By Tanya Krochta, EVP & Chief Operating Officer, ACORD
AI is rapidly reshaping insurance, from underwriting and claims to customer service and risk assessment. The next wave of agentic AI will accelerate that change. These tools promise faster, more connected, and more data-driven processes, but they also raise new questions about trust, governance, and accountability. But while technology may improve speed and consistency, people must remain central to how decisions are made, how judgment is applied, and how sensitive data is handled.
AI risks do not stop at organizational boundaries. Model drift, sophisticated fraud, autonomous decision pathways, and unintended consequences in automated workflows can emerge from shared data ecosystems. No single company can see the full picture alone. Addressing these risks requires collaboration, common understanding, and trusted ways to exchange information across the insurance value chain.
As the global insurance industry's internationally recognized and trusted standards development organization, ACORD helps create the conditions for responsible innovation. We do not dictate how organizations deploy AI. We bring the industry together around the shared foundations that make collaboration possible: neutral governance, common data standards, and member-driven engagement. That mission becomes even more important as AI interacts with sensitive insurance data. The path forward must be human-centered, using AI to strengthen expertise, support informed judgment, and ensure data is handled responsibly.
Practicing Human-Centered AI at ACORD
At ACORD, we view AI as a tool that amplifies — not replaces — human expertise. As we explore ways to apply AI in our own work, including activities that support standards development, people remain firmly in control of decision-making, governance, and accountability.
Our AI initiatives reflect that philosophy. We are currently embedding agentic AI capabilities in the ACORD Reference Architecture, one of the industry’s most sophisticated assets for helping insurance organizations to streamline operations and systems integration. As a set of interconnected models that define the nature of the insurance industry, the Reference Architecture enables organizations to identify and efficiently apply its functional capabilities, data structures, messaging frameworks, and schema definitions to work in harmony. The more comprehensive a user’s understanding of the various models and how they correspond with an organization’s specific business needs, the more they can get out of the tool. This is exactly the kind of task where agentic AI can be especially useful: helping explore the massive amounts of information in the Reference Architecture models more efficiently, identify relevant connections, and locate the information needed to move an implementation forward.
On our end, this approach also enables ACORD’s subject matter experts to focus on higher-impact work where their experience and judgment can help our members the most. When AI supports routine navigation and information discovery, our experts can spend more time partnering directly with clients and the broader community on implementation, identifying specific use cases, addressing emerging edge cases, supporting governance considerations, and advancing digital transformation across the insurance ecosystem. We are investing in AI to make human expertise more accessible, impactful, and fulfilling.
Building the Next Generation of AI Talent
Responsible AI adoption also requires investment in people. ACORD is helping prepare the insurance workforce through academic partnerships that connect students with practical, standards-based industry challenges. These initiatives build interest in insurance while developing the AI literacy, data fluency, and critical thinking skills the industry will need as AI becomes embedded across core insurance functions.
One example is the ACORD Student Challenge, which recently used pet insurance as a practical AI use case. Students worked with the kinds of data, business questions, and operational complexity they will encounter in the industry, learning both what AI can do, and where informed human judgment remains essential. The goal was not simply to use AI tools, but to understand how to apply them thoughtfully in an insurance context, with attention to data quality, standards, governance, customer impact, and responsible implementation.
ACORD is building on this work through a collaboration with the University of Connecticut School of Business, expanding into an instructor-led, semester-long engagement with capstone work at the intersection of financial and insurance technologies. Students will explore public data, market signals, and information about emerging lines of business such as pet insurance, cyber liability, and professional liability. They will apply AI techniques to turn this information into logical data sets in order to inform and accelerate standards development. These projects show how academic partnerships can turn AI from an abstract concept into a practical standards development exercise. Ultimately, ACORD’s goal is to help build AI-fluent talent that understands both the opportunities and responsibilities of applying AI in insurance.
Data, Truth, Trust
Long-term confidence in AI depends on trust. This is where data standards become essential for responsible AI risk deployment. As AI depends on data moving accurately and responsibly across many participants, systems, and decision points, the industry needs shared definitions, consistent processes, trusted data exchange, and common expectations for how information is interpreted, governed, and used. ACORD Standards provide that foundation by establishing a common vocabulary, promoting interoperability, and enabling collaboration.
For further exploration of this critical topic, please join us this September at ACORD Connect, which returns as a live in-person event this year at Mohegan Sun in Connecticut. The theme of this year’s conference is “Data, Truth, Trust” — we welcome your voice in the discussion.
At ACORD, we believe the most powerful use of AI is to strengthen, not replace, human expertise — guided by common standards, responsible data practices, and a shared commitment to helping the industry innovate… with people leading the way.