You may imagine leading a global enterprise AI company’s finance and operations would consist of spreadsheets, forecasts, and quarterly targets. Brian Unruh, ABBYY's Chief Financial Officer, sees the role differently. For Brian, finance is really about problem-solving: spotting the right challenge, rallying people around a solution, and following through until it delivers real value.
That mindset traces back to his roots of training as an engineer before pivoting into accounting and finance, a path that taught him to combine analytical rigor with a genuine drive to solve problems. Today he brings that same curiosity to how ABBYY runs internally and how the company helps customers put their information to work.
We sat down with Brian to talk about mentorship, the real opportunity in AI, and why customers keep choosing ABBYY for the long game. His perspective fits perfectly within our ongoing YouTube series, "Human Intelligence Driving ABBYY Innovation."
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The career pivot that made a CFO
Mentorship and the 3 I's framework
The career pivot that made a CFO
Not every finance leader set out to become one, and that includes Brian.
He went to school to be an engineer and got halfway through before a moment of clarity changed his direction. "I feel like I want to solve problems, but this just isn't my passion." After talking it over with his counselor, the first problem Brian solved in his new career path was where to turn next. Engineering wasn’t a fit but Finance, on the other hand, genuinely excited him.
So, he pursued accounting with a computer science minor, then moved into public accounting during a period of major corporate transformation. Throughout each step of his career, he found himself at the center of every problem-solving meeting he could position himself within. He found himself working with US-based multinationals as they reorganized offshore, took advantage of shifts in the EU, and pursued location savings. Each new challenge pulled him further into complex problem-solving.
Brian’s blend of engineering logic, financial discipline, and orchestration skills is exactly what shapes his leadership at ABBYY today.
Mentorship and the 3 I's framework
Early in his career, Brian was fortunate to have a mentor who gave him a framework he still uses: the three I's. Identification, innovation, and implementation.
Here is how he breaks it down. Any one person tends to be strong in one of those areas. A smaller group excels in two. And a rare few are strong in all three. Recognizing where people fit helps you build balanced teams and move work forward. The real challenge, Brian notes, is momentum. Meetings often stall at the first stage. "Everyone wants to talk about the problem," he says, so the key is helping teams shift from identifying issues to actively innovating and implementing solutions. His belief is simple: "You always can get better."
That philosophy now shapes how ABBYY invests in its people. Through initiatives such as the mentor/mentee program at ABBYY, Brian is actively developing a collaborative environment where new employees feel acclimated and supported from day one. For him, it comes down to a phrase he holds close: pay it forward. With decades of expertise designing purposeful teams, Brian’s goal is to transfer his experience across the whole company, not just his own team.
"We have a goal. We have that North star. Let's go for it."
When experienced leaders guide others and give them room to grow, that trust ripples outward into stronger teams and better outcomes for customers – this is human intelligence in action.
"There's no AI without PI"
Brian has a memorable way of framing one of the most common mistakes he sees in AI strategy: "There's no AI without PI." In other words, there is no meaningful AI without process intelligence.
Many finance leaders jump straight to a narrow fix to a singular problem. His advice is to look horizontally first, before going vertical. Upskilling the whole enterprise to understand where AI can help reveals far more opportunity than tackling one isolated pain point.
Why does this matter so much? Because, as Brian puts it, "that exposes where data meets process, that's where AI exists." Understand your core data sets and your processes together, and you uncover where AI can genuinely accelerate results.
This is exactly where ABBYY Process Intelligence earns its place. By giving organizations a clear, data-driven view of how their processes actually run, it pinpoints bottlenecks, inefficiencies, and the precise moments where automation delivers the most value. Rather than guessing where to apply AI, teams get evidence. That horizontal lens then makes it far easier to target the right verticals, whether in accounts payable, accounts receivable, customer onboarding, or the many other workflows that connect teams across a company.
The practical lesson: map your processes first, then apply AI where data and process intersect. That is where scale and real acceleration happen.
AI's biggest opportunity: Insights that unite teams
When Brian looks at AI's potential, his focus remains on the insights AI provides rather than the flashy demos.
AI enables you to take a fresh look at your processes and see where it can accelerate decision-making. Sometimes that means brainstorming new thoughts and ideas, and other times it can surface patterns you were not even aware of, especially when you combine unstructured and semi-structured data. The result is a powerful look into deep analytics and opening data in a way that can unite teams through shared understanding.
Much of that valuable information sits locked inside documents in formats that traditional processing struggles with. This is where ABBYY intelligent document processing (IDP) turns trapped content into structured, usable data.
With ABBYY Document AI, organizations extract and validate information from virtually any document, in any format or language, then feed that clean data into analytics and decision frameworks. Combined with a hybrid approach that pairs purpose-built AI with large language models, teams gain both advanced capability and the accuracy they can trust supporting all document types, in any format or language, then feed that clean data into analytics and decision frameworks.
A hybrid approach that pairs purpose-built AI with large language models enables teams to gain both advanced capabilities and the accuracy they can trust. document, in any format or language, then feed that clean data into analytics and decision frameworks. Combined with a hybrid approach that pairs purpose-built AI with large language models, teams gain both advanced capability and the accuracy they can trust.
Brian also points to something ABBYY takes seriously: living the promise internally. "We're experiencing internally as customer zero exactly what we're providing to our customers," he says. When a company uses its own technology to unite teams and accelerate decisions, it understands firsthand the value customers receive.
Why customers choose ABBYY
We closed our conversation with a straightforward question: why do customers choose ABBYY? Brian's answer was just as direct.
"I think customers choose ABBYY because we're honest," he says. "And we're always there for them." He describes a relationship built on genuine partnership, an approach that earns ABBYY a role customers value: trusted advisor. Part of that trust comes from a deliberate commitment. "We've chosen the path of compliance. We value that," Brian says. "We're in here for the long game and they know that."
As the landscape moves week over week due to the rapid advances in generative AI and the growing use of large and small language models, through all of it, ABBYY stays grounded. With over 35 years of experience leading the market in AI powered document understanding, customers understand that ABBYY is here for the long run.