Workday Podcast: What’s Next for the Insurance Industry

Is the insurance industry ready for the next stage of AI and machine learning? We talked with PwC’s Rima Safari about insurance trends, opportunities, and challenges.

Audio also available on Apple Podcasts and Spotify.

The insurance industry has been using AI and machine learning for a while, mainly for underwriting and operations. Now insurers are exploring new use cases for AI that can help them transform their firms. 

According to Rima Safari, partner in the insurance advisory practice at PwC, we are at an inflection point for end-to-end AI transformation. Rima predicts that AI will impact every function within insurance, from sales, claims, and customer service to HR and finance.

I’m your host, Rich McKay of Workday. In this Workday Podcast, Rima and I talk about insurance industry trends, opportunities, and challenges. She shares insights from years of experience leading business-wide transformation in the insurance industry.

Here are a few highlights from Rima, edited for clarity. You can also find our other podcast episodes here.

  • “The talent that leverages AI and learns how to best use it to make their jobs more efficient are going to be more successful than ones that don’t. In this case, it’s no different from any other technology that has come up in the last several years.” 

  • “Insurance companies have data coming from a multitude of different sources, and it’s structured as well as unstructured—including policy documents, claims notes, medical record forms, etc. The large language models can analyze these and translate them into simple human language. They can classify and prioritize this information, too.”

  • “By showcasing a commitment to employee well-being, digital adoption, and work-life balance, firms can differentiate themselves as the employer of choice. Even from one of our latest U.S. PwC Pulse surveys, we found that almost 65% of employees are looking for new jobs, and over 60% of them are paying more attention to the benefits that their employers offer.”

Rich McKay: The insurance industry has been using AI and machine learning for a while, mainly for underwriting and operations. But with the recent buzz about these technologies, insurers are exploring new use cases for AI that can help them transform their firms. 

According to our guest Rima Safari, Partner in the insurance advisory practice at PwC, we are at an inflection point for end-to-end AI transformation. Rima predicts that AI will impact every function within insurance, from customer service to HR and finance.

I’m your host, Rich McKay of Workday. In this Workday Podcast, Rima and I talk about insurance industry trends, opportunities, and challenges.  

Thank you so much for joining us today, Rima, and welcome to the podcast.

Rima Safari: Thank you, Rich. It's a pleasure being here.

McKay: Thank you. And could you share a little bit about yourself and your background before we begin?

Safari: I'm happy to. Yes. So hi, everyone. I'm Rima Safari. I'm a partner in our insurance advisory practice at PwC. I partner with our clients to solve some of their most complex issues, mainly focused on technology strategy, digital transformation efforts, as well as major claims transformations. Just a little bit about my background. I'm an engineer by education, and I'm a consultant by trade, as you know. I'm a first-generation working mom in my family, and it's a dual-career household. So things like employee benefits, things like insurance, like absence management, paid leave, are really near and dear to my heart. And I'm really excited about what the insurance industry has been doing so far and has also planned ahead in this space.

McKay: That's fantastic. You just definitely bring a lot of good personal and professional perspectives to this conversation. So excited to hear them. And can you set the stage for us and share some of the trends you're seeing in the insurance industry?

Safari: Yes. What I would say, Rich, is I've been leading the GenAI. I'm the sector champion for GenAI for insurance. What that means is I've been driving a lot of our thought leadership in this space, as well as client projects. This gives me the opportunity to look at what insurers are doing currently and where they're investing in as we look at 2024 and beyond. And I would say it impacts every single function within insurance because insurance has a lot of structured and unstructured data coming in. So if you think about customer service, for example, people are often classifying and documenting knowledge after a call, then they're trying to submit it to the system. GenAI could create almost 50% efficiency there. Even in claims, GenAI could help with the actual collecting and analyzing information for the claims adjudication decision. They could also help generate the letters, which typically, currently, I've seen carriers spend almost 15 minutes on a letter, sometimes. That could go down to a minute or even seconds. Even in underwriting, you could create hyper-personalized coverages.

So overall, I think GenAI can help automate a lot of the repetitive and time-consuming tasks, whether it's related to claims or billing or customer servicing. And then the whole other aspect of it is around building virtual assistants, because if you think about it, so much of what customers expect now from any of their interactions is very similar to what they see with an Amazon, or an Uber, or others. They're looking for simple, intuitive, personalized experiences, and I think GenAI can be used here to build virtual assistants to provide really easy advice around insurance. Think about it during enrollment, for example, or even resolution to customer queries. So that's a little bit of different areas where GenAI would be helpful. I would also say it impacts some of the enterprise functions. So whether it's the finance function, whether it's the HR function, we are seeing tremendous use of GenAI in terms of the different use cases. Every place where there's heavy data involved, it is driving tremendous impact.

McKay: Yeah. That's so interesting. And you mentioned the structured, unstructured data, and just trying to wrangle all that data and make sense of it is such a huge opportunity still. I know I've been doing this for a while, and we've talked about it years and years ago, but it seems like we're kind of at that point where even AI and ML is ready to help with that. 

And so with all the hype around AI and ML, artificial intelligence and machine learning, are there other ways that can impact insurance? [Are there other?] big opportunities with this technology? And how can insurance use it now?

Safari: Yeah. So Rich, that's an interesting one, right. I would say that the biggest opportunity is going to be in business model reinvention for insurance carriers, and I'll talk through what I mean by that. But AI solutions and even machine learning has been deployed across the insurance industry for a while. Mainly, it's been in underwriting or in operations. However, true end-to-end AI transformation is yet to come in the industry, and I feel like this is an inflection point for that because this is not a brand-new technology. We talked about machine learning having been here for over a decade. But still, there was a lot of manual activity involved in insurance, especially because most insure activities are around unstructured data, whether you think about claims notes, whether it's medical record forms and ingesting information out of that, or even the plan provisions or coverages that are many times in very large PDF documents of the actual policy itself to evaluate underwriting risks and analyze it. Insurance companies have data coming from all these different sources, and it's structured as well as unstructured. The large language models can analyze these and translate them into simple human language, like chat or text messages or even a simple summary. They can classify and prioritize this information, too. So they can take into account, what is the type of policy this customer has, what is the nature of the loss, and what is the eventual impact of the policyholder and explain it to them in simple, easy, intuitive terms, especially because the amount of data that's available to insurers right now is enormous, and it's growing year over year.

So the winners here are really going to be ones that are at the forefront of this, understanding how this data can be used to drive value. And from a business model reinvention perspective, right, what I'm thinking is if you could completely change the way you interact with your agents, your brokers, and your customers using GenAI, whether that's driving speed to market. So for example, if it was in the group insurance space, if it would take me three-plus weeks, sometimes two to three weeks to respond back to a quote request, if I can get that within a day, that's completely reinventing the model. That reduces and potentially even eliminates several steps in the process so that you can get back to the broker faster and make the sale happen sooner. I also see new types of ancillary services in addition to insurance products being available to customers as part of this. So for example, if the insurance carrier was trying to sell short-term disability or long-term disability or other types of insurance, now based on the data they have, can they also sell supporting services, whether it's related to behavioral health, whether it's related to diabetes prevention, right, other preventative care services that they could partner with and offer to the customer based on their personalized needs? And that is where I think GenAI can play a huge role in analyzing that information and making it available for the carriers to either drive efficiency or growth through new products.

McKay: So switching gears, so less than 25% of the insurance industry is younger than age 35. So how can firms address the current and future talent shortages, and what role does employee experience and technology play in attracting and retaining talent?

Safari: Firstly, fostering and enriching employee experience is paramount in today's day and world. This involves creating a workplace culture that values diversity, inclusion, and professional development. So offering programs that are about continuous learning, offering avenues for career progression that can significantly enhance the appeal of the insurance sector to younger professionals is going to be really important. And by showcasing a commitment to employee well-being and work-life balance, firms can differentiate themselves as the employer of choice.  So the employee experience, I would say, is extremely important, more so today than it was ever before. And then simultaneously, the cutting-edge technology these days that we have, right, plays a pivotal role in attracting and retaining this talent. Because if you think about it, by 2030, a vast majority of the workforce will have grown up with cell phones. They would have always had a smartphone around them, and they will demand robust digital capabilities from all of their providers, just like I talked about with an Amazon or Uber or others

The younger workforce is inherently tech savvy, and they're integrating these advanced technologies, like the artificial intelligence agents, data and analytics, and digital platforms, not only to modernize some of the practices that were existing in the past. So say if we were using a ton of manual Excel work, that moved from the Excel to using macros. Now, we are changing that from macros to actually using AI to turn something that would take hours or minutes into it being done in seconds by this younger demographic. So I see a lot of automation of routine tasks that can free up employees to focus more on strategic, fulfilling aspects of their roles, something that's truly thought-provoking and requires critical thinking, thereby creating a much more engaging and dynamic work environment for them. So I think technology and the overall employee experience is extremely important. The synergy between them, you can't deny that, right. As the industry evolves, I think most firms should be embracing a progressive mindset. I'm not saying go all in on AI without thinking through the risks associated with it, but be a cautious adopter, right. Be open to progress, even though you might be cautious about the process involved there. Take the right steps from a responsible AI standpoint to implement it, but still be open to the progress associated with it.

McKay: Absolutely. And I think that's an excellent way to put it. With all the technology advancements, I think, sometimes, there's fear involved and uncertainty, but the way you put it is kind of a complement to people and freeing them up from what might really be tedious work or manual work. This allows them to really focus on more strategic endeavors.

Safari: That's right. Exactly. And that's why we're seeing a lot of these-- the advent of these co-pilots or assistants coming into picture this year. The whole idea is, "Could I leverage AI to do my job in a way where I'm reducing any of the administrative effort?" So it's like hiring your best new hire. They can still do the easier tasks. They can help make you more efficient, but it's not going to do the critical decisions for you. You still have to make them on your own. And I think that is a key difference, too. I hear a lot of concern about what is the impact of AI to our workforce? And what I would say is, it's going to be all about learning and development. The folks that leverage AI and learn more about it to make their jobs more efficient are going to be more successful than ones that don't. It's no different from any other technology that has come up in the last several years. Whether it's personal computers or others, the idea is, "How do you leverage this to make yourself successful?"

McKay: Excellent. Yeah. Thank you. And shifting gears again, could you talk about PwC's alliance with Workday and how that has helped customers?

Safari: I sure can. So PwC has a very strong alliance with Workday, and I'm very proud to say that we are strategic partners together and have helped many of our clients. One such example I would take is in the group insurance space. So while we work with insurance carriers to introduce new products in the market or to drive higher enrollment, many of those carriers, their customers are employers. So think about a large employer, like PwC or others. And these employers are using Workday as their HRIS platform. And what happens is, currently, the customer or the plan administrator on the employer side has to go to multiple portals to understand their data. If I wanted to know-- if an HR manager wanted to know, "Who are all the people in my team that are going out on leave?" I'd have to go to the insurance carrier to understand that and look at their employer portal. I might have to go to Workday as well. I might have to synchronize all that data. And what we've done is we've worked with a couple of carriers to say, "How do you provide the right data exchange seamlessly between Workday and the insurance carrier so that it benefits all of the customers, so that we can really reduce the burden on the customer, especially for things, for example, like the number of new hires or fires?" right. Currently, you have to manually submit Excel files for the insurance carrier to know that, and then the insurance carrier will update their information and their billing procedures. And instead of that, if you can do it through APIs in a seamless manner, then it's a win-win because it's happy customers for Workday, as well as for the insurance carrier. So that's just one real-life example of how we are partnering with Workday, with our insurance carriers, to solve truly relevant problems in the current industry and landscape.

McKay: Awesome. Thank you. So for the last question, I usually like to be more future-focused. So based on the conversations that you're having with insurance leaders, what do you think the future of insurance looks like, and what world do you see technology like AI and ML playing in it?

Safari: That's a great question, and I feel like all of us have been thinking about that a lot, not just the future, overall, but also, what are some predictions for 2024, in particular, and then how do they evolve going forward? I would start by saying, as an industry, we have a moral obligation to do more with the data than just let it sit idly in our archives. For all insurance carriers, there's a moral obligation to use it to make the policyholders safer, healthier, and wealthier. The ultimate purpose of data and insurance is to save and lengthen lives, and it is the one thing in our power that will help this industry, overall. So in the future, I really see insurance carriers harnessing their data to support customers during their most important life events. And when I say life event, it could be somebody is about to have a baby, and they have insurance tied to that. They are about to go out on leave to take care of a sick family member, or they just had an accident, and they need somebody to be there for them during that time frame. These are all major life events. Every time somebody calls an insurance carrier, it's probably not a good day. So how do you make that event simpler? How do you make the experience more intuitive and easy to follow?

So just as an example, right, let's imagine a scenario for an insurance customer named Tina. Let's say in the future, Tina is looking to purchase a car insurance policy in the GenAI world. She interacts with an AI-powered virtual assistant specifically designed for these types of queries. So as Tina simply speaks, and she's speaking in her layman's terms, and she speaks to her requirements, the virtual assistant can understand exactly what she needs. I mean, this could get even more complex when you talk about all the voluntary benefits products, like an accident product or a hospital indemnity product or critical illness, right. It's very difficult for the average consumer to understand what is the difference between these products, but if they could just describe their needs, the virtual assistant could understand based on understanding the natural language and processing that and engage in a conversation with Tina to gather all the relevant information and understand her preferences, that would be huge. Because in today's day and world, you have somebody talking to her, capturing all of that, taking notes, summarizing notes, and feeding it into the system. And instead of that, you could have this vast knowledge base of information that you just collected and access to real-time data, and the virtual assistant could quickly process this information and provide personalized insurance coverage options. It could also compare multiple policies. Like if it's an individual insurance, it could compare multiple policies from different insurers and educate her or guide her in terms of coverage limits, in terms of deductibles, or premium costs that are not always easiest to understand for an average consumer. It could also provide visualization or simulations to demonstrate what the different claim scenarios could be should she have a question about that. Then impressed by that, she could purchase a policy, and then all her interactions could be associated with that, right.

Say, for example, if she has an accident, and now, she's trying to figure out. And she calls her employer. She lets them know she will need to be out of work for a few days. Then she calls her insurance carrier, and she says she will need to file a disability claim, and she might require she had access to the accident product that she had bought. So now, she's going to need support for that as well. She might call up her car insurance carrier and provide pictures of the actual incident itself. It's such a stressful process right now, and all of that could be simplified. And it could be tied to simple payments that are directly in her bank account. So I see the whole insurance sales process, as well as the claims process, being much more efficient, seamless, and stress-free for the customer in the future. And I'm really hopeful, and I can't wait for that day when that happens when we can see insurance carriers being as easy to work with as you do with a lot of the other consumer retail sites or providers.

McKay: Yeah. That is excellent. And I love the idea of kind of a moral obligation to better use the data because you're right. It is an incredibly stressful part of a customer's life, often, when they have to rely on insurance. Or even when they're thinking about the insurance, there's so many things that are going on. And I just love trying to make that easier, more seamless. Anything we do using technology to help with that, I think, reduces so much headaches.

Safari: Exactly. Exactly, Rich. Yes.

McKay: Okay. Well, thank you for joining us today, Rima. And thank you for this amazing conversation. I'm so happy we could talk.

Safari: Likewise. Likewise. I think we're in a really exciting phase right now, and this space is going to continue to evolve. So let's stay in touch. And I'm sure we'll have more predictions on how insurance carriers are leveraging AI to make it easier for Workday and insurance customers.

McKay: We’ve been talking about the future of the insurance industry with Rima Safari from PwC.

If you enjoyed what you heard today, be sure to follow us wherever you listen to your favorite podcasts. And remember you can find our entire catalog at Thank you for joining us and have a great workday! 

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