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FORECAST 2026: AI Outlook

Author

Tammy M. Appel
Contributing Editor
LIMRA and LOMA

January 2026

We asked our FORECAST 2026 panel of executives how artificial intelligence (AI) — including generative and agentic AI — shapes their business strategies today, and where they see its greatest future potential. Their responses illustrate just how deeply transformative this technology has become, with many executives emphasizing how extensively AI is now embedded in their operations.

“AI has emerged as an enabler of execution excellence at RGA,” says Ron Herrmann, CFP, EVP, Head of Americas, Reinsurance Group of America (RGA), “empowering our workforce and creating new growth opportunities.

We have expanded our capabilities by adopting best-in-class enterprise technology, upskilling employees, and integrating market-leading external resources, and prioritizing new business opportunities that have emerged.”

Other leaders echoed this sentiment, highlighting how AI is driving efficiency and unlocking new opportunities across their organizations. Executives shared specific examples of how AI is reshaping operations.

Operational Impacts

“AI/agentic AI has been introduced throughout the organization and is becoming a larger part of our business strategy,” says Denise McCauley, President & Chief Executive Officer, WoodmenLife . Some examples of WoodmenLife’s broad use of AI are Microsoft AI tools, including those used by technology (GitHub), and the Copilot version of chat, as well as M365 Copilot.

AI is now embedded into how Guardian works every day as well. Kevin Molloy, Chief Financial Officer, Guardian , lists some of the key functions across which the company has deployed AI tools:

  • Finance for variance narration and board-ready insights

  • Actuarial for summarizing experience studies and testing documentation

  • Distribution for drafting proposals and content

  • Operations for handling emails, chats, and call wrap-ups

  • Compliance for policy mapping and evidence retrieval

“This is only the beginning,” says Molloy, “but we’ve seen AI free up time for colleagues for higher-value work.”

F&G and Allianz Life also point to productivity gains realized by using AI.

“We have adopted AI across the organization and are finding productivity opportunities in virtually all departments,” says Chris Blunt, Chief Executive Officer, F&G.

Like F&G, Allianz Life has deployed enterprise AI solutions to all employees to that end. According to Jasmine Jirele, President & Chief Executive Officer, Allianz Life Insurance Company of North America, examples of enterprisewide deployments include AllianzGPT and Microsoft Copilot. Allianz Life also has implemented various business-specific AI solutions that drive growth in Distribution and Marketing, reduce risk in Ethics and Compliance, and improve operational efficiency. Jirele says an example of “a business-specific solution is SmartCalls — a next-best-action solution that uses data and AI to surface the best sales opportunities with the most impactful messages to the right people at the right time.”

At New York Life, AI has evolved from a series of pilots into a core part of how the company operates and grows. “What began as efforts to streamline underwriting and service,” says Aaron C. Ball, EVP, Head of the Foundational Business, New York Life , “has become an enterprisewide transformation — improving efficiency, accelerating decisions, and creating more personalized experiences for clients and advisors.”

Process Improvement

As AI adoption accelerates, insurers are finding practical ways to embed it into core business processes.

“AI already plays a role in our business strategy,” says Robert M. (Bob) Jurgensmeier, Chief Executive Officer, Ameritas Life Insurance Corp. The company’s early efforts focused on leveraging AI’s potential value to change its cost curve and to enhance customer experience. Jurgensmeier believes that AI-enabled and reimagined business processes represent the greatest potential. Ameritas has “taken one function and road-tested that concept to help gain practical understanding on how to re-engineer using AI, as well as provide guidance on how to replicate that to other areas,” Jurgensmeier says. At this stage, the company has implemented a number of AI tools and solutions, including GenAI, early-stage agentic AI, algorithmic AI and machine learning (ML), and AI that is embedded in existing applications and systems.

While Ameritas emphasizes re-engineering processes, other companies are applying AI to enhance existing capabilities.

“AI is the natural evolution of the data and advanced analytics journey we began years ago,” says Matt Berman, President & Chief Executive Officer, Foresters Financial . “We’ve long embraced algorithmic solutions and machine learning to improve underwriting, pricing and product design. Generative AI (GenAI) simply expands that capability.” The company is focusing on practical, high-impact applications, using AI to streamline underwriting, strengthen risk insights, enhance service, and help advisors provide protection to families faster and easier.

Reinsurers are also leveraging AI to push the boundaries of underwriting innovation.

“AI is at the heart of what we do, especially in underwriting and risk assessment,” says Marc Giguère, President & CEO, Munich Re Life US . At the moment, the reinsurer is deeply focused on aligning its innovation and efforts to deliver underwriting decisions that not only are faster, but also smarter, powered by digital health data and AI. Munich Re’s alitheia platform, which was recently granted U.S. patents for its innovative technology, “exemplifies our commitment to technical excellence and industry advancement,” says Giguère. “These patents recognize alitheia’s unique capabilities in ingesting and analyzing digital health data to improve and speed decision making in all underwriting scenarios.”

These examples underscore a common theme: AI is transforming operations at every level.

Widespread Use

Executives also are reporting that their companies are leveraging AI throughout their organizations to automate, streamline and simplify key processes.

In the near term, State Farm views AI as a tool that can help its largest operations become more efficient by automating and streamlining repetitive tasks. “We are seeing dividends from traditional AI solutions in Life Underwriting and Customer Service,” says Sarah Mineau, SVP, Financial Services, State Farm. The company currently is investing in generative and agentic solutions in operations, marketing, distribution, and IT. “We’ve had some traction,” she notes, “but as the technology — and our use of it — matures, we expect the impact to grow to every part of our business.”

Beyond efficiency, companies are using AI to elevate the customer experience with speed and precision.

Currently, Aflac is focusing on the use of AI to improve speed and quality, particularly in its claims experience, according to Virgil R. Miller, President of Aflac Incorporated & Aflac U.S. “Aflac is leveraging machine learning and AI to help automate the adjudication of certain benefits to provide a faster and more consistently accurate experience for our policyholders,” he says. Aflac U.S. also is rolling out a version of GenAI-enabled support for employees to boost internal productivity and efficiency in a secure environment, while helping the workforce spend more time on high-touch customer experiences.

A growing number of companies are building enterprise-level AI ecosystems to drive efficiency and innovation.

"AI and GenAI are deeply embedded in our business strategy today,” says Wade Harrison, Vice Chairman & Chief Operating Officer, Protective Life Corporation . Protective currently operates more than 40 AI tools across the organization, supporting functions such as human resources, the IT service desk, and its Life & Claims Centers. These tools enable critical use cases including knowledge management and search, document summarization for underwriting, claims document analysis, and developer assistance for coding tasks. “Building on this foundation, we are expanding Copilot adoption to deliver value in marketing, compliance, IT, investments, and legal, enhancing functional support across the enterprise,” Harrison says.

For others, AI adoption builds on years of strategic investment in data and technology.

One example is MassMutual. For more than a decade, MassMutual has been integrating data-driven decision making and new technology like AI into its strategy. “We have made significant investments in our AI capabilities, buying vendor solutions as well as building our own proprietary tools that have enabled us to streamline processes, create efficiencies, and make it easier to do business,” says Paul LaPiana, CFP, Head of Brand, Product & Affiliated Distribution, MassMutual .

Some insurers are gradually introducing GenAI, starting with focused use cases to gauge effectiveness.

“All managers, directors and officers utilize Microsoft Copilot,” says Jerald J. (Jerry) Lyphout,President & Chief Executive Officer,Modern Woodmen of America.

“We have identified many use cases for GenAI and have implemented the technology in low-impact areas at this time. Approximately 20% of the software generated using AI is accepted and utilized.”

Lessons Learned

Some executives also shared the lessons they have learned from the adoption of AI.

“One of the most important lessons we’ve learned is that technology alone isn’t enough; success requires a cultural shift to a ‘data-first’ mindset and disciplined, informed decision making,” says Harrison . “Our Enterprise Enablement organization plays a key role in aligning business and IT to ensure we solve the right problems with the right mix of processes, technology, behaviors, and programs.” Early wins are already visible in automation and simplification, and leaders are encouraged to identify broken processes and implement solutions quickly.

Berman also emphasizes the importance of culture when implementing AI, saying, “If there’s one lesson we’ve learned from previous waves of disruption, it’s that adaptability is as much about culture as technology,”says Berman. “The same mindset that helped us navigate the rise of Fintech and Insurtech now guides how we embrace AI, with curiosity, discipline and an emphasis on creating lasting value for our members.”

Giguère emphasizes that innovation must be balanced with integrity, particularly in terms of data protection and trust; thus, Munich Re is prioritizing transparent and ethical frameworks for AI governance. “One important lesson we’ve learned,” he says, “is that AI requires collaboration, iteration, and a deep understanding of both technology and human context.”

“A key lesson learned from our AI journey has been the importance of bringing our employees with us as we expand usage of AI,” says Jirele . “From AI literacy training for all employees to AI Innovation Week, where we demonstrated the potential for AI to transform our industry, our employees are prepared to help us shape the future of our company in the age of AI.”

“While friction points remain, such as embedding tailored AI solutions into mature architecture,” says Herrmann, “we believe the opportunities far outweigh the challenges.”

The takeaway is clear: AI is poised to transform the insurance industry, driving significant advancements across every aspect of the business and reshaping how insurers operate, engage with customers, and manage risk.

Future Outlook

Some of our panelists shared their perspectives on where they believe AI holds the greatest promise for the future.

“We are very excited about future advancements in AI, in particular the opportunity to leverage AI tools that can improve experiences for our customers, financial professionals and our employees,” says Jirele.

“Looking ahead, the greatest potential lies in scaling AI to transform customer experiences, drive operational efficiency, and embed intelligent insights across every function,” says Harrison . “AI will continue to be a catalyst for innovation, enabling us to deliver greater value for customers, partners, and employees.”

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