Kyndryl Fellow Clea Zolotow: reimagining the future of mission-critical enterprise technology

For Clea, the story of the mainframe is one of continuous innovation. She remembers when organizations debated whether to move large-scale transaction processing off the mainframe. But that robust environment already featured the security, resilience and reliability that enterprises continue to depend on. Often, the challenge was not the platform itself, but how applications and integration patterns needed to evolve. Much of Clea’s work has centered on modernizing critical mainframe applications to play well with cloud-based software so organizations can continue to get the most out of their deep stores of operational data.

Emerging AI solutions are helping to drive technical modernization while also addressing the mainframe skills gap. AI is enabling a digital lingua franca that makes decades of uncodified expertise — often held in the memories of retiring mainframe experts — accessible at scale. As a result, today’s programmers can use AI-powered agents and reusable models to automate an increasing portion of tasks that used to require experienced specialists. “AI gives us an opportunity to preserve institutional knowledge and make it available to the next generation,” Clea says. 

For example, it’s now possible to codify VSAM tuning — optimizing a long-standing mainframe data access method used in many financial-services environments — into repeatable processes that previously required specialized expertise. “I used to get calls in the middle of the night from all over the world to do one specific thing: tune VSAM files for banks. I got sick of getting on a plane to fly halfway around the globe to do that, so that was the first AI agent I wrote,” Clea says. “Success is when systems can take care of routine problems on their own, allowing people to focus on higher-value decisions. If I can teach an agent to wake up in the middle of the night, or better yet just fence it before it even gets to that point, then I’ve succeeded.”

Clea’s journey from “technology-curious” to technology expert was perhaps unconventional by today’s standards. Clea began her career in a series of administrative and temporary roles in data centers. But she seized opportunities when they arose — or created them herself. As Clea recalls, “The systems engineers said they were sitting around for three or four hours every Sunday, and that I should come by to work and they would teach me. And that’s what I did.” 

To pay forward the generosity of her teachers and mentors, Clea engages with what she sees as growing excitement among earlier-career professionals about the scale, complexity and global impact of modern enterprise computing. She teaches mainframe-related courses at the university level and has founded and supported hands-on experience programs.

As restless as she is curious, Clea is also a Master Inventor. She once wrote “about 20 mainframe, AI and quantum-related disclosures” during a slow week. She also developed plans for a dress that the wearer could configure for different events. “When I retire, that’s one of the things on my list. I want to make that dress,” she says. Another fun patent involved overcoming the challenge of moving large volumes of data to a remote, mountainous location with spotty telecommunications coverage by loading the data onto USB thumb drives and flying them up with drones. 

In her spare time, Clea enjoys cycling and playing classical music — two activities that prompt her to compare career development to learning a new sport or piece. “If you never fail, you might not be pushing yourself enough.”