Ted Balzano is the Chief Data and Analytics Officer at Westfield Insurance, a leading global property and casualty insurance company based in Westfield Center, OH. Ted was interviewed by Anthony Habayeb, CEO and Co-Founder at Monitaur.
Ted, what does it mean to build a better foundation around data quality before focusing on AI?
“It starts with ensuring a strong data governance framework or program. Data is the fuel for AI, and many organizations haven’t yet matured their data governance practices. You need quality, completeness, accuracy and timeliness in your data. Without these, you’ll struggle with AI’s accuracy and the outcomes it delivers. Establishing a solid governance foundation is essential for making AI successful.”
Do you see certain patterns causing the biggest issues with data quality and AI enablement?
“Many vendors tout AI, but they should also emphasize the need for good data to drive it. Our approach is to start with use cases where there’s already good data and governance. This ensures success and avoids wrapping AI around incomplete or low-quality data, which AI won’t fix—it’ll only highlight those issues. At Westfield, we focus on the right use cases to maximize business value and implement AI thoughtfully.”
Why is it important to approach data governance at a project level rather than perfecting it upfront before AI projects?
“It’s important to identify gaps and challenges as you go and address them incrementally. Start with the business imperatives. Sometimes, you can solve 80 percent of a problem with the data you already have, and that can still add significant value. If you wait for perfect data, you’ll miss business opportunities. A business-led, data-supported approach is the way to go.”
How do you think about ownership and responsibility for data governance when managing diverse stakeholders?
“Artificial Intelligence spans a spectrum—from narrow AI, like predictive models, to generative AI and emerging agentic AI. For narrow AI, we often already have quality data and can leverage third-party data under well-established governance frameworks. Generative AI presents opportunities like data summarization, especially for unstructured data, driving real business value. Agentic AI can assist with areas like underwriting, claims and call centers, turning tacit knowledge into actionable insights.
Regulation is a critical consideration, especially in our global, highly regulated industry. Understanding and adapting to evolving rules, whether in the EU, UK or elsewhere, is key. Wrapping governance around all these efforts ensures compliance and drives value.”
If you walked into a company early in its AI journey, how would you guide them to success?
“Start with the end in mind. Identify key use cases where data and AI can address challenges or create opportunities. Avoid massive, all-encompassing projects. Instead, build incrementally, like assembling Lego bricks. Focus on areas with good-quality data to deliver real impact quickly, and expand from there.”
What frustrates you most in the conversation around AI today?
“Vendors over-hype AI and its capabilities. While there’s incredible potential, we’re still years away from realizing its full impact, especially in industries like ours. Vendors believe they have the silver bullet, but AI requires strong foundations. Organizations need to experiment, run proofs of concept, implement quick wins and stay engaged as the technology evolves.”
Is data governance or AI governance more important?
“Data governance is the priority. Without a strong foundation, AI and advanced analytics won’t deliver. You don’t need everything perfect upfront, but you must establish foundational elements to support AI effectively.”
Who do you work with most closely to ensure thoughtful data governance in an AI-driven world?
“Internally, we work closely with our Chief Data Privacy Officer, Chief Information Security Officer, Chief Risk Officer, Chief Administrative Officer and Chief Human Resources Officer. They ensure fairness, address bias and navigate internal and external regulations. We’re also monitoring emerging regulations in places like the EU and the US. While we’ll leverage outside partners as needed, our internal team takes the lead in this evolving space.”
Any final thoughts you’d like to share?
“As an organization, we’re advancing our data strategy to ensure a strong foundation for AI and beyond. We’re actively building generative AI capabilities and focusing on attracting the talent needed to thrive in this rapidly evolving landscape.
I often say the world changed in November 2022 when OpenAI launched, making everyone realize the importance of a strong data program. Whether it’s data or AI governance, taking a project-by-project approach—focusing on key business use cases—is the best way to accelerate progress.”
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