← Me, Myself, and AI
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- [00:02]
Podcast Host (Intro/Outro)
We hear a lot about using agents for workflows. One company has 80,000 active workflows and believes it's making innovation, employee experience, and other aspects of its business better with AI. Learn more on today's episode.
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Jackie Canney
I'm Jackie Canney from ServiceNow, and you're listening to Me, Myself and AI.
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Sam Ransbotham
Welcome to Me, Myself and AI, a podcast from MIT Sloan Management Review exploring the future of artificial intelligence. I'm Sam Ransbotham, professor of analytics at Boston College. I've been researching Data analytics and AI at MIT SMR since 2014 with research articles, annual industry reports, case studies, and now 13 seasons of podcast episodes. In each episode, corporate leaders, cutting edge researchers, and AI policymakers join us to break down what separates AI hype from AI success. Hi listeners. Thanks again for joining us. Today I'm talking with Jackie Canney. She's the Chief People and AI Enablement Officer at ServiceNow. She leads all talent strategies for the company's rapidly growing global workforce. We've known each other for a few years, and I'm glad the timing finally worked out for us to talk with our microphones on. Jackie, thanks for joining us.
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Jackie Canney
Thank you. Thank you, Sam, for having me. I'm really excited for this conversation. Thank you.
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Sam Ransbotham
Could be fun. Well, let's start with ServiceNow. It's huge S&P 100, but some listeners might not be familiar with all that the company does. Can you give us a bit of background?
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Jackie Canney
Sure. I'll start with what our purpose is, which is to put AI to work for people. And at that core, we are the AI platform for business transformation. And if you think about automated workflows, you think about the ability to drive your business results. It comes down to how you direct work. And our platform is literally built on AI so that we can help companies in. I think it's now 80 billion workflows that we manage that produce either better service, more analytics, all the things that companies are seeking to do with their organizations. I was a customer of ServiceNow, so that brought me to really be excited about working here, too.
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Sam Ransbotham
You really led with AI right there. How did that happen? We're just relatively few years into this whole AI world. How do you have 80 billion? I thought for a second that just seemed like a huge number. How do you have that many workflows using AI already?
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Jackie Canney
We have a very innovative company. It's 22 years old, I want to say, and was built on how to help people experience work better. Fred Luddy, our founder, built the first workflow for a colleague who was struggling with the swivel chair of getting work done and Excel spreadsheets, et cetera. So at our core innovation has been something that we've always tackled and you've seen the movement like analog to digital, prem to cloud, cloud to mobile. Now this conversation to AI and ServiceNow has had these amazing engineers and product leaders who've been thinking about this for a long time, A long time before even people Talked about like ChatGPT maybe
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Sam Ransbotham
give us an example like what is one of these 80 billion and how does artificial intelligence involved in that?
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Jackie Canney
Yeah, so I'll take one in my area that I see a lot when somebody gets hired to work here, there's lots of steps to onboard people and that can be a lot of conversations. It can be different managers, different departments. But with our onboarding platform you say, hey, this is the person that's starting. This is the kind of computer that they want. This is the kind of cell phone that they need. This is the training they need to have happen, the proof of identity so that they could be paid, that they get paid, that they show up and they're free, feeling productive before they even start on that day. And then what happens? Post that onboarding because there's follow ups reminding a manager, hey, so and so started 10 days ago. Why don't you check in? Or so and so, you know, got their first kudos, you know, a recognition like why don't you check in and see how they're doing? So it's an automated workflow that takes the guessing and makes the manager and the employee really feel a relationship right at the gate. That's personalized.
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Sam Ransbotham
So I guess in that process then where was artificial intelligence? How does that fit into all those steps?
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Jackie Canney
So you can have an agent. If I say I want a MacBook, it makes the order, the agents get the order done, the agents get the order shipped to your house. It's agents working in the background while people are able to focus on what they need to, which is welcoming this great new employee.
- [04:33]
Sam Ransbotham
Yeah, that seems like a good separation of tasks of the classic getting rid of from the dirty, dull and dangerous parts to the things that humans are better at. So tell me a little bit more about how would you organize a process like that Because I think I would be tempted to get whatever computer or phone I wanted without oversight perhaps. How do you integrate that?
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Jackie Canney
It's a really great question because it does bring it down to practical like how do you get this work done? And there's governance, you know, that is built into the Platform, you're creating that governance as a leader when you implement the technology. So, you know, like price points, options, you know, whatever it is that your company is governing gets embedded into the choices. But also there's design, which is something that maybe not everybody thinks about when you talk about platform technology. But designing the experience is equally as important so that it's not just about, here's what the CIO is trying to get done, here's what procurement is trying to get done, here's what HR is trying to get done. But putting the person at the center, manager and the employee and designing a process that's really great for them and we also have it so you could do it on your phone is at its core with the right governance around it. And then if something goes wrong, because that can happen too, what's the feedback loop? If the wrong computer came or it didn't come in time or you know, that we can get the signal so that we can continue to improve our process and certainly find where a process flow might break down so that you can correct that in the tech.
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Sam Ransbotham
Yeah, that makes sense. So how much do people then know? Let's go back to your new hire example. How much do they know that artificial intelligence is involved in this process? Or where is it obvious? Where is it not obvious?
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Jackie Canney
It's becoming less obvious is what I would say. We've acquired a company called Moveworks, which is in and of itself a front door conversational experience. Earlier versions of our platform would feel potentially more like, I'm interacting with technology, I'm searching, I'm getting directed to KB articles, things that were all easier, not perfectly seamless. Now this conversational layer which we've implemented for all our people is like going to search. You know, you go to it and say, hey, I'm meeting with Sam. What was the last meeting that we had? And it's literally having this conversation. So I think it's becoming less clear if you're talking to a person or you're talking to tech, which is making it really easy to get to the answers that you want.
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Sam Ransbotham
Actually, one of the things that I think about, maybe this is just my own personal weirdness, but I feel like I interact with people differently than I do with machines. Like for example, if I was talking to you about getting a computer, I might say, oh, hi Jackie, how are you doing? You know, it sure is snowy here. It's really cold. I was thinking about getting a computer. On the other hand, if I was talking to a machine, I might be a little bit More brusque and say, buy machine now and maybe the robot overlords will come back and get me for that. But it seems like there could be some efficiency in being transparent about, hey, you're talking to a machine. You can drop the conversation about the weather perhaps or the social glue.
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Jackie Canney
And it's funny, you can have sort of social conversations with the machines too. You know, it can recognize if you're stressed or in a hurry, you know, the tempo of our voices and it directs into, you know, sort of responding in that way. You also can find a way out to talk to a person. Like you can click through to get to a person. So that way you can, you know, get out of the whatever chain of conversation that you're in. It's one thing you bring up though that I do worry a little bit about us as humans in if we are abrupt with the machine, are we going to forget and be abrupt with each other that we're talking to the human? And I think that's at the core of what I've been spending a lot of my time on, is that there's a lot of technology talk. There's 80 billion workflows just with us, but without getting the change management of the users. Right. Whether they're your employees or your customers or the end users of your technology. I think is where, that's where the concern for me, that's what I've been thinking about.
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Sam Ransbotham
I haven't thought about the spillover the other way, but that's a good point that maybe I'm becoming brusker to my human.
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Jackie Canney
You're humans.
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Sam Ransbotham
Yes. Okay, well, now I got a new thing to worry about. So how much do these employees need to know about artificial intelligence? What's your thinking on how much awareness people need to have of these technologies in order to be successful? Hi listeners. Sam here. We're all fighting to keep up with the latest advances in AI technology. You can unlock transformative power of AI with the new AI Executive Academy at MIT Sloan Executive Education offered jointly with the MIT Schwarzman College of Computing. This 10 day in person course dives deep to explore both the technical and business aspects of artificial intelligence, providing a comprehensive understanding of AI's impact across industries. Learn more at Executive MIT. Edu AISMR. That's Executive MIT. Edu AISMR.
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Jackie Canney
We've invested quite a bit in this space. Every person who works here has had AI training and we've been doing this for a couple years. Which one? Because the products we build, no matter what part of the company you're in understanding what AI is, have a common vocabulary about. That was really important to our CEO and our leadership team for the company. We've invested having from speakers to AI Day to different kinds of training. And we've evolved quite a bit now where we've assessed the whole company on AI skills. And it's not like one size fits all. Different roles have different expectations and different experiences. So we've customized the assessments and built personalized learning journeys so that people can grow their skills. And we've seen our organization really lean in and be excited about that. We also celebrate people who use AI tools really frequently because they're learning from each other. I want to eliminate as much fear in the workforce about what AI is and what we're using it for and how we can use it in the future. And I think by being transparent, by offering opportunities, by giving people learning experiences, even for myself, I've been seeing more confidence grow. And we ask our people all the time, how are they feeling? And they feel pretty strongly that they're getting the tools that they need. So we're going to keep at it.
- [11:09]
Sam Ransbotham
Actually, there's like four or five things that I wanted to follow up on there. You mentioned lots of good topics. Maybe the first one I'll start with is just how much do people need to know? Like what kinds of things? You mentioned vocabulary, I think was one of the things you meant, which makes sense. I mean, we need to be able to talk about technology in ways that make sense to communicate with each other. But what are these skills that people are trying to pick up on?
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Jackie Canney
Yeah, so like prompt engineering is something we all have been talking about, and it is not something we talked about that long ago. Right. And you have a team, like in my organization, which is a human resource people team, and we have implemented obviously our own tech, and we were able to double the productivity of what my team could do. It was 1 to 400 to 1 to 900 that we were serving because of the tech. Now, I didn't want people to be displaced because of that, but then they became better at either. A couple things. One is prompt engineering so that they could help create better questions that they're asking so that we can get better answers and then train AI so that it continues to be better ANSWERS, because over 90% of our inquiries that go to our Now Assist, which is our own tech, get answered by the tech. So the more we can make that smarter and better, the more people will be happier to use that. And then we also created new roles it's just adjacent skills that I've seen the team lean into. We have product engineers and product designers inside hr. We didn't have that before. We've built a new role called Forward Deployed Engineer, which is somebody who is quite technical but has a interest and a desire and is really great at talking about business problems and business transformation and marrying those conversations together. So you can imagine talking to an HR lead, a CIO somewhere out there that is using our tech and they know they have this problem they want to solve or this opportunity to fix. Now we've built a workforce that can go meet with that team, talk about their problem and then say here's how we suggest the technology can solve the problem versus saying here's the technology. Like work it around it and work it into your solution. It's more in service of the human.
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Sam Ransbotham
Yeah, those are some interesting numbers, like the 1 to 400 to 1 to 900. And your first reaction would be okay, yeah, that's going to lead to reduction. But as you point out, there's just a bunch of new tasks that are coming up and new roles that are coming up. As quickly as we maybe whack a mole a little bit, you're trying to eliminate some work and new work's getting created. What's your sense of the net like if we're moving from reducing things that people are needing to do by let's sort of the 2 to 1 ish type of number that you mentioned. But you mentioned new roles too. Like it seems like a big deal if that is a one to one swap, a one to a half swap or a one to two swap, like that's big. Which direction is it right now?
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Jackie Canney
A crystal ball would be really good on that one right now. I think every company's tackling it in their own way. I think that at its core some companies have gone after this with a cost cutting lens and I don't think that's the way I would start if someone asked me. I really think the opportunity, as has in history to technology provides capacity and creativity hopefully or new adjacent business lines, the things that can grow. I've seen it not just here at ServiceNow, but even in my old job at Walmart where you could see where you implement this powerful tech. But it does create expansion and the hard work is the work redesign that has to happen. And that's where leaders, CEOs, chief people, officers really should be spending their time. Because I think whether it's a one to one or you're flat or you're growing. You got to design that future. And if you don't design it, you'll lose the capacity, is what I think.
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Sam Ransbotham
And I think I was too sort of crude to say, is it net plus or minus? I'm sure in many areas it's plus, in many areas it's minus. And then we're looking at the net of the net across a big aggregate. The crystal ball is not quite polished enough for that. So I think this training program you mentioned is part of the ServiceNow University. And I like the idea that you mentioned the skill assessment as part of that. But at the same time, you also mentioned just a second ago that prompt engineering wasn't something you were paying attention to a couple of years ago. So we have the changing skills of people and the changing needs of people. How often are you measuring these things? How are you measuring these things? What kinds of. I mean, just the details on this seem very difficult in a rapidly changing world.
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Jackie Canney
Yeah, well, we have jumped on this with all of ourselves. The board, our CEO, the leadership team. Everybody's fully supportive of the changes that we're making and that we're driving inside our own company. And this assessment was important. I felt like we needed, like, an X ray of the company to know where we were to be able to go forward. And we didn't use it as anything scary or a negative. It was really meant to be, like, we're all going to get smarter about what we know we have as skills and what we know we're going to need. And then if you take what we're going to need, you're able to see, and this is with the help of Pearson, they've been a good partner to us to say, like, here's the jobs, here's the skills, here's the new work that you're planning, and then here's the gaps you need to close. So it's very personalized, but it's also how we're moving our change management through as a company. And I have other HR leaders that I really, you know, sort of love working with. And we all talk all the time about how they're tackling it. And I think commonly that's what I'm hearing my peers talk about, how we're sort of going after it. It's like your X ray, your gaps, what can you build, what's adjacent, who can you train, who can you grow? Who do you have to hire?
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Sam Ransbotham
You know, actually, I'm ready to. Do you let outsiders take this. I'm ready to. I'm ready to sign up because you know, one of the things, like I screw up a lot of stuff and I could be so nice to know ahead of time the that I'm, you know, I always think about this in the, you know, one incremental hour. If I had one extra hour, what would I do at that hour? And lots of times I just don't know what the right thing to learn is or the new thing that would help the most. And I'm fascinated by the promise that this technologies could help us learn about these things.
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Jackie Canney
Yeah, well, ServiceNow University's got a lot of free courses out there. You can go check it out. I'd love for your feedback about it.
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Sam Ransbotham
Great. So you gave me homework. That's no fun.
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Jackie Canney
Yeah, there you go.
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Sam Ransbotham
One of the things you've talked about is soft skills. And so you know the idea of a soft skill versus hard skill. Well, so first, what are your thoughts on the relative importance of those two types of skills going forward?
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Jackie Canney
I have always believed that critical thinking, the ability to like pattern recognize those things that you learn, whether it's through your work, your university, you know, all the experiences that you have are never more important than they are now. And I know lots of people are talking about that and it's not meant to be like an easy thing. Not everybody has those skills. But people can be nurtured, I think, to learn better how to create those skills. And one of the things that I've been really kind of thinking about is we talk also a lot about leadership. And we've all talked about leadership for a very long time. But now more than ever, the ability to find the people that have the wisdom is really important. So if you're leading a company or you're leading a team, it's never been harder. Everything's really complex. People are on the road, people are hybrid. We still have some Covid stuff that we're dealing with. And now you have this really important technology that's kind of hit everybody's desk but at the same time the world is moving faster than ever. So how do you have the confidence to literally pattern recognize, have the wisdom to say these are the use cases I want to go after as opposed to these are just the use cases that everybody is bringing to me because that's where I think these soft, they're not so soft but they're really non technical capabilities that we all should be focused on growing.
- [19:14]
Sam Ransbotham
It was interesting we had Taylor Stockton, who's a former student of mine, on a previous episode, he works at the department of labor. And we were asking them hard skills, soft skills. And so he talked for a bit about soft skills and the importance of that, but then at the same time he said, well, people also need those technical skills. So what's your take? If I have one hour this afternoon, should I spend it on developing a soft skill or a hard skill or listen, not me, don't pick on me. One of my students who wanders in here, what's the one hour? Where do we spend it?
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Jackie Canney
Oh, I think the one hour, I might say 30 minutes on what are they curious about with the tech? So is it protocols? I think protocols is going to be the next thing we're all talking about. Like how do you govern the agents inside a company? That's really important. So understanding the nature of how do you build and create protocols is not something you need to be the computer science person to do. And then the second is, I do really think the ability to drive this critical thinking. I'm absorbing problems, I'm absorbing information. How am I able to take that and process that into an idea or a point of view? And, you know, I think the world of my university and that was a lot of how we were taught, was not just to be great accountants or great finance people, but also to be great thinkers. And having that be part of what you're thinking about. If you have one hour, I think it's worth it.
- [20:42]
Sam Ransbotham
I have a ton of students who are about to graduate. They're talking about difficult job markets. And I know you get asked this probably every time someone talks to you, given your role, but what should students who are close to graduation be doing? What should they be thinking about as they enter this job market?
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Jackie Canney
Yeah, I think two things are really important, and one is what are the skills that they're taking out of their university experience? When you go to work at a company, they're going to teach you a lot of. They're going to teach you how to work. They're going to teach you a lot about that company, about how they work. But if you can come out of school with one great skill that you're super proud of, it could be you're a great writer, it could be you're a great coder, it could be that you are a great speaker, like whatever it is, but really know what that skill is and how you're going to sell that into an employer that you're going to work at. You're probably more AI native than anybody else in the company because of the nature of how you're Growing up and like the world that you're in already. So that's also on your side. But the second thing is growth mindset. Demonstrate your ability to learn and change and be agile. Because I've also said, and I don't have this written down because somebody told me, but the companies with the best language models are not going to be the ones with the most adaptive agile workforces. So I look for those kinds of qualities, especially in the early and career talent that I get to meet.
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Sam Ransbotham
I like that it's hopeful. And I think your point about how well prepared students are. I love job descriptions that have something like needs, 30 years of experience, large language models. It's just not possible. And so the students graduating now are just as, or maybe probably more familiar with this technology than many of us are. So that kind of leads to some thinking about. I was thinking about blind spots. You've been working at Walmart, WPP. I think ServiceNow. What are people getting wrong? What are leadership blind spots here when people are thinking about artificial intelligence?
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Jackie Canney
Well, I think focusing on the tool and not the talent is one of the top things people really get wrapped up around. Like, what's my AI strategy? Where it's really your business strategy? And then how does the business use technology? But certainly how does it bring its people along with it? And that gets missed a lot, I would say. I talked about the cost cutting exercise. I think people get that wrong when they lead with that. Waiting for a perfect plan is another one. I think people get stuck in. I know. Sometimes even I do. Right. It's like you don't have this all figured out. Like you said, 30 years of LLM experience. Where's that gonna come from? It doesn't exist yet.
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Sam Ransbotham
Ooh, I feel seen with that one.
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Jackie Canney
Yeah, right. And I think people skip the hard parts. They skip the culture, they skip the trust, they skip the people part. I feel like that's the stuff that I've seen go wrong.
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Sam Ransbotham
I think there's a lot of ways to screw this up too. There's just a lot more ways to get things wrong than there are to get them right. Your idea of not having a perfect plan to start with feels wrong. Well, I was reading something that you'd written about. I think it was a family trip where you had AI write a poem for the family trip. Okay, I was thinking about that. It struck me as funny because we actually, just for a cringe moment, I had my classroom write a theme song for our ML machine learning class. What would generative AI say is A good theme song for our class and we did not all recite the class anthem afterwards. But you said that surprised you as something that the tool could do. What's surprising people about what these tools are capable of? What are the things that people are learning. Aha. From these tools?
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Jackie Canney
Yeah, I mean, I think it's the ability to be better prepared for X meeting opportunity we have seen in our sales organization where they have access to all the data about our customers, about the work that they've been doing and now how to prepare for those meetings in minutes and not days has been, I think really exciting and eye opening. And people are loving that because it's just easier to get to answers quicker. The other thing that I saw that people were super excited about, especially in our sales organization, it went from like four or five days to find out what your commission's going to be to 8 seconds. So if you have a workforce that's motivated to know that making that easier has been a great, well received use of what the technology's been able to do in the day to day. And I probably could think of a bunch more, but those two come closest to me right now.
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Sam Ransbotham
Actually, I like the quick feedback part because as you were thinking about earlier, you were talking about assessing people's skills and I was thinking about testing and how in the education world we do a fair amount of testing. And one of the things I was thinking as you were saying that is that students actually don't dislike tests. Now I'm sure people are freaking out right now as I'm saying that, but people like to get feedback about what they know and what they don't know. People like quick feedback. And so the same thing with your commission example there. If you do something and you get feedback quickly, then that helps us reinforce it helps us know what to do better. I mean, HR is historically driven by the idea of the annual performance review which 364 days ago, what did I do right or wrong, I don't learn very well from that. And that's the example. I mean you were mentioning commission, but the example of quicker feedback. Both of those though, I'm going to push back a little bit. Both of those feel like productivity enhancing. But we said earlier that there's a bit of a trap of getting too sucked into productivity. But faster meeting preparation, faster readiness is good, faster feedback is good. But both of those feel like productivity. What would be the missing thing that we would want to add to that to make it a non productivity?
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Jackie Canney
I think it would mean like the Sale got better, bigger. You know, if I had all the things I maybe before wouldn't have known about, like what did they say on LinkedIn? What's the stock price? Doing what's the biz? You know, like, there's an opportunity to not be incremental, but to be more impactful. And maybe the sales commission, one is a little bit about productivity, but I think it's also highly motivating that might get the salesperson to say, if I could just sell this much more, look at what my commission could be, and then lean into being better prepared for that. I think too that I've seen us think about leadership in a different way that I'm not sure without AI, we would have had the capacity to do. We have really stepped up. What does it mean to be a leader here and invested in that bigger than I've ever seen, because we know that that's really the unlock for the organization. And I think because of AI, maybe creating the capacity even for my own team, to be able to dream a little bigger about what the future of leadership and this concept of wisdom, I see that opening, too. And I would say this lane of opportunity is what we still haven't figured out yet. What are we going to build? Are we going to build a new business? Are we going to have totally different companies that are created? That's what I think we're on the cusp of figuring out.
- [27:55]
Sam Ransbotham
Well, I don't know about figuring it out. So you've touched on this. I mean, you're obviously from a human resources background, but you're talking about a lot of stuff that feels like you're stepping on some IT toes here. So how is this relationship between these formerly quite separate parts of organizations? What's the relationship going to be as you're using more of these tools? Is there? Yeah. On today's branded interview segment, I'm talking again with Shayan Mohanty, chief data and AI officer at ThoughtWorks, a global technology consultancy. Shan, thanks for joining us.
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Shayan Mohanty
Thank you so much for having me.
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Sam Ransbotham
A lot of us can't help but think about productivity when we talk about AI implementation. What are your thoughts on productivity in the age of AI agents?
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Shayan Mohanty
I would argue that productivity is not actually the only measure. It is a measure. But some organizations, some roles, may not care as much about productivity as they do other things. Our core thing here is that every use case is going to measure these things differently. It's going to be entirely up to the organization to decide what they care to measure and what is actually driving Their outcomes, we have a few guesses as to what those are going to look like. There's performance. So overall quality measurements. So that could be precision recall, accuracy. In the case of classification, it could be trajectory, it could be all sorts of different things, reasoning capabilities. There's all sorts of stuff there, right? That's one quality latency. How quickly end to end are you able to go through one invocation of an agent workflow which then leads itself towards like performance in the form of faster iterations, faster throughput, larger volume, more productivity. Right? Latency. And then the final one which is super important is cost, but really it's roi. Right? Across every single interaction. Let's say that I have a complex agentic workflow that has many different agents, many different models, many different MCP servers. Every single hop in that workflow is going to cost me some amount of money at the end of the day, right? I'm either spending it on tokens or I'm spending it on tool calls, or I'm doing some combination of those things. And the amount of money I'm spending per token differs depending on which model I'm using. And I might use many different models throughout this workflow. So I have some fairly complex calculation. But there is a calculation that I can do that's like this is how much invoking this agent flow cost me. And here's what running that business process end to end netted me, right? Every business is making that assessment at some level. Our point is that every organization is going to balance these things differently and it's going to be per use case, which implies that every organization has some type of control plane, like just a UI over their operating system that lets them optimize in the ways that they expect for a use case, for an organization, for a team, whatever it ends up being.
- [31:07]
Sam Ransbotham
I like thinking about measuring agentic AI. Where can listeners go to learn more about ThoughtWorks thinking in this space?
- [31:14]
Shayan Mohanty
Feel free to Visit us@thoughtworks.com where we write a whole lot about governance and compliance and all sorts of other very fun agentic things.
- [31:34]
Jackie Canney
I think AI is disintegrating the org chart and not just between HR and it. It's sort of coming across a bunch of places because it just doesn't see that way. It doesn't see silos, right? It sees across. And leaders are having to get comfortable with that. It doesn't mean that the roles aren't important, it's just that they're changing. And here at ServiceNow, I was promoted to AI Enablement Officer along With the chief people officer role just a little bit over a year ago. And that was because Bill felt like this is truly a human capital moment. It doesn't make me in charge of it all. I'm the team captain. I'm not alone. But I have to have sort of like keeping score of how we're doing with that. And I think that says a lot about what he sees as a guy who's seen across technology for decades of where change really gets. Now, our cio, our product team, we work really closely and we have agreed that the employee experience sits primarily with me and my team. So how technology, how processes, how policies, how all that impact the experience were kind of like the filter on it. We work really closely together. We have very transparent look at what use cases are in productivity across the company. Who's driving roi, who's not. We have a control tower for that. I think that that kind of keeps us all square because we can see very openly what's happening. But yeah, HR roles are totally evolving. If you're a chro who's really focused on process and policy and annual cycles, the CIO is going to come for you.
- [33:06]
Sam Ransbotham
We have a little segment where we ask quick questions. Just answer the top of your mind. What about artificial intelligence is moving faster or slower than you expected?
- [33:15]
Jackie Canney
Moving faster in headlines? Moving slower in. I'll say, scalability.
- [33:26]
Sam Ransbotham
Yeah. Getting something across an organization. I'm sure you think about that a lot. How are people using AI? Poorly.
- [33:34]
Jackie Canney
I think they're writing poems like I did.
- [33:37]
Sam Ransbotham
Okay, all right, there you go. What do you wish that AI could do better?
- [33:41]
Jackie Canney
Hmm, I wish it could. I think it's getting there, but it's like the context and memory of being better. But I think that's maybe more even how humans are using it. It's like how I truly can make AI be a digital twin of me. I haven't figured that out yet.
- [34:02]
Sam Ransbotham
Are you finding because of AI you're spending more time with technology or less time with technology?
- [34:07]
Jackie Canney
I think it's just in the flow of work now for me, I'm not really discerning am I in the tech or not?
- [34:14]
Sam Ransbotham
But this has been fascinating. I think one thing we'll come back on is this idea that the use of artificial intelligence is eroding these org charts. I think that's a really interesting high level thought to come away from this. Thanks for taking the time to talk with us.
- [34:28]
Jackie Canney
Thank you, Sam. This was great.
- [34:31]
Sam Ransbotham
Thanks for joining us today. On our next episode, I'll speak with Peter Corte. Chief Technology Officer at Siemens, and we'll talk about industrial AI. Please join us.
- [34:41]
Podcast Host (Intro/Outro)
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