The Road Ahead: AI Decisioning 2026

Mark Sidlauskas: Hi everyone! Welcome to the Sapiens Insurance 360 podcast. I’m your host, Mark Sidlauskas, Director of Marketing at Sapiens. I’m glad that you’re out there listening. This is where we discuss the latest news, trends, and issues from across the insurance solutions and technology spectrum. And our latest episode, “The Road Ahead: AI Decisioning 2026,” starts now!

The countdown to 2026 has begun in earnest, and for insurers across the industry, 2025 was a year that saw AI transition from experimental pilot programs to production-ready decisioning systems, from underwriting to claims processing and fraud detection, AI and AI decisioning. We’ve moved past the buzzword phase into everyday usage, yet significant questions still remain — how do we ensure AI decisions are explainable and compliant? How do we balance automation with human oversight, and how do we build trust in systems that are reshaping the very foundation of insurance decisioning? With regulatory scrutiny intensifying, data quality challenges persisting, and competitive pressure mounting, 2026 may be the year that separates the leaders from laggards in AI decisioning adoption.

With us today to help us look back at 2025, and the road ahead in 2026 for AI decisioning is our special return guest, Sapiens’ own Rafael Goldberg. Rafi heads up Sapiens Decision and brings 20 years of experience in product strategy and delivery. Rafi, welcome back to the show. It’s been a while, but you’re here now to walk us through the year that was. And the year that will be for AI decisioning.

Rafael Goldberg: Thanks, Mark. It’s great to be back and really hard to believe we’re at the end of the year. 2025 was definitely a milestone and we’re super excited about what’s to come.

Mark Sidlauskas: Yeah, that’s great. So let’s jump off from there. A lot of milestones were achieved in 2025. Talk to us about what’s happened in Sapiens Decision. Talk about some of the technology enhancements, the market, what’s going on?

Rafael Goldberg: Yeah. So 2025 has been very exciting for Sapiens Decision and the decisioning market generally. And that’s really as you talked about in your introduction, making AI real and combining it with what previously has always been a very declarative discipline. And so the combination of the probabilistic side of the house in AI and the deterministic side of the house in decisioning, is super powerful. And now we’re getting the best of both worlds. We’re getting customers to market quickly. We’re getting insights that previously would take a significant lift in IT to achieve. And [we’re] really seeing the promise that we’ve always had between business and IT when it comes to decisioning, just getting that much more potent. So a lot of milestones in terms of new customers, a lot of milestones in terms of new products, which we’ll talk a bit about. And also, I think just the category itself, the analysts, the major analysts have been releasing some very exciting and major reports on the category. And customers are taking note and realizing that to be competitive, they have to engage in this space.

Mark Sidlaukas: So congratulations on being named a leader in the Forrester Report on AI Decisioning platforms. That’s a huge accomplishment!

Rafael Goldberg: Thanks, Mark. It’s really the great work of the team and the customers who have helped guide us and influence the roadmap. Forrester has done a tremendous job with that report and the competition was great. I mean, that’s a vibrant market where competitors are pushing each other to leapfrog and provide more value to the market. And they really crystallized, I think, the category, they got there early [and] talked about…they’ve named the category AI decisioning. And they really, at the heart of the matter, they talk about [how] enterprises compete on decisions, the ability to make precise, rapid, and adaptable decisions. And that’s really where they focused. And we were very pleased with the Leader status.

Mark Sidlauskas: Great. So before you mentioned some of the capabilities that are being brought to market right now, let’s talk a little bit about that. So what are the new capabilities that really extend what the former decision management had been and make that an AI decision platform? What are some of the new use cases and technologies?

Rafael Goldberg: Definitely. So I think the fundamental aspect of this category is that bringing together of what previously were siloed disciplines. So disciplines in their own right, but siloed, number one. And number two, the application of AI to the decision process. And so really you can think of the three aspects of an AI decisioning platform or AI. And that can be generative AI and as well as traditional AI like machine learning. It’s decision management, which is the evolution of business rules. So you can think of those declarative decision models which are requirements and also code and then finally data and analytics. And I think that piece was really the missing piece in the platform. You can think of data analytics and analytics as previously a very specialized field. Data scientists and the business and IT groups that were creating decisions and deploying them weren’t getting that real-time feedback and the ability to monitor and adapt the outcomes. And now these platforms that are bringing these three areas together are getting a much faster and tighter loop of optimization. And so, we’re very excited about combining these disciplines and the use case, I think, really at a general level, is what I just mentioned, which is number one, using AI to get decision models to production quickly. And number two, being able to get that feedback and act on that feedback rapidly because of the combination of the analytics with the decisioning.

Mark Sidlauskas: So that’s a huge quantum leap from where decision management was previously. Now you can actually use what I would suppose are decision analytics. What’s going into that full decision? All the different sub decisions that have to take place to achieve an outcome and then optimizing on that outcome, whether it’s a set of KPIs or some other business metric, to be able to optimize what that outcome is, that what the platform delivers to customers?

Rafael Goldberg: Exactly. You really hit the nail on the head there. So not only are you getting the observation of the observability of all of that detail, all of that granular detail of what’s happening with the outcome of the decision, but you’re also now being able to optimize and with the application of AI, what we’re super focused on and excited about in 2026 is what we’re calling optimized AI, which is part of our decision AI roadmap, and that is now your AI partner. Your AI agent will be monitoring 24 over seven what’s running in production and based on the KPIs that the business is setting, it’s going to be watching for drift. It’s going to be telling you when things are happening that you may want to take a look. And it’s also aware of the details in the decision architecture, in the decision models themselves. And so it’s able to actually say, hey, I noticed you were getting less people eligible for that product. I think that if you made this change in this part of the decision model, I’ve already done it in the background. Run a production test run and you actually see this percentage increase. So just a really, a quantum leap, as you said in the opportunity for the business.

Mark Sidlauskas: So just looking forward, I think 2026 is going to be the year of the agent. Agentic AI, I think that’s really going to come into place. What you’re describing is that that scenario. So is that going to become real for our customers in 2026? What could we expect down the road?

Rafael Goldberg: Absolutely. It does feel like science fiction, but it is real. It’s here. We’re proving the concept out actively, both in hackathons and in analysis and design work. The frameworks are available and it’s really about, implementing it in a user experience, in a paradigm that makes sense. I think those are fairly well established with some of the available, consumer technology and enterprise technology. And so it’s putting it all together, and I’m very confident that companies will be able to interact with that kind of system in 2026. And it really is a game changer and it’s exciting. I think there’s a lot of questions about trust and about, accuracy, but from, from our work, we see, there’s really an opportunity to have the AI agent as a partner, not as an overlord, if you will, so that that that AI agent is,  really doing the work that we’re already doing as humans, but much, much more rapidly, and it still just is giving the business or the human the ability to review what’s been recommended. Do any testing that we want to and then and then redeploy. So it’s that whole human in the loop governance opportunity.

Mark Sidlauskas: Thanks so much for your insight today, Rafi! As we look toward 2026 and AI decision technology continues to evolve and become indispensable for insurers, it’ll be interesting to see how carriers implement these systems balancing efficiency with explainability, automation with accountability, and innovation with trust. Your perspective on how customers can navigate these challenges gives us a lot to think about as we plan for the year ahead.

To our listeners, as always, thanks for joining us. We have so much more exciting content planned for the rest of 2025 and 2026, and we’d love to hear from you. Connect with us on social media, share your feedback, and don’t forget to subscribe to the podcast, so you never miss an exciting and insightful episode. Until next time, this is Sapiens Insurance 360. Thanks for listening!