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Moving Research Forward With the Help of AI

Author

Bryan Hodgens
Senior Vice President, Head of Research
LIMRA and LOMA
bhodgens@limra.com

September 2026

The rapid technological advances happening in the workplace are not slowing down. Tools like artificial intelligence (AI) are more valuable now than they were even a year ago and can be a strong component for an organization’s research capabilities. As AI continues to evolve and get smarter, the way our industry generates, validates and applies its findings and insights must evolve too.

Although AI can be a productive tool in research conversations, the human element remains indispensable in interpreting data and generating meaningful insights.

Determining how to integrate AI into a company in a smart and ethical way remains a priority. Yet, the future of conducting research and gaining insights is clear: Successfully integrating AI into the research process will not only streamline workflows but also help researchers generate more strategic and impactful insights.

AI Tools

In 2026 alone, AI has improved in how it thinks and delivers content. Tools like digital twins can be utilized to create personas of consumer behaviors, mimicking themselves from the data used to build the customer profile. Creating digital personas enables researchers to develop and evaluate multiple scenarios across different hypotheses.

Other AI resources have become powerful tools for cleaning and augmenting the data, improving efficiency. Training your AI to look for specific details in the data can eliminate some of the more tedious tasks in the research process. What many AI tools have demonstrated is their ability to create structure within research projects, allowing some aspects of research to be automated while freeing up time for those working on the project.

AI can also give organizations a baseline understanding of relevant trends and data. When you have a foundational understanding of your ideas and the data to support them, you can develop those into more advanced research projects that uncover new opportunities for organizational growth, supported by AI-driven insights.

People Power

As impactful as AI can be, we cannot forget how crucial it is to have humans remain at the center of industry research. Because AI is often pulled from resources that already exist, biases and stereotypes can occur in its findings. Additionally, AI tools often do not have access to industry-specific or proprietary data that can help inform research insights. Misinformation is not new, but it can spread more easily through the sources AI uses to generate its findings. Having individuals read through, process and understand the data is imperative in combatting misinformation and biases in the research process.

Human oversight remains essential to ensuring the quality and integrity of the research. Researchers embedded within the insurance and financial services industry also carry a knowledge of the space that AI cannot match, which makes the human element even more valuable. When going through data or reviewing the findings, a human researcher can pause and question whether something makes sense, could be improved, or is incorrect.  

A Winning Combination

Industry research becomes even more impactful when the power of AI is combined with human expertise.  Together, they provide the tools, data and insights needed to strengthen every research project.

“The future of impactful research lies at the intersection of advanced technology and human insight. Integrating AI and emerging data capabilities allows us to move faster and uncover deeper patterns, but it’s our commitment to human context, empathy and industry expertise that turns those insights into meaningful action for your organization,” said Lai-Sahn Hackett, corporate vice president, Applied Research Solutions, LIMRA and LOMA.

When you think about investing in a research project for your organization, you want strategic, actionable insights that answer your original question and clearly demonstrate how the underlying data were used to create the insights. The results should be grounded in relevant data, drawing on prior trends and analysis related to your research project, while providing guidance and input on what the findings mean. That can only be achieved by bringing together the power of AI with human expertise throughout the research process.

Conclusion

Our industry is evolving — with organizations thinking of new ways to approach distribution channels, testing new product concepts, exploring new markets and more. Assessing whether to make these changes based on research and data is still as important as ever. Because of this, our way of approaching research must also evolve.

When we combine the strengths of AI technology with traditional research methodologies, we can achieve more powerful results. This combination can generate insights that expand what is possible in our industry, identify new opportunities to achieve organizational goals, and provide the data needed to support sound decision making. Understanding both the strengths and limitations of AI in the research process is crucial for its successful integration.

Our session at LIMRA’s Annual Conference happening later this month will continue exploring how to bring together research strategies and AI tools to create more advanced insights, the considerations organizations should be aware of, and why maintaining the human component of research is essential. Join Sean O’Donnell and me on Sunday, September 27, at 4:30 p.m. for The Future of Insights: Research in the Age of AI.
 

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