In a recent three-part article series for Monitor, Brendan Cronin, Divisional Vice President of Innovation at Great American Insurance Group, explored the roadmap for moving organizations from experimental digital projects to enterprise-wide adoption. As the industry grapples with the rapid rise of AI and the overwhelming volume of information, many leaders are left wondering how to find actionable insights within the “noise.” In this conversation, Cronin joins Monitor Editor in Chief Rita Garwood to discuss the value of unstructured data, the importance of “semi-technical” talent, and why digital transformation is more about task replacement than job replacement.
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Rita Garwood: We recently published a three-part article series on our website titled “Future-Proofing Your Business for Digital Success” (see Part 1, Part 2 and Part 3 here). The series explored how organizations can move from experimental side projects to enterprise-wide adoption by building a scalable digital foundation. The author of that series is with us today, Brendan Cronin of Great American Insurance. Brendan, can you introduce yourself and tell us what you do for the industry?
Brendan Cronin: I’m with Great American Insurance, and my role is around technology and innovation. We are an insurance provider to the equipment finance industry. I’ve played a role in redeveloping and transforming some of our products and services, and I’m looking ahead to AI and the upcoming advancements for our industry.
Garwood: In a recent LinkedIn post, you compared unstructured data to a muppet, calling it “fuzzy and unpredictable.” For an industry built on order and verified numbers in ledgers, how do leaders begin to shift their mindset to be more open to the possibilities of this data?
Cronin: A lot of the data we are talking about is already on our desks, screens and in our meetings — we just hadn’t previously thought of these things as data. Financial services firms have had 50 years of databases and ledgers, which require a disciplined, orderly approach and that precision must continue. However, we now have the tools to take that layer of information above the ledgers — productivity software, transcripts, emails and notes — and make it actionable. The “unpredictable muppet” part is that it will feel a little odd and disarming at first, but organizations can now take that content and use it for insight.
Garwood: You’ve noted that a team’s adaptability and curiosity often matter more than technical skills. When building team literacy, what is the first step a traditional finance firm should take to make AI feel like an extension of the team rather than a threat?
Cronin: There is a lot of concern about AI and job replacement, but the right frame is “task replacement”. This doesn’t change the organizational chart, but it changes the work on their desks. When looking for people to lead this charge, look for “semi-technical” employees — they might not have computer science backgrounds, but they understand the business and the technology. These individuals can “paddle on both sides of the canoe,” and they are the ones who will naturally start to apply the value of AI within an organization.
Garwood: Besides some technical interest, what other characteristics would you look for in a person who has that ability to bridge the gap?
Cronin: It is surprising, but sometimes their background isn’t what you would expect. A liberal arts background can be a clue that they have a good ability to take on these challenges. You want someone who has a good eye for what works but isn’t so entrenched in the business that they are resistant to change. It is behavioral and cultural; you often know it when you see it in the right person, even if they have had a winding path to get there.
Garwood: Many organizations hesitate because they assume transformation requires a total overhaul. How can companies start small today while ensuring their strategy remains future-ready and scalable?
Cronin: Being put in a room and told to “innovate” for an hour doesn’t work; it forces people into an artificial environment. Instead, build on your existing planning and strategy practices. When obstacles surface during your SWOT analysis or forecasting, give them extra space to be addressed by new tools and technologies. Do not build a separate practice for innovation; make it an extension of existing business practices to ensure longevity. If it’s folded into how you routinely manage the business, it has more “legs” to survive and thrive.
Garwood: You noted that structured data tells us what is happening, but unstructured data tells us why. Can you share an example of how a piece of “messy” data — like a maintenance note — can prevent a loss or identify an opportunity?
Cronin: When you don’t close a sale, the revenue numbers might show a decline, which is a lag indicator. The unknown is why someone passed on an offer when your price was better — that is “gold” and constitutes unstructured data. Customer signal is very valuable. Software systems always have a “notes” field; when a salesperson adds a note, that is a signal. Tools like AI allow you to capture that signal from the notes field and make it quantifiable, helping you identify patterns and stories behind the numbers.
Garwood: For a company buried in PDFs and legacy systems, what is the most effective way to begin an inventory of the hidden value scattered across the organization?
Cronin: It can feel like a mess because people have individual habits, but the good news is that technology is getting better at arranging it for you. You need to centralize your information and address security concerns regarding AI. Once you have those repositories — what technical experts call “context” — you can point the AI at that information. I’ve seen this work firsthand: by giving AI access to a central repository of my notes and files, it can now create high-quality agendas for complex topics that were previously scattered across emails and meetings.
Garwood: How do you advise firms to balance the need for financial precision with all of these “fuzzy” insights?
Cronin: It’s a “yes, and” approach. The accounting and validation that goes into creating precise numbers are as important as they ever were. Good financial analysts look for the story behind the numbers, but when you encounter the “unknowns” in the data, that is where the narrative comes up. Use metrics as lag indicators and use the unstructured data — the notes fields and context — to explain changes to those numbers. The two should work hand in hand.
Garwood: When looking into establishing a strategic partnership for custom AI or data labeling, how should firms weigh “build versus buy” options?
Cronin: One of the key things transforming technology is that AI is being used very effectively to write software. Coding is the first area of impact; many firms have reached a point where people aren’t writing software by hand. This changes the “build vs. buy” calculation because people should be able to go through their backlog of projects at a higher rate of speed. Judgment and empathy, however, are human-centric and will always stay with the people. Ask yourself what makes your organization special. If you use outside vendors, ask them how they are using these tools to increase productivity.
Garwood: Beyond traditional ROI, what are some key performance indicators that prove a company is actually becoming more digitally successful?
Cronin: I look at a “market basket” of metrics. The key one is velocity: Are you moving quicker from data to insights to decisions? It is also helpful to identify areas where you can make measurable efficiency gains, such as saving time on manual tasks like sorting through inbox communications. Then there is the subjective “feel” — do the leaders of the organization feel like they are getting something out of it, and can they explain their innovation efforts to stakeholders?
Garwood: How do you prevent innovation groups from becoming experimental side projects and instead ensure they lead to enterprise-wide adoption?
Cronin: It comes down to a sustained approach. At Great American, we institutionalized innovation by ensuring our leadership group routinely communicated what we were doing and why. It became part of our story, socialized in town halls and routine check-ins. Innovation needs the continuous support of leaders who can communicate the vision, saying, “I know it’s over the next hill, but it’s there,” even when others start to doubt.
Garwood: If a person listening to this podcast could only do one thing from your list of ways to set themselves up for success this quarter, which one would have the greatest impact?
Cronin: I would say the “culture of possibility”. It is foundational. You cannot drill into these other areas where there is work to do unless it is cultural. Companies are people-first and behavior-first. Giving people the sense that the company is a dynamic, living thing — that the organization can change — is the most important thing. If you step into an organization where that possibility exists, you are going to get so much passion and energy from your team.
