AI Leadership Insights: The Impact of AI on Finance and Human Resources

Amanda Razani: Hello, I’m Amanda Razani with Techstrong.ai and I’m excited to be here today with Laura Hanson. She is the chief human resources officer for InsightSoftware. How are you doing today?

Laura Hanson: Great. Thank you, Amanda. Nice to be here.

Amanda Razani: Nice to have you on the show. Can you share a little bit about InsightSoftware and what services do you provide?

Laura Hanson: Certainly. We’re a technology provider. We are a global provider of solutions that help with reporting, data analytics, performance management solutions that predominantly serve the office of the CFO and all the products that go along with the office of the CFO and our data teams. And we’re about 2,000 people in 30 countries, half a million users. So pretty decent-sized span of impact that we have.

Amanda Razani: Wonderful. So our topic today is the state of AI in finance and across the board in all industries and how it’s making its impact. So, to get started, what, from your experience, are you seeing as far as AI in the industry and how is it impacting different roles and different processes?

Laura Hanson: I think there’s really three main areas. I think the impact, at least that’s come to mind for me, and I’ll start with recruiting because not the fact that we use AI in recruiting. We do. That’s been around for some time. We use bots to engage candidates, we keep them engaged along the way, screen résumés, et cetera. That is in existence and continuing. What I think the implication though, that Bear’s talking about is the labor market and what kind of skills are out there.
So with this blooming attention on AI, those skills, they’re going to be competitive to try and go get like deep machine learning, deep LLM skills are going to be hard, especially for small midsize companies who are competing and lots of organizations are going to be looking for those AI skills. So I think that’s not unlike other times that we’ve had hot skills in the market, but it is going to be an impact for companies to try and find that skill set.
So that’s the downside. The upside is a lot of these guy’s skills, not the heavy tech skills, but lesser tech skills can be trained. So I think that that’s a real opportunity for companies to think about how can you grow some AI capabilities in your organization, particularly in light of this really tight market for those types of capabilities and how can you train them? It reminds me a little bit of HTML, when HTML came out and everybody needed HTML skills, but not that many people had them, but it was something you could train and it’s really great, for one, employees. InsightSoftware is a tech company, so we obviously have people who like to stay abreast of current technologies, but lots of organizations have technology workers in their companies and having the ability to train those people in AI skills is great for the people, but it’s also great for the organization particularly because you’re bumping up against this tight market of people out there who have the capability.
So I think it’s a good thing is we’ve got an opportunity here to grow some of that capability within the organization. So that is something I do think that companies should harness and it’s almost out of necessity because of a tight labor market, but it’s also a benefit to both their people and the organization to get people in-house that can do those kinds of things. So I think recruiting is a big implication.
The second part, which is a bit akin to recruiting and talent development is a focus on career development and learning. So I think that there’s … You know, AI people talk about all the jobs that are going to go away with AI and that’s true. There’s jobs that are going to go away or parts of jobs that are going to go away. InsightSoftware does this as part of our solutions is that we’re trying to increase productivity with our tools for those teams, for those data teams, for those finance teams.
And AI is a similar approach. So there’s lots of tasks that people do that can be replaced by AI. And I think that the thing to think about here is when that happens, the shift is going to be to have employees who can focus on higher level skills, different skills than those rote skills that they might be doing and embrace that the technology within AI paves the way to build capabilities and employees that are not technology specific.
So let me give you an example. So chatbots have been around for a long time in customer support, et cetera. And if you can minimize some of the level one tech support, for example, you can shift to having your employees work on different types of skills. So that part of the job’s going away. There’s always going to be a need for humans. You can have them focus on audit skills or problem-solving skills or customer relations skills and having those high level of skills.
And I think those skills are ones that, one, employees want. “I don’t want to be doing things that are not challenging me.” But two, it’s great for their careers because those types of skills, any of those kind of higher level skills they can take with them to other companies.
So I think that that’s a really important message for learning teams in organizations is to make sure you’re focused on what are the skills when AI comes in and takes away some of these kind of rote tasks that people are doing. What are those kinds of skills you want to employ? And while AI is fantastic, there’s context to everything that comes out. So having people use critical thinking, problem-solving, those kinds of skills and building those into learning programs for organizations I think is going to be really great way to, again, harness your employees’ capabilities that they might have otherwise not had. But it’s a great shared success model for the organization to have their employees performing at a different level, maybe service customers in a different way than they had been. And it’s good for the employees because it helps build those skills that they can take with them wherever they go. Those are skills that transcend technologies. So I think that’s a really good message for the learning teams to focus on what are those types of skills you want to build when AI is coming into their organizations to augment that need.
So I think that that’s a big one. And then the third thing I would say about implications is around really retention and engagement of people. So obviously Great Resignation, lots of people out there moving jobs and then we’ve had a ton of tech layoffs in the last year, so people are staying put a little bit more. Open jobs have come down a bit. And while that means people are staying put, it doesn’t necessarily mean they’re engaged. So that when the local market opens up again, you want to be able to retain your people.
And I think about this because I have teenage sons who use AI for everything, and that’s just not … I do, too. I mean, we all use it in our personal lives. And so, I think there’s a message to employees. If you embrace AI in your organization and are an organization that says, “Hey, we do want to embrace these technologies and make your jobs easier, we want to give you opportunities to do different things. We want to free up maybe some of that time you were spending doing some tasks that you didn’t want to do,” that gives them opportunities to do different things. I think that’s a positive message.
One of the reports that insightsoftware ran was we find that data teams and finance teams spent a day a week just doing reporting and interesting, but can get a little slow. That could be a little boring at some point. So you do want to make sure that if you’re an employee saying, “I don’t understand why we couldn’t just have AI doing this part of my job that I don’t really like doing.” I think embracing that is actually a message to the organization and helps you retain people if you can demonstrate that.
So there’s some scariness and jobs going away kind of thing about it. But I think there’s opportunities here to really leverage AI in an organization and big things that people should be working on, particularly in HR department.

Amanda Razani: This brings so many questions. So you shared so much there, so let’s try to go back and dissect a little bit. So let’s go back to the staffing issue. So there’s going to be that upper level AI skill that’s needed, and that’s going to be a recruiting and a staffing issue. And then there’s the lower level where you say it would be great to train and skill up current employees or bring in employees with all the characteristics and traits that could learn these skills very easily on the job.
So there’s two different things there to dissect, I guess. How would business leaders go about recruiting and staffing for these higher level skills? What’s the solution there? And then how do they implement a training program to skill up current employees or employees that they want to hire that don’t have those skills?

Laura Hanson: Well, there’s a couple things there I think you can talk about is not every company needs machine learning expertise. For example, you might not need to have a duty. We’re a technology company. Obviously we do need some of those resources, but one of the common models is really to hire and focus on what the hire is. We’re not going to hire 20 people with AI skills. We’re going to hire the ones that we really need and then employ like a train the trainer or employ people who can bring others along and teach them skills.
So if you can get a couple people that have those types of skills in your organizations, I think that helps balance out balancing the pulling in some people from the outside, but also training them. And to deploy those, you really can. I think, not to generalize, but I think technologists, you don’t have a natural urge to learn new technologies and tons of those architecture guilds and things where you can actually train other technologists. They can jump in and they love that stuff.
So I think there’s a real opportunity to focus on what absolute people you need coming out of the marketplace and then which ones can you build from a train the trainer component? And that’s where you need to leverage some of those people who have that expertise in order to replicate that knowledge and then share best practices and stuff. And it works pretty well I think because you have such an appetite for learning from some of those people that it works well to do it that way.

Amanda Razani: Wonderful. And then as you were saying that human element is still so important and AI is more of a tool to be harnessed. And as some of those, that’s interesting how you said, “We still are in an age where while some of these employees are staying, are they really invested,” and removing some of those really mundane and boring, inefficient tasks and replacing those tasks with AI handling those. And that does free up more opportunities to interest the employees, bring their interests back in and give them other challenges and opportunities.
So as we use AI for a lot more tasks and it’s going to open up new tasks and new positions. And so, where do you see the future in regard to AI and as we implement more and more technology in general, where’s the future going as far as positions that are going to be eliminated, but new positions that you foresee being created?

Laura Hanson: I don’t know if I think that many positions are being eliminated. Maybe in some industries they are. There are some that’ll be. I think parts of jobs will be eliminated and so that you can choose from.
So in the example I was using with support teams and tech support teams, that level one, sometimes level two technical support that can be handled by a bot. You could then have those people doing proactive outreach to customers and shifting the work away from that kind of receiving questions to outreach to customers and shifting more to checkpoints with customers.
So I think that that’s the difference is that we’re going to see a shift away from doing some of those manual tasks to doing tasks like more customer engagement, like more problem-solving, like more consultative work with customers. I think there’s also going to be a need for audit too.
And I feel like this is a little bit akin to sometimes when teams offshore work to different places and they’re like, “Oh, the work’s going away.” Actually, your job shifts from doing some work to maybe auditing work. So all those kind of skills around critical thinking and problem-solving and contextualizing will come into play. So I don’t know if I could say all these jobs are going to go away. I do think there’s going to be a shift in a lot of jobs to free up parts of them to do other work, if that makes sense.

Amanda Razani: Okay. Yes. And so earlier you also mentioned that there is some opposition to the implementation of AI. Even though we’ve all been using AI, we may just not have known we were using AI until it became a bigger thing in the past year and everybody became more aware with OpenAI and ChatGPT and such. But AI has been around a while. We’re using it, we just didn’t coin it as AI necessarily.
So for business leaders who are currently in change management projects where they’re trying to implement technology and digitally transform, as a human resources leader, what’s your experience as far as opposition and how can business leaders meet that opposition and get everybody on board for these changes?

Laura Hanson: Mm-hmm. Yeah. Change management. Wow! That is such a big one for every technology that comes into an organization and people do go through a change curve. There’s the letting go of the old getting to the new, and there’s a dip in that where they come out of the change and it kind of accept the new, and people go through that change curve at different rates. Some people are, you want to hold on to the old because it’s comfortable and that’s human nature. Some people be really out in front, early adopters. You have that with customers too. And I think the message is to, one, recognize that people are in different parts of a change curve. If you can keep a focus on the true north, like what’s in it for the people and what’s in it for the organization, that helps. Now, that said, there’s always people who are slow to adopt change, and one of the ways that you can help is identify the people who are working through that change curve more quickly and help them bring others along.
So there is some change components that I think can help organizations in that regard is identifying those people who are going through the change curve quickly, early adopters types, help them be kind of the … Demonstrate, “Hey, here’s what it did for me,” or, “Here’s how I used it, and help them bring others along.” But leaders going through that should recognize that people go through this very differently. Sometimes it’s out of fear to let go of and you’ve got to just address your strategies accordingly. Talking to people who you may asking them, “Why are you …” Maybe it’s like, “My job’s going away. I’m nervous, I’ve got a family to feed.” And helping them think through and picture, what’s it going to be for them in the future? It’s much easier to keep people than to go hire them.
And so, “We want to keep you, we want to help your skill set, we want to bring you along.” So really focusing on, one, the big picture, the true north for why we’re going through this change. But then also targeted strategies for helping people get through the change curve. Change is consistent through organizations. So that’s a big part of any change is recognizing those people and where they’re at.

Amanda Razani: Okay. And then more specifically from your finance industry experience, what do business leaders need to consider as far as the cost of implementing AI and how do they know if implementing AI or any technology is going to be a smart decision financially?

Laura Hanson: Yeah, that’s a good question. I think that there are opportunities to measure productivity. So for example, that one study I cited that InsightSoftware had done is if our teams are spending, if our finance teams are spending a day a week reporting and you’ve got five people doing that, you can measure that productivity. If we implement AI and say, “Hey, this tool can do this for you,” and cut it down to a half a day,” then you can measure that productivity.
So there is a return on that, particularly in those areas where you can … Customer support is like that, too. You can measure ticket time and how many people you’ve got. And honestly, I think it’s not just the cost of it, but it’s avoiding adding more people sometimes and looming reception. Lots of people who are not adding jobs and they’re worried about it, and yet you want to do more work. You want to grow your business.
So if you can measure how many people you can even save, adding people, do more with less people, that’s another element of it. So it’s not just maybe just straight productivity. We can cut our days to reporting down from five days to four days or one day to one half a day. But also can we avoid adding jobs because our business keeps growing and a lot of the manual work is. So I think there’s a couple ways to look at the return and how to see the benefits of AI and any technologies in general that help improve productivity in that regard. It’s like you can look at it from a couple of different ways as the return on the investment there.

Amanda Razani: Okay. Absolutely. So if there is one key takeaway you can leave our audience with today, what would that be?

Laura Hanson: I would say to embrace AI and what it can mean for your organization and your people skills and helping them build their careers and how to get your organization to be even better. It can be scary, but if you can embrace it and think about, “Okay, now what does this mean for everybody,” in a positive way, then I think there’s lots of opportunity.

Amanda Razani: Wonderful. Well, I want to thank you for coming on our show and sharing your insights with us today.

Laura Hanson: Thanks, Amanda. Great to be here.