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Jun 15, 2026

How AI is Being Adopted to Improve Employee Benefits

In employee benefits, Artificial intelligence is actively reshaping how insurers design, deliver, and manage benefits across the globe. And for multinational employers, that shift matters.

What’s striking about AI in employee benefits is not just the pace of innovation, but how widely it is being adopted.

From Reactive to Predictive

Traditionally, employee benefits have been reactive. Claims are paid after the fact. Trends are analyzed after costs rise. AI flips that model. With advanced analytics and machine learning, insurers can now:

  • Identify emerging health risks earlier
  • Predict claims trends before they escalate
  • Personalize coverage and wellness programs
  • Detect fraud or anomalies in real time

This type of AI-driven automation is already reducing costs and improving efficiency across underwriting and claims processes. 

How AI is Being Applied in Health, Benefits and Wellbeing

What’s particularly interesting is how consistently these use cases are emerging across the industry. According to Ricardo de Almeida, Regional Leader MMB, Latin America & Caribbean Mercer Marsh Benefits has found AI is already being embedded across the full employee benefits value chain:

  • Advanced analytics are helping professionals make more informed, strategic decisions
  • Predictive analytics are being used to estimate future outcomes based on historical patterns
  • Benefit navigation tools are creating personalized recommendations for employees on how to interact with their benefits
  • Customer service models are being enhanced to handle first-line inquiries quickly and efficiently
  • Fraud prevention tools are improving detection of waste, fraud, and abuse

On the healthcare side, the impact is equally significant, where Mercer Marsh Benefits found AI is:

  • Supporting clinical care and imaging, helping analyze large volumes of medical data more accurately
  • Enabling personalized medicine, with treatment plans tailored to individuals
  • Improving operational efficiency by automating administration, triage, and delivery

These are not theoretical use cases. They are already being implemented across markets, fundamentally changing how benefits are delivered and experienced.

In fact, other leading brokers and advisors globally are seeing a clear shift, as well:

  • According to WTW’s 2026 Advanced Analytics and AI Survey, insurers investing in AI-driven analytics are already seeing measurable impact, including improved profitability and stronger premium growth.

  • Aon’s Global Benefits Trends Study, based on input from over 500 global HR and benefits leaders, shows organizations are increasingly leveraging technology and data to balance rising costs with more personalized employee experiences.

  • Lockton’s SME Benefits research found that nearly 70% of business leaders are already using AI to inform benefits decisions, highlighting how quickly the technology is being embedded into day-to-day strategy.

  • In its article, The Future of Benefits: Personalization, AI and Human Connection, Gallagher highlights how AI is reshaping employee benefits through predictive analytics, personalized health and wellbeing support, and more intuitive navigation tools like chatbots, helping employees access the right resources at the right time while improving operational efficiency for employers.

  • HUB International has stated in its Outlook. Employee Benefits, AI has enormous potential to improve recruiting and benefits compliance, as well as develop benefits strategies that improve engagement and employee wellbeing.

AI's Emerging Role in the Benefits Experience

As benefits programs become increasingly complex, helping employees understand and make informed decisions remains a challenge for employers around the world. Artificial intelligence may offer a new way to bridge that gap through more personalized education, guidance, and decision support.  

Prudential's 2026 Benefits & Beyond study, The Future of Work: Navigating rapid AI adoption while building employee trust found strong employer interest in using AI to improve the benefits experience. More than eight in 10 employers (83%) say they are interested in using AI to help employees better understand their benefits. Yet employee adoption remains limited, just 24% currently use AI for this purpose, and only 58% say they would consider doing so in the future. These findings suggest that while AI has the potential to transform how employees engage with their benefits, organizations must first build confidence in the technology and demonstrate its value.

The greatest opportunity may not be automation, but personalization. AI-powered tools can help employees navigate increasingly complex benefits programs, surface relevant information based on individual needs, and provide support when important life and financial decisions are being made. As organizations continue to explore these capabilities, balancing innovation with trust, transparency, and human support will remain critical to successful adoption.

The Cost Conversation Isn’t Going Away

At the same time, global employers are facing sustained cost pressure. Medical inflation remains high and complex. AI is also becoming a critical tool in managing that reality. By improving data visibility and predictive capabilities, insurers can help employers:

  • Better understand cost drivers across countries
  • Optimize plan design
  • Implement targeted prevention strategies

This can help them to create smarter programs that better respond to their employee-base and its specific needs.

Adoption is High. True Transformation is Still Catching Up.

While adoption is widespread, there is still a gap between experimentation and full transformation. A large proportion of insurers are still piloting or testing AI solutions, with only a small percentage having fully scaled them across operations (CoinLaw). This creates a divide between those using AI tactically and those using it strategically.

For multinational employers, that distinction matters and is where Insurope becomes increasingly relevant.

AI may be transforming employee benefits, but its impact depends on how effectively it is applied locally. For example, regulations differ and Healthcare systems vary across markets. At the same time, employee expectations are not the same in Singapore, Germany, or Mexico.

Through its Network Members in more than 80 countries, Insurope connects multinational employers with insurers that are not only adopting AI, but applying it in ways that reflect local realities.

Because while AI can generate insights, it still takes local expertise and global coordination to turn those insights into meaningful outcomes.

But at its core, employee benefits has always been about taking care of people. AI does not change that. But we look forward to seeing how it will continue to enhance it in the future.

AI CASE STUDY: ICATU SEGUROS

For Icatu, Insurope Network Member and one of the largest insurance companies in Brazil, the journey began with a structural modernization of the database and evolved into practical applications of analytical and generative AI, generating concrete gains in agility, efficiency, and scale.

Icatu divided this evolution into 4 major stages:

  • Data foundation and infrastructure: they started by migrating to a 100% cloud architecture (Microsoft Azure and Databricks), structuring a Data Lake that centralized the company's information and enabled the Self-service BI model. This gave autonomy to areas such as Marketing, Pricing, and Actuarial to use data in a more strategic and decision-oriented way.
  • Analytical intelligence and modeling: with the organized database, Icatu moved on to Machine Learning models, such as the Life Score, aimed at the automatic acceptance of risks, and Speech Analytics, which transforms voice interactions into a structured source of insights, contributing to the continuous improvement of service and the anticipation of customer needs and expectations.
  • Leap into generative AI: In August 2024, the company launched A.V.I. (Icatu's Virtual Assistant), integrating ChatGPT with WhatsApp to support brokers' journeys. Simultaneously, through a structured training and support strategy, Icatu made Copilot M365 available to employees, contributing to the organization and synthesis of information, increased efficiency and standardization, allowing teams to focus their efforts on higher value-added analyses, decisions, and activities.
  • Experimentation Framework: Icatu has been consistently maturing its capacity to conceive and execute Artificial Intelligence and Machine Learning initiatives. Within a portfolio whose curation and reporting fall under the Innovation area, there are different experimentation formats, ranging from predictive models applied to Pricing to agency solutions focused on Compliance, structured to test, learn quickly, and increase efficiency and value across various fronts.

Some of the benefits observed to date include:

  • Greater efficiency in processes: the average time for obtaining a life insurance quote has been reduced by 85%, from minutes to approximately 40 seconds with A.V.I., for example.
  • International recognition: this maturity led Icatu, in 2025, to 2nd place in the Gartner Eye on Innovation Awards for Insurance and 1st place in the Innovation and Vision for the Future pillars in the Época 360 ranking.
  • Accelerating the experimentation cycle: Standardizing the innovation framework and creating a portfolio of experiments has propelled the AI and Machine Learning pipeline at Icatu. This structure enables the transition from ideation to MVP in a predictable cycle of 8 to 15 weeks, ensuring diligent monitoring and delivery of measurable results.

This evolution was also reflected in business results: in 2025, premiums issued represented a growth of 23.2%, highlighting the positive impact of technology in expanding access to financial protection in Brazil.

AI CASE STUDY: PING AN HEALTH

Insurope Network member in China, Ping An actively leverages its proprietary artificial intelligence (AI) ecosystems to dramatically optimize employee corporate benefits, focusing heavily on digital healthcare and streamlined workforce operations. As the core implementer of Ping An of China’s "Integrated Finance + Healthcare" strategy, Ping An Health Insurance has fully rolled out AI capabilities covering two major dimensions: external customer service and internal operational empowerment, driving the industry’s shift from the traditional post-event claim settlement model to a proactive health risk management model.

In terms of AI-empowered customer service, the system now serves over 10,000 agents and has processed more than 50,000 service cases. AI assistance has boosted premium receivables by approximately RMB 43 million and cut total manual working hours by over 100,000 hours. Meanwhile, supported by the AI healthcare service system, general practitioners are assisted with case triage, long-term chronic disease management, post-treatment rehabilitation follow-ups and other tasks. The direct adoption rate of AI medical consultation replies stands at 97.6%. Corporate employees can connect with specialist physicians within hours for zero-distance online consultations. This digital solution constitutes a key pillar of Ping An Health’s differentiated core competitiveness.

For internal operations, AI helps the company identify risks such as medical overutilization and insurance fraud. To date, over 6 million claims have been processed, delivering RMB 3.3 billion in loss reduction with a contribution rate of 26.9%, while the proportion of fully automated claim reviews without manual intervention reaches 49.4%. In addition, AI tools are widely accessible to all Ping An Health Insurance staff. The AI Application Center serves 2,713 employees, of whom 1,866 are active users, representing an active rate of 68.8%, with a cumulative usage volume of 305,425 sessions.