Beyond the code: Bridging the technical and non-technical divide
Ana Sulakvelidze ’24 MBAi views AI as a never-ending puzzle.
As an AI product architect at NVIDIA, a company known for designing and manufacturing graphics process units, semiconductor chips and software for AI, Sulakvelidze is constantly facing new challenges and determining the best ways to resolve them. In her role, Sulakvelidze develops enterprise AI applications that solve internal business problems.
Her current project involves building a platform to help employees interact with critical business data. She’s building agents and autonomous AI systems that need to take action, find relevant information and evaluate results. To develop a good information retrieval system, she also needs to focus on the structure of information being received — a concept emphasized to her in Northwestern University’s MBAi program.
“What excites me the most in my current job is its creativity element,” said Sulakvelidze, who has worked at the company since February 2025 after interning there in 2024 as a student in the joint AI-focused MBA degree offered between the Kellogg School of Management and the McCormick School of Engineering. “Solving existing problems and redesigning existing workflows and processes with AI feels like I’m constantly solving puzzles.”
Sulakvelidze’s interest in AI dates back more than a decade to when she moved to the United States from the country of Georgia. She worked as an AI programmer focused on rule-based systems for automating document creation.
That experience set the foundation for her current work with cutting-edge AI technologies. Her passion centers on bridging the gap between technology and business while making technology concepts more approachable for non-technical colleagues.
Sulakvelidze works with a wide variety of stakeholders to find unified solutions to complex challenges. Sulakvelidze is collaborating with colleagues from finance and marketing — two stakeholder groups with different knowledge bases and needs.
To succeed, she's relying on lessons she learned in MBAi. She explained the challenge with building software using generative AI is its non-deterministic nature — the inability to predict definitively how a system will respond to given inputs. To overcome the challenge, she has to create a safe and robust software ecosystem — something she learned how to do in the MBAi program.
“MBAi was my top choice because of its intent to bring technical and non-technical mindsets together,” Sulakvelidze said. “I had a strong technical background and needed to advance my business knowledge and skills. MBAi fit that bill perfectly.” Her approach to making technical concepts accessible to non-technical audiences is rooted in her belief that simplifying complex ideas leads to better understanding.
She often uses analogies to connect the technical and non-technical worlds. “Technology is very logical and recyclable. It is never completely original in a sense that it borrows bits and pieces from its predecessors or even unrelated technologies,” Sulakvelidze said. “That’s an advantage when you want to explain it, because you can draw parallels with familiar concepts.”
Sulakvelidze also appreciated the MBAi program’s emphasis on not rushing to solve a problem. That, too, is a skill she finds herself relying on daily. “I learned a lot of things during my time in the program, but the most valuable lifelong lesson I received was to get better at listening,” she said. “It is challenging to truly listen to and internalize unfamiliar perspectives, but it is essential for growth and success.”
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The views and opinions expressed in this post are those of the author, and do not necessarily reflect the position of the Kellogg School of Management or Northwestern University.