger for longer, so for some people, it's gonna be a challenge, and it's gonna take more time, so to say, because there are always the early adopters and the laggards and that those that are laggards. Are not going to have a job for a certain period. I'm sure as laggards they're going to catch up, but there are some, let's say, more challenging years to come for them. So I advise everyone to, if it's a choice and if it's not very, if it can be made conscious and it's not an unconscious motivation, then try to be an early adopter and try to, you know, tackle your fears and start going down the unknown route, because if you stay with all the known, the risks of losing your job is much higher. So it's. So that's pessimistic. And I think the other pessimism is what you said about this, Klorina, that many companies will a little bit overreacted, the productivity gain in this storming phase without, you know, waiting.

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Fanni   40:20

I'm not saying you should wait a lot, but, you know, taking such heavy downsizing decisions, I might be a little bit afraid to do so.

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Helena  40:30

Well, there'll be no one left to buy now, pay later for Klarna if they do, you know, if every CEO took that.

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Fanni   40:36 

Yeah, exactly.

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Helena  40:37

So maybe to sort of come towards the end. Obviously, organisations like Go figure and Highbridge Consulting are here to help and here to advise. So if anyone watching this would like to reach out to you, would like to find more about the work that you do. How can they connect with.

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Fanni   40:57

On LinkedIn. I'm always available. I love to chat, and I'm usually active in chats over LinkedIn as well. So on LinkedIn, everybody can find me, drop me an email and I'm super happy to chat. I think when we chat, many things are getting clearer. So even if you think that you have a very strong opinion about something, when you put it into a discussion, more questions and more perspectives are going to come out of it and it helps everyone.

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Fanni   41:36 

I think so.

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Helena  41:37

Fantastic. Well, I thoroughly enjoyed this conversation. Let's do it again. And thank you so much for joining me.

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Fanni   41:45

Thank you. Thank you, Helena.

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