Getting to grips with workplace AI
This is the second episode this month about AI and the implications for our jobs.
Two weeks ago I went along to a huge event run by Workday down in North Greenwich. Workday, their partners and customers took to the stage to talk about applications of AI that are coming to their platform. As part of the event I was able to run a discussion with a couple of voices from the company who are helping businesses navigate the challenges that AI presents to us.
I was joined by Jerry Ting. Jerry is the founder of Evisort and now teaches at Harvard Law School and is a senior leader at Workday. And the other contributor was Angelique de Vries Schipperijn, she’s the EMEA president for Workday. The conversation was fascinating for me in a few ways, firstly we can be so daunted about what AI represents in our jobs and this seemed simple and easy to understand, but secondly because as I mentioned last week the conversations I got from the audience suggested that there’s a lot of businesses who have barely started their own journeys.
Here’s the challenge of the moment, I think the conversation at the event described a future that we have the agency to participate in. It seems real and like something we can connect with, but also everyone who came up to me afterwards anxiously told me that their organisations are doing nothing at all. That’s why I got so much value from this conversation. I think inverted commas “doing AI” feels scary and huge whereas incorporating it into some of the things we’re already going feels possible and easily achievable.
I need to declare that this is a promoted episode in the sense that Workday is a client that I was working with at this event and have worked with before, but critically it was a conversation that I’m delighted to be sharing here.
I want to give a shout out to Hollie Benneyworth at Workday who has worked so hard to make this happen.
You can find a full transcript below.
Transcript
Bruce Daisley (00:00)
Hello. I’m Bruce Daisley. This is Eat Sleep Work Repeat. We’re recording a live episode of a podcast here today. The podcast is about making work better. And so hopefully it’s in the spirit of the event that we find ourselves at today, which is Workday’s Elevate event, Elevate London. The Elevate event brings together leaders who are weighing up changes that lie ahead in the next few years. And obviously right now there’s no shortage of complications and complexity to the way that work is looking. And so to navigate some of those themes.
I’m joined by a couple of members of the Workday team who are going to help us answer some of those big themes and questions. I’m joined by Jerry, Jerry Ting. And Jerry is the founder of Evisort and now works at Workday. And I’m joined by Angelique de Vries Schipperijn. OK. Well done. And she’s the EMEA president for Workday. So welcome to both. Thank you for joining us. I wonder if you could…
Just as we get going really, I wonder if you could maybe just give us a touch more detail of what you both do inside the organization. It sort of helps conceptualize maybe some of the themes that you’ll be drawing on today. Jerry, do want to kick off?
Jerry Ting (01:10)
Yeah, so I started a company called Evisort, which is AI for contracts. I was in law school reading contracts, did not like the manual work of doing that, and thought about using AI in 2016 to try to make that work a little bit more efficient. As of last week, I actually have a new role at Workday. So in addition to running Evisort’s business, I also lead all of the agentic AI development efforts. And so excited to be here.
Angelique (01:31)
Yeah, and you mentioned my last name, that’s Schipperijn. That’s a Dutch name, so you can hear on my accent that’s typical Dutch name. So I use my husband’s name, which is De Vries. That’s easier internationally. But I’m the EMEA president and it’s a real pleasure to be here.
Bruce Daisley (01:47)
Now, I spend my time thinking about workplace culture and thinking about the layer of humanity that exists within businesses. And I guess the interesting complexity and complication of today is that we’re talking about technology. And it sort begs that question then of, as we go forwards, will the layer of technology be more important for business success or will it remain the human element? And really, that’s the theme I’m quite keen to explore. I want to break down today’s conversation into maybe three blocks, three themes. The AI shockwave, I’ve sort of given it a bit click-baity introductory title, the leadership shift and then leaning into that final change which is the human differentiator and to start off then to think about that AI shockwave. I’d love to, maybe Angelique you could give us a theme, I’d love to kick off thinking big picture, thinking about where we’re going. If you broke the the future ahead of us into sort of a five year block. How disruptive do you think the next five years is going to be in the way we do business, the way work is configured? Is this going to be as big as the last five years have been or bigger? How do you see it?
Angelique (02:54)
It’s a big question, but I think if I take it back, AI will be everywhere, is everywhere, and I think it will impact everybody’s lives and everybody’s work. there is a lot going on also from technology events. was watching yesterday the Google event and Microsoft Build, Salesforce, and also our events. And I think we all come to the common understanding that we all believe that this is an incredible tectonic event which will be bigger than ever and what we’ve seen before. And if you ask me what’s the next five years, I think we will learn a lot. We will experience a lot and it will drive constant change and curiosity a lot. But I have to say, Jerry, you started in the AI, so most probably you experienced already the last five years, real life, and as you are leading the whole agentic drive within Workday, most probably you have a perspective here as well.
Jerry Ting (03:50)
I think life is going to change very fundamentally. I think it’s going to change in a good way. The analogy that I’ll use is the Industrial Revolution. We used to have the right horses and now we have cars. When I talk to venture capitalists, I also teach at Harvard Innovation and I talk to faculty members. This is bigger than the smartphone. This is bigger than the internet. Everything that’s happened in the last 20 years brought us to this point, which is compute, which is the internet and connectivity, which is the smartphone, the computers, all of that combined led us to now where machines can actually start to think like humans and not just think like humans, it can actually teach us. So I just finished teaching my course at Harvard actually and I was talking to some of the students and one of them said, I think the one area where AI will not change is actually education. And I said, thank you for saying that because I’m an educator. And I said, but can I challenge you to think about that a little further? For me, I’m learning how to do some stock trading.
It’s a hobby I picked on on the side. I’m a little bit nervous to ask my friends how does an ETF actually work, but I’m not scared to ask GPT. And if I ask a question to GPT, I’m not shy about that. I can ask follow-up questions. It’s a more engaging way to learn. So even education is going to be changed. I think if you think about the next five years, that kind of impact is going to be from driving cars by themselves to not having to do all the manual steps of payroll to how we work with our family and friends. All of that’s going to change.
Angelique (05:10)
And maybe Bruce, just to add to that, I think we are seeing an incredible tectonic shift. But then in addition to the tectonic shift, it’s about the adoption, right? What are we going to do with it? How are we going to work with it as individuals, as businesses? So it’s the technology and it’s the adoption, I would say.
Bruce Daisley (05:26)
That’s really helpful. Quite often when we’re hearing, you gave these examples of these big conferences that we watch, self-generating video. We watch all of this stuff and it’s actually dazzling, it’s overwhelming to stay in touch with. And the buzz, I think, has become… something that right now is leaving a few people overwhelmed and cold. I’d love to get into some of the specifics. Then in the last 12 months, there some direct specific elements of AI that you’ve seen have impacted work? You talked about your product in the introduction downstairs, and maybe I’d love to delve into some of the specifics of the way that AI is already impacting, aside from the buzz of what’s to come.
Jerry Ting (06:06)
So this is where I think reality really matters. Because it’s easy for us on the podcast to say AI is going to change the world. I mean, you can listen to any podcast and they’ll say that. I’ll try to give some concrete facts. So we’re working with one of the largest banks in the world. And they have a large legal and compliance department. And year on year, because of the regulatory framework, they have a 40 % increase of the need to review policy documents and contracts. Huge compliance burden, internationally and domestically.
By using, they reduced their outside legal spend by about 70 % in one year. And by using Evisort, they were able to turn around a contract that was being negotiated in a sales context, actually. They were able to turn that around 65 % faster. That’s actually, that’s reality and that’s in production. There’s a lot of vendors out there that will talk about AI as though some magical fairy dust. But if you ask their customers, what have you actually done? There’s still an implementation or even worse than that. I think for AI to be real, you have to be transparent. You also have to drive real impact and quickly. It can’t take years.
Bruce Daisley (07:03)
Does that mean it’s already proving to be differentiated between businesses, the businesses that maybe are too busy to get down to actually implementing things and the ones who are like, okay, we’re setting aside a certain group of people or a certain amount of time to bring these things into reality right now. I’ve met no shortage of leaders who say, we’re not really doing much stuff just yet because we’re sort of busy with the day-to-day work. And I just wonder, is it already proving to be a differentiator?
Angelique (07:30)
Yeah, so maybe I can give some insight on what I’m seeing in maybe in EMEA specifically, but also I had talking with a lot of our customers. if we talk about change, it’s scary, right? But I think we also recognize there is so much going on if a business stands still, that’s never a thing, right? So businesses are always used to constantly evolve and look at ways about what do you do and how can you do smarter, more efficient where should you focus on and prioritize? And then if we look at some of the data points, so from a Workday perspective, we always talk about the 3x innovation, meaning from a Workday perspective, we innovate and we constantly help our solutions to get better, smarter, where AI and agentic AI plays a big part. Also, our customers innovate on and with our platform and we have our in the wide sense of the word. So also customers can be partners, system integrators, technology partners, it’s a wide sense of the word. They also build and drive new innovations. Then if we really look at the adoption, to your point, it’s interesting to see that already 50 % of our customers are using AI capabilities. And sometimes, most of the times they use the AI capabilities. capabilities which are embedded natively in our solution and they build on that. So to give you an example, Sanofi, maybe that’s an interesting example, Sanofi pharmaceutical company in France. They are an incredible fast moving research and development is an always changing business for them as a pharmaceutical company. So for them, it’s always do we have to write talents and how can how can we really grow our talents as a community in the company? So they are using our skills framework, skills cloud, and they call it their internal Tinder. I thought it was a funny name. But I think it says a lot, right? So they are matching skills to positions and they already are matching more than 8,000, approximately 8,000 positions with their, let’s say, career hub. or career marketplace, their internal Tinder, because it’s a big topic.
Bruce Daisley (09:41)
So this is internal, people already working there, having skills that’s greater than…
Angelique (09:46)
Skills and Sanofi is always a fast moving company as well. They need to invent new drugs and bring to market, etc. So they constantly evolve as a company. And that on scale, they are a global company, so matching the right skills to positions, open positions, new positions, is a big topic for them.
Bruce Daisley (10:06)
Okay, so that’s quite helpful to understand. in a context where we keep hearing all the time that, yeah, there’s going to be a reduction in the size of certain organisation or we’re losing jobs somewhere else, what you’re potentially saying is this could be some way to realise that we’ve already got the talent inside the organisation but we just need to redeploy them somewhere
Angelique (10:23)
And talent is big topic also. I talk with CH Rose, it is about constantly upskilling our talents, right? Because it constantly moves. and many companies have incredible talents. So, working with the talents and upskilling those talents is a key focus area for many companies. And that’s where you hear skill-based organizations. Also, how we do a lot of analysis about
What do we see in the market? And already 50 % of the companies say we move to a skills-based organization. So is work ourselves, right? So also for us, we move into a skills-based organization because now we see ourselves, the whole focus on AI and agentic AI. We also need to have that curious mindset and leveraging our talents to really lead the way forward. So skills-based is a big topic.
Bruce Daisley (11:18)
We keep hearing the phrase, agentic. But how are you thinking about agentic when it comes to the day to day uses of Workday products or other AI products? How should we explain this to our boss or our colleagues?
Jerry Ting (11:30)
So I’ll give two examples, one in HR and one in CFO. In the HR world, we’re building an agent that allows users to ask questions about their policy documents without having to go and ping somebody. And so I would be a user of something like this because I’m not good at reading policy documents. I literally started a company so I don’t have to read. So I’m a user of this kind of thing. So I’m expecting a child. I can go into Workday in the future, very near future, and you can ask a question of, for me in France, what is my Parental Leave policy, have I been here six and a half years? And is that different than if I was here six years? That kind of family planning on a policy document, that’s every user of every employee base. So that’s one example where you don’t have to talk to a human. Another one is on the audit side. On the CFO side, audit is a really big challenge because when we WorkDay acquired Evisort, we had to go through an audit of sorts where we got 300 questions of give me every customer contract of X shape and size. Well, we have people literally to go out finding documents. In this use case, Workday’s audit agent can actually go and find these documents and bring it back for the humans to review. So when we talk about skills, these are skills that the agents are actually doing. And it’s usually the parts of jobs that people don’t want to do. And so for me, never having to go through an audit again by looking for documents is a great thing.
Angelique (12:45)
And maybe just to build on. the way we look at it is, what’s the definition of agents, right? So the way we look at it from a Workday perspective as well is that it’s not one single task, but it could be part of a role or it could be a role, right? So multiple tasks where you really connect different processes where I think the beauty from a Workday perspective and that’s why we are super excited is that we were born in the clouds, which means that it’s a very clean day, source with a number of data. So high quality of data and high number of data, which gives a very clean basis to say, let’s leverage that data, but put it in the business context, right? And then take a human centric approach to help with the agentic AI to help the human. And the day before yesterday, both you and myself were in Amsterdam, also for Elevate. And we had an interesting lunch with McKinsey as well, where they
They also said the future will be agents talking with agents. And Microsoft in the Microsoft Build event yesterday evening, it was, I believe, they showed also the Workday. We were very proud of the Workday agents talking with some of the agents Microsoft is doing. So the agent to agents with a human-centered approach, meaning to help everybody in their role, where they are in the business process, that is, I think, extremely exciting opportunity to help upleveling all our personal roles and tasks.
Bruce Daisley (14:19)
Whenever people are feeling fearful about what’s happening in the changes coming, a couple of things they go to, they talk about hallucinations and they talk about confidentiality, that maybe our data feeds some wider model. How do you think about those things with when we got to contract or proprietary information that sits inside something like the Workday system?
Jerry Ting (14:37)
Maybe I’ll start. I was talking to a customer. You and I are both very customer-centric, which is great. I was talking to a customer, and they’re saying, I’m so glad Workday is now taking AI very seriously. Because up until this point, our IT department was using a off-the-shelf third-party model and trying to access Workday data. And they’re not HR professionals. They’re not security experts. They were just trying to accomplish a task. And so I think that’s where the risk is, is if you’re having people that are doing this outside in, or even employees going off with a corporate credit card and buying a third-party license, that self-help is going to happen because of the excitement around agents. How does an IT department and the HR department and the finance department actually take the hill, so to speak, and provide the tools that the next generation of workers are going to demand? My students are going to demand that they have these tools. From a centralized perspective of work, they can provide that. It’s more safe, it’s more secure. We have access to the roles and the policies of which these agents are working in. That’s a better approach than a self-help, free-for-all kind of approach.
Angelique (15:36)
Yeah, and if I take a step back, so Workday was born in the cloud, right? 20 years ago, we are celebrating our 20th anniversary this year, and everything started with, let’s say, trust, security, data safety in mind always. So we were born with that as a key pillar of how we started, and that’s still an extremely important pillar for us going forward. So we talk about responsible AI.
And we have a very advanced process and framework in place to make sure that data usage is safe, but also transparent, right? Because we just touched upon hallucinations. So that also means that the data model should be very transparent about which data is used, where, by who, et cetera. So we see that security responsibility is also traveling with and it’s highly embedded in everything we do and everything we drive forward.
Jerry Ting (16:34)
And I can actually attest to that. So I come from a different environment. I come from a startup environment where you think about the innovation first and then you think about how to build it. It has been an adjustment for me to come to Workday to work in that security first mindset that comes from an HCM background. But we’re not playing for the next two quarters. We’re playing for the next 20 years. And so for us, if we want to work with Fortune 500 companies and global companies and EMEA and APJ, those security standards are critical. And so I think that’s where the fact that Workday is born in the cloud, I still have access to the right data with the right security privileges, but also in a compliant way. So it really has been a great merging of two cultures.
Bruce Daisley (17:11)
Now this is a leadership event and the people in the room are leaders. I just want to sort of move on and talk about what the implications for all of this change in technology is going to have on the way that we do our jobs and the way that we lead to teams. I’ve seen Microsoft have published data and they said, look, we’re going to have to move in the future from thinking about org charts and about sort of pyramids of hierarchy into workflows. We need to think more specifically about short term projects.
How do you think about how work is going to look specifically different? What are the differences that working week might have to it in five years or two years that we’re not necessarily able to tangibly feel right now?
Angelique (17:52)
Yeah, it will be a very exciting journey. And the way we look at it is that we always will have people, humans, right? But we also will have agents who will be part of our workforce and do specific parts of the business helping the humans. So we are thinking in a way that we call it the agent system of record that we think there is a role to play for us in managing people, but also managing agents. Agents also need to be embroidered
Agents also need to be tested and checked on security and safety and biased. They also need to have a kind of continuous learning process. So we look at ourselves as playing a role for people, also money and all financial management, but also agents. So people, finance or money and agents. And I think this is a very interesting one. McKinsey was talking about two days ago about a new workforce where it is about people and agents and as leaders, because also your question is about what does it mean for leaders, there will be very important human skills like for example the curious mindset, the constant learning which will be even more important. think culture and managing a company is not only about data and processes but it’s also who are you, what’s your purpose?
What’s the culture in the company? That always will be where we as humans will be strong in. And then building networks of people. So there will be very strong leadership skills, mainly important in areas like continuous learning, people networks, culture, et cetera. And I think we will learn a lot there about how this will evolve. don’t know how you look.
Jerry Ting (19:38)
maybe I’m coming from too futuristic of a mindset, but I don’t know why work trucks existed in the first place because it should have been about doing the job and then how do you put the team together to do that job, right? So outcome driven. I think if you take that mindset of, if I want to go take a lead from a sales perspective, from marketing lead handoff to salesperson, that entire process I think should be done by an agent because it’s a very manual process and there’s a lot of rooting, there’s a lot of rules, there’s a lot of policies. What does that do if an agent does that?
the salesperson to actually have good customer conversations human to human? Isn’t that better world than the salesperson having to find the lead? So I think org charts are a thing of really a legacy mindset. It’s more about what is the job to get done and then how do we put together the right people, process, and technology that framework still applies.
Bruce Daisley (20:25)
So to some extent you’re talking there about removing layers of management because that layer of management won’t be needed. People will have more agency to do a specific job and they won’t need the supervision. That’s almost what I’m reading into what you’re saying there.
Jerry Ting (20:37)
I think you’re seeing that in a lot of large organizations where organizations are flattering because there’s more empowerment of the employees. If you set it clear to your point, what’s our purpose? What’s our North Star? What are our key priorities? You don’t need many, many layers of management. Then you have more alignment for the individual employee.
Bruce Daisley (20:53)
When we had the briefing call for this, you said something that really intrigued me. said, Jerry, said that in the future, we’ll never do this call. Our agents will do this call for us. firstly, I’d love you to explain what that means. But Pote is a really interesting question. If we are that predictable, are we not superfluous? If we didn’t need to do a briefing call because it was so self-evident from everything else that we’ve created, the agent could write that outline for us, then surely we’re unnecessary. I’d love you to sort of unpack that whole comment because it really caught my imagination. No, at all. ⁓
Jerry Ting (21:25)
Hopefully it wasn’t offensive. My purpose in that is we were coming up with a framework for this podcast and it was here’s the topics and here’s what we should discuss in the topics. I appreciated that preparation, but GPT can do that in like less than six seconds. I think what we need to figure out as a society is what are the tasks that agents are better at? So, and then what are the tasks that humans are better at? And we’re not following the framework. We’re having a conversation right now. This is, this is not going to be replaced by agents. A human to human… thought process about culture and emotion and us bouncing ideas off each other. This is the valuable part of it. The script is not valuable.
Angelique (22:04)
And it can be helped with the data coming from agents and insight. That’s what you’re saying, right? So I think we will up-level the type of thinking, the type of conversation. So yeah, if I look at my personal life, and I’m not native English as you can hear, so I have a lot of help from Gemini and JetGPT to make that better, to be honest, right? It’s helping me.
Bruce Daisley (22:25)
It raises a really interesting question. If the AI becomes the most knowledgeable being thing in the room, then what’s the point of a leader? What value is a leader offering? It sort of begs a really interesting question about how any of us as leaders can prepare for the future if AI is going to give us an objective answer to any question.
Angelique (22:43)
Yeah, so a couple of things and I’m just thinking out loud. So as a leader, right, I think it’s very important that we also have a curious mindset and an effort learning. So what can it do to us? How can we help with setting a strategy in a direction, right? how, like Jerry is saying, part of the work, it’s also understanding the analysis, right? AI can help tremendously to give me the insight I need and then take the insight to say, maybe I can do here a bit better or maybe can can be focusing there a bit better and then work with the teams. The emotional intelligence is us as leaders. think that will be very important and also connecting the teams but then also leveraging the technology so that it can us as humans and as leaders. So we can free up some part of our work to focus there.
Bruce Daisley (23:33)
It begs a really interesting question, and let’s come on to that notion of the human differentiation, like how we humans play a difference. And I guess one of the things that have seen a discussion of is that increasingly in the future, the leader will have to see themselves as the chief energy creator, the person who knows how to mobilize a team, knows how to say the right things to excite people. And…
Can you see any sense of that? Do you see you’re a very senior leader yourself, Angelique. Do you see a sense that that could be the thing that you really lean into,
Angelique (24:04)
I think that will be one of the elements. So connecting with people always will be important in organizations. So do we all understand? Can we mobilize ourselves? Are we energized? Is the purpose right? Do we feel motivated? That’s emotions. And I think this is super, super important for us as leaders and for us as people to feel that connection, call it purpose, call it culture. But I think that is the emotionally intelligent part will be even more important. I think it’s already an important part of leadership, but I think it will be even more important. And then I also think there will be a very important part as leaders to have a curious, open mindset. So when I listen to Jerry, I think, okay, it will be very interesting to see which part of my role can I leverage agents more than I do today, right? So that constant learning, constant adoption, piloting innovations to help the company. Companies to move forward. think it’s fair to say if you look at businesses today, it’s an interesting time. There is a lot going on in the world geopolitical, economically, from a skills perspective, how to build up teams. So we need to move as companies. Standing still is not an option. And I think from a leadership perspective, leveraging the capabilities of AI, helping leaders to do that.
it’s super, I see it as a super interesting, exciting time. So if I go back to examples like Sanove, yeah, we can help to shape the talent base and to make better use of skills and leveraging and helping to grow the company. Not in terms of size alone, but in what they do.
Bruce Daisley (25:47)
What are your thoughts? guess, Jerry, if I was going to characterise the product you created was almost to some extent, you wanted to take the thing, the contract analysis that humans hated doing, found boring, and enable them to focus their energy elsewhere.
Jerry Ting (26:03)
So I used to sit on a law firm in New York, and I would work till 1 AM at night, control F-ing in case there’s something wrong inside of a contract. All of that time I was doing that was grunt work, so to speak. And what was the purpose of that task? The purpose of that task was to have a conversation in the morning with a customer to say, hey, you’re about to buy a company. Is it risky or not? So if you think about that business process, 80 % of it was groundwork. The really valuable part of it was that conversation from a risk analysis perspective with a customer. What if you can have that conversation more quickly? I think to your point, leadership is still going to be there. Consulting, judgment, decision making, that’s still roles of the human. But the groundwork to get there, nobody wanted to do that in the first place.
Bruce Daisley (26:43)
There some forecasts that were published about a month ago that I found completely haunting by a former researcher at OpenAI, a guy called Daniel Kokotajlo. he, I guess if I was going to summarize it, he says we’re going to have 100 years worth of progress in AI by the next presidential election. And it’s an amount of change that I think is so overwhelming that I don’t think any of us can take it on board. But secondly, Angelique, you’ve spoken lot about curiosity. I think it’s very difficult for us of us to sustain a level of curiosity when the change is so fearful and so it undermines everything we’re doing. I’d love your perspective on whether you think that that’s hyperbole, that extent of change and how we can keep our sense of curiosity, tetheredness in the the face of all of that.
Jerry Ting (27:30)
I think it’s happening already. Like in San Francisco, you can actually just jump in a Waymo and you sit in the back of the car and there’s actually not a steering wheel in the whole car.
Bruce Daisley (27:39)
The only thing I’d say about that is that people have been talking about self-driving cars for 20 years. And so it just feels like this weary thing that, yeah, yeah, yeah, sometime it’s going to happen. And I don’t think we’ve been hit with a tsunami of all of a sudden we look out there and there’s robot cars. Whereas in this Daniel Kokotajlo I can’t recommend it enough, AI 2027 it’s called, then we tell you there’s two scenarios, humans don’t survive in one of the scenarios. And that’s in four and a half years that we don’t survive. But it’s like a wave of change that’s so extraordinary that I don’t think anyone can even begin to comprehend it. It doesn’t pass the can you explain this to your mum test.
Angelique (28:15)
so I think there is absolutely a point. We don’t know what we don’t know yet, but we will experience and learn a lot. And it’s interesting. think we talked about technology. There will be incredibly new capabilities coming from technology, but adoption and learning from it and how you use it to your advantage for your own purpose for the people, but also for companies that will prove, let’s say the value. And there will be a balance as businesses, they’re always will be a balance about what do you need to invest and what do you get out of it. it was, for example, Edemond Trust Core just did an analysis just to check is there a cultural element here, right? What came out of that is that, for example, India and China, 75 % of the people said, yeah, we will just take it and we will play and learn and we will go. We as European, and I call UKI also, let’s say the whole European, scale, we were in the 30 % range. So 75 %-30 % range. And then even if you look into EMEA, there are also differences. So for example, Sweden and Denmark are far more innovative on just trying and learning from that. And I think that this will be a bit where I would like to encourage us to say, yeah, we will learn a lot. We don’t know yet what five years will bring, but we will that there are a lot of new capabilities and let’s learn from it, right? So for example, in Workday, we now have an initiative kicked off which is called Everyday AI. And everybody who’s interested just plays around with AI tools. For example, Gemini and me as a person, I’m not native English but I’m also dyslectic. So I like pictures and I like summary.
Notebook LM I love it, right? It makes a podcast and a summary. So I think this is what I find fascinating also, just as a user, we need to play experience and learn. And McKinsey also had an interesting quote there that for companies, they encourage companies to start, but then start smart, right? And I think we can play a role there because we bring a lot of AI capabilities and genetic are standardly embedded in the platform. So if you implement it, it’s a relative okay or low price. If you build it, right, from scratch, it could be super expensive, which also might be worth doing it if it brings new business value. So the guidance of McKinsey was find a balance of what is the cost investment versus what is it delivering. to your business value. And I think this comes back to, we will learn a lot, but to try it in a smart way and an efficient way so that it brings value in making your job easier so that you can focus your role on more valuable time, that’s I think that’s the way we go.
Bruce Daisley (31:16)
You mentioned something interesting there which was almost setting time aside for learning. Do you think organisations right now need to be doing that specifically saying we’re going to sandbox certain amount of
Angelique (31:28)
absolutely I feel I feel personally very passionate about it that me as an individual and companies should encourage I like our initiative of everyday AI encourage to to to play pilot with it Just coming back to your earlier questions culturally we see differences But also to be honest, we see larger companies adopting it earlier than then the medium enterprise companies not that medium enterprise
companies are not interested but larger companies have I think they have the opportunity to build a dedicated team to really help to accelerate it in the company. but ME companies, medium and medium are super interested because that’s where a lot of innovation comes from but not always they have the bandwidth to do it. that’s currently what we are seeing. There is incredible interest here.
Bruce Daisley (32:19)
Jerry, we’re talking there then about learning, about mindset change, about rethinking how we wire up organizations. How do you think about that? Is there anything that you would advise these leaders in the room? How would you advise them to recalibrate their teams?
Jerry Ting (32:33)
Everyone needs to be a student right now because some of the skill sets that made people successful are going to be the skill sets and the habits that make them not successful in the future world. talking about large organizations at Workday, I have a team now of people whose only job is to build agents. But there’s people on that team who come from not AI native pasts. But the reason why they volunteered for this department is that they want to go and take the hill. That is a brilliant culture that we have in this team. I think that needs to happen across the entire organization. But the fact that there’s people literally saying, I want to leave my old job, and I want to go into the great unknown, and I want to my career on that, we want to celebrate those people.
Bruce Daisley (33:13)
It’s fascinating self-selecting, it? I saw something recently that said a lot of people in their jobs who were upskilling themselves about AI are doing it in their own time, in their own capability. And you’ve almost said there that almost there’s something about people putting their hands up saying, can I do this? Is a really good tell for actually capturing the enthusiasm to try and shift to where we’re going.
Angelique (33:32)
Absolutely, curious mindsets, right, as a characteristic of people will be super important. And companies have that back in their cultures, right? This is where purpose culture comes in. There are a lot of great companies who have that curious mindset of, let’s learn, let’s try, but that will be a very important one. Sometimes we talk about agility, same thing. It’s companies who are more agile, constantly want to learn, try. and evolve, I think, are running ahead of others who are more standing still.
Bruce Daisley (34:02)
Angela, you’re an incredibly energised, optimistic person. There’s a lot of people right now who are describing the job market for new entrants into work as maybe one of worst job markets that they’ve ever witnessed. People are trying to get in, they can’t get entry-level jobs. We’re seeing reports of the job market contracting in other areas. Is there a reason for us to be optimistic about what lies ahead? There seems to be plenty of reason to be cautious and pessimistic about some of the business disruptions we see but what’s the booster case for for the people who maybe aren’t necessarily on the fast track inside the best organisations
Angelique (34:38)
I’m a positive person as such. So I always look at the glass half full instead of glass half empty. But I’m personally super positive because the change is happening now and maybe change should have a different word. But it’s super exciting that we will learn a lot. So people who come in with a curious mindset and Jerry just gave a brilliant example that it’s not about what people have done in the past, but it’s about the curious they will take forward because there will be an ever learning and this will be super important. So also for the talent markets and this is where a lot of companies work on a skill-based culture. It’s about encouraging and opening up this talent pool, to really learn and adopt and bring companies forward. So I think this is if your mindset is, yeah, let’s jump into Jerry’s team and let’s learn and let’s bring it forward. I think there are huge opportunities everywhere.
Bruce Daisley (35:37)
I’m old enough to remember that when email came onto mobile phones, we were convinced it was going to make our job so much easier because we get all of the emails done when we’re on the tube, walking up some stairs, we’d answer a few emails and work would be a lot easier because we’d sit at our desk chatting to people having a laugh. And it didn’t, it didn’t turn out like that. Is there a danger that we’re going to fall into the same, that we spend so much time checking in on agents that we’ve got doing jobs? That we need to be sort of checking 24-7 how they’re getting going. Is there a danger that this technological innovation that’s sitting right in front of us is going to make work even worse?
Jerry Ting (36:18)
I think it’s really dangerous saying, we’re in an AI wave, so let’s use AI to solve every problem. It’s a giant hammer, and every problem is a nail. There’s a lot of things where AI should not be used to solve that problem. And so I think that’s where. At Workday, we want to be super thoughtful on which problems, what are the right tools. I think to your point about this sort of ungrounded LLM hallucinating, you can create more work than you can save. So from us, a product perspective, we need to be super thoughtful. Is this a good problem to solve? Is it valuable? And then is AI the right way to solve it? Sometimes a good old-fashioned pen and paper may be a better way for some problems. So I think we have to be super thoughtful on that.
Angelique (36:55)
Yeah, just to go back to your example, think with having had the email example you were giving, I think this is really resulting that you go faster as a business. And I think we see that with the tectonic shift of technologies, information will come faster. And if I look at the younger generation, I’m super positive because they are digital natives, right? So my sons, who are now 21, and 25. My youngest son in university, he leveraged tools like Notebook LM standardly and he’s doing brilliance with his results at this moment. So let’s hope that it will continue to do so. But I think it will be an acceleration of what is possible. And we see that with email everywhere as well. And most probably we all believe that AI, agentic AI will help us to go even faster. But then let’s have time for coffee and for a really good conversation because that’s will definitely something we as humans are very good at.
Bruce Daisley (37:56)
We’re almost out of time. We’re at deadline. I just want you to leave us with one thing. our card for something. If you were going to make one prediction, one cultural bet, whether it’s about the world of work or how we’re living inside organizations, one bet that you think will pay off by 2028, what would that be for you?
Jerry Ting (38:14)
I think the companies that lean into AI will attract the better talent. And that’s going to be before 2028. It’s going to happen today. The kids’ age that you talk about are the age of my students. And when I watch what they do, I’m the iPhone generation. This is the GPT generation. Tthey’re not going to be OK with using legacy processes, legacy culture. They’re going to say no to that, and they’re going to leave. And so there was a student in my class who actually built a software. It wasn’t a production-ready software, but he built it in nine seconds in a prompt using a Vibe coding software. And I asked him, why did you build this piece of software? Are you trying to start a startup? I’m happy to help you with that. He said, no, I built it for myself because I just don’t want to do this part of the homework anymore.
So if they’re doing that on homework exams, they’re not going to sit in an old company and do old things. They’re not going to do that.
Angelique (38:59)
No. So for me, adoption is key and that curious mindset. That is, I think, really key.
Bruce Daisley (39:05)
I’m so grateful for everyone’s presence today. A fascinating discussion. Thank you, Gerry. Thank you, Angelique. I’ve been Bruce Daisley. Thank you very much.
