Liberty Mutual Headquarters
Randy Bean
How are data and AI being used to deliver value to customers and employees in the insurance industry? This is among the questions that I recently posed to Monica Caldas, Global Chief Information Officer (CIO) of Liberty Mutual Insurance. Founded in Boston, Massachusetts in 1912, Liberty Mutual today is the sixth largest property and casualty insurance company in the world and ranks 87th on the Fortune 100 list of largest U.S. corporations.
Caldas, who has served in a CIO capacity at Liberty Mutual since 2018 previously held CIO roles at General Electric (GE). Today, as Global CIO at Liberty Mutual, Caldas leads a global technology organization of more than 5,500 employees across 27 countries. Caldas explains, “Our mission is to unify our technology ecosystem into one cohesive, high-performing enterprise. This structure enables us to accelerate innovation, strengthen our competitive advantage, and deliver consistent value across markets.” Core to this mission are data and AI.
Embracing Data and AI as a Business Strategy
At Liberty Mutual, technology is designed to operate as a unified enterprise engine—owning IT operations, engineering, AI and GenAI capabilities, and the data ecosystem that enables intelligent decision-making at scale. This model reflects a deliberate choice: to embed data and intelligence directly into the fabric of how the company operates, rather than treating them as standalone functions.
From this foundation, Caldas—alongside the Chief Operating Officer co-leads the company’s global enterprise data and data science office, sponsoring initiatives spanning the establishment of data fundamentals of domain, quality and data products across the company and innovative ways to accelerate value. Caldas comments, “We are balancing global integration with local delivery and embedding a focus on reusability, velocity, quality, and resiliency. This approach has positioned Liberty Mutual for its next phase of strategic growth.”
“At Liberty Mutual, embracing data and AI isn’t a technology initiative, it’s a core part of how we run the business,” explains Caldas. “The conversations I have with my peers at the executive leadership table are centered on how data and AI enable better decisions, smarter operations, and more meaningful experiences for our customers and employees.”
Caldas notes that Liberty Mutual’s AI journey began well before the rise of generative AI. “Our early efforts focused on predictive capabilities that strengthened core processes, such as underwriting completeness and claims forecasting, helping us plan capacity and manage risk more effectively,” she says. “Those investments gave us the discipline and foundation to adopt GenAI thoughtfully when it emerged.”
“As an insurance company, we didn’t start at step one in terms of data and artificial intelligence capabilities.” Caldas notes, “We’ve been leveraging data, data science, and machine learning for many years to help us understand how we can better serve our customers.” She notes, “When GenAI emerged in 2022, we quickly recognized its transformative potential not just in terms of operational efficiency, but how we serve our customers and empower our employees.”
Liberty Mutual is taking a hands-on approach to data and AI adoption across the firm. This begins with developing a shared vocabulary and understanding of what technology can do to improve business outcomes, says Caldas. Corporate learning initiatives include:
- Executech. “Through our Executech program, leaders across the company participate in conversations and classroom style learnings about technology fundamentals, emerging trends, and how technology can drive business value”, explains Caldas. The program has helped increase shared knowledge across all functions and enables the co-creation of outcomes via technology with business subject matter expertise. “The Executech program has enabled us to better align priorities through the lens of understanding what business capabilities are differentiating and thus, reposition our investments towards greater outcomes,” says Caldas.
- LibertyGPT: “We launched LibertyGPT, our secure, internal generative AI platform, with direct support from executive leadership,” comments Caldas. She continues, Today, more than 74% of eligible employees have access to enterprise GenAI tools that can help streamline daily routines and free up time for higher-value work.” Caldas adds, “This rapid adoption was possible because we approached it with discipline, including a required training and leadership prioritized both the technology and the cultural change needed to make AI accessible and available to the organization.”
Caldas comments, “These efforts have already delivered measurable results—improving efficiency, reducing costs, and enhancing customer experience.”
Building an AI and Data Culture and Talent
Building a Data and AI driven business culture remains an ongoing challenge for many organizations. According to a just published survey of Fortune 1000 data and AI executives, 93% of respondents report that people and cultural challenges represent the greatest impediment to data and AI adoption within their firms.
“Our leadership believes that technology transformation is about people as much as systems,” notes Caldas. She continues, “We’ve invested heavily in upskilling our workforce, ensuring employees have the right tools, training, and guidance for responsible AI use, continuous learning and skill development. That commitment is helping us build a future-ready, resilient organization.”
Caldas adds that generative AI represents a fundamentally new way of working. “This shift applies to everyone, whether you’re an engineer, a Claims professional or a lawyer. Our goal has been to make these capabilities approachable, helping people understand how AI can meaningfully support their work and decision making.” She notes, “Integrating AI into the lives of 40,000 employees has been intentional, with a strong emphasis on hands-on experience and practical application.”
To support this approach, Liberty Mutual has established a Digital Progression Framework that enables employees to learn, experiment, and innovate responsibly. Caldas explains, “Through Everyday AI, we encourage teams to explore practical ways generative AI can simplify their day-to-day work, from drafting communications to analyzing data.” She continues, “These efforts are supported by a growing learning ecosystem, including a GenAI Hub for hands-on guidance, an AI@Liberty Community for peer collaboration, a Responsible AI Steering Committee and a Change Champion Network that helps teams adopt and integrate new tools.”
“Our goal is to embed AI into the core way of working. We’re not just improving speed and quality–we’re giving people the confidence and capacity to focus on what matters most: solving real problems and delivering meaningful outcomes for our customers.”. She continues, “Ultimately, we’re inviting employees in, empowering them to see that AI is a fundamental enabler for everything they can do, empowering them to imagine what’s possible, and enabling them to apply AI in thoughtful, innovative ways every day.”
Delivering Business Value from Data and AI Investments
Ultimately, the success of Liberty Mutual’s data and AI investments will be defined not by the number of tools deployed, but by the measurable business outcomes they enable. Caldas explains, “With strong sponsorship from the executive leadership team, we’re embedding AI directly into core business processes such as underwriting, claims, and customer service,” explains Caldas. Championed by the executive leadership team, we’re embedding AI into core processes like underwriting, claims, and customer service.” For example, AI-powered capabilities are helping Liberty Mutual underwriters make faster, more informed decisions, while generative AI copilots assist claims teams through tasks such as document summarization and workflow automation—reducing friction and freeing up capacity for higher-value work.
Caldas notes that Liberty Mutual evaluates the value of its data and AI investments across three key dimensions: operational efficiency, impact, and adoption. She elaborates:
- Operational efficiency is measured through productivity gains, time savings, and the ability to redeploy capacity toward more complex work. Caldas comments, “For example, across our engineering organization, the introduction of AI-assisted development tools has meaningfully increased delivery velocity by on average 10%.” Caldas adds, “More importantly, it has allowed our teams to spend more time on higher-impact problem-solving and innovation.”
- Impact is assessed by improvements in both customer and employee experience, including faster decision-making and reduced operational friction. Caldas notes, “With more than half of our eligible employees actively using large language model-based tools, we’re seeing significant time savings each week. Averaging 13,500 hours per week, this capacity that is being reinvested into better service, stronger outcomes, and deeper focus on our customers.”
- Adoption is tracked through usage patterns, engagement, and employee feedback to ensure that AI capabilities are being applied in meaningful, responsible ways that align with business goals.
“Our transformational efforts are delivering tangible results,” says Caldas. She continues, “In our investments business unit we have modernized core systems, migrated data to the cloud, deployed GenAI as part of everyday work, and are now advancing our strategy toward agentic AI.” Caldas explains, “These outcomes point to a bold, disciplined and pragmatic approach not only to eliminate technical debt but also unlock capacity for innovation, positioning Liberty Mutual to deliver faster, more secure digital experiences and sustain long-term growth to support the company’s promise of being there for customers 24/7.”
Ensuring Responsible AI
Highlighting the critical importance of Responsible AI, Caldas explains, “We established a Responsible AI Steering Committee that brings together leaders from Technology, Legal, Privacy, Security, and HR to ensure that our use of AI is responsible, transparent, and aligned with our company values.”
Caldas notes, “This group Committee governs both risks and opportunities, balancing defensive and offensive, as well as pace and accountability.” She continues, “This group ensures that every AI innovation meets our standards for governance, ethics, and compliance—balancing the need for speed and experimentation with the responsibility to protect our customers and brand.”
“Responsible AI is about risk and compliance as well as how we empower our teams to experiment safely, align to evolving regulations, and create measurable business value,” notes Caldas. She continues, “We’ve been thoughtful about governance long before GenAI became mainstream. We had already built the scaffolding—data pipelines, model testing frameworks, and internal structures—that allowed us to adopt GenAI responsibly.”
Caldas concludes, “Governance is how you scale trust. It’s not just policies, its pace, visibility, accountability, applied consistently across the enterprise.”
Looking to an AI Future
Across Liberty Mutual, GenAI is creating the opportunity to reimagine how work gets done. Caldas explains, “At the heart of our philosophy is the notion that we want to unleash human potential.” Liberty Mutual plans to expand its use of GenAI across the business units in alignment with the business aspirations of the company, says Caldas.
“We have been disciplined in how we have moved forward with our 35 use cases which are now live and within the construct of our governance mechanisms,” says Caldas. “Within this, is the idea that we have to continue to operate with the best tools and capabilities so that our employees can deploy their creativity and domain expertise towards outcomes that matter most.” She elaborates, “This means enabling our employees to focus on deep work while streamlining more routine aspects to the workflows.”
Looking ahead, Caldas outlines a clear vision for the role of technology, noting, “Our vision is that technology is a force multiplier in support of our business aspirations.” She continues, “AI is another powerful capability in our toolbox—but one that represents a shift from deterministic systems to more dynamic, context-aware technologies. That shift gives our teams greater flexibility and adaptability to the context in near real time.” She adds, “We are unlocking the full value of our data, ensuring that real-time, AI-ready information can seamlessly integrate with large language models and autonomous agents.”
Caldas concludes, “We will continue to focus on developing a culture of adoption, training our employees for responsible use of GenAI, and alignment to our business goals in how we plan to develop products and services to best serve our customers.” She sums up, “As we embed new AI capabilities directly into workflows, we’re enabling automation and augmentation that accelerate decision-making and free our people to focus on higher-value work. We are unlocking human potential for a resilient and future ready enterprise.”
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