Former Global Leader and Industry CTO of Data Science and AI, IBM
Deborah Leff is a leading expert in outcome-driven business transformation. She is a proven advisor to senior executives on successfully identifying, prioritizing, and delivering on strategic AI initiatives that impact their most critical business objectives.
Currently, Deborah is an independent consultant, advisor, board member, and frequently requested public speaker. She served as the Global Leader and Industry CTO of Data Science and AI at IBM. In this role, Deborah worked with senior leaders of Fortune 1000 companies, helping them gain critical insights from data to drive improved customer experiences and optimized business operations. Prior to IBM, Deborah was the SVP of Business Development at GyPSii, a provider of geosocial networking applications and services, and she was the VP of Sales at Kadient, Inc.
Deborah joined the advisory board of Recruiter.com in July 2019 and was subsequently appointed to their board of directors in August 2020. In this role, she focuses on the intersection of human capital management and AI to develop strategies for eliminating bias in employee recruitment and retention, as well as leveraging AI to drive employee growth and development and enhancing the overall employee experiences.
Deborah also founded Girls Who Solve in 2019, an enrichment program for high school girls designed to spark interest in using technology and data science to solve real-world problems. Deborah uses the AI that students engage with every day and takes them beyond the scenes to understand how things work and why. Hands-on exercises teach participants how technology allows us to solve problems, capitalize on opportunities, and impact our world in new ways. After only one year, this program is in high demand, and she has been asked to replicate it in high schools across the country.
Deborah shared with us that over her career, she has worked with all levels of management and been involved in a wide variety of AI projects. In her role at IBM, as CTO for Data and AI, she met with executives around the globe at some of the largest companies in several key industries during the last number of years. In many of those conversations, she observed a recurring theme: Most executives thought they would be further along with their AI initiatives than they were. It seemed that an inordinate number of projects had not been delivering the value they had expected—they either get stuck in experimentation or took significantly longer to put into production than they had anticipated. “This may be hard to believe, but I have seen companies really struggle to put these advanced technologies to work. Most have hired talented and capable data science teams and are very proud of the work that they are doing. The conversation got tougher, however, when I’d ask about their successes and turn attention towards what had successfully been put into production. That’s the point in time when it felt like the energy suddenly drained from room. Very few companies I worked with are advancing on their AI agendas as quickly as they’d like.”
Deborah says, “Given our world is changing rapidly, companies need to be able to respond and adapt in near real time. Getting to AI at scale is no longer a nice-to-have, it’s a must-have, and executives are feeling the pressure to modernize—especially if they are a legacy company competing against digital natives. It’s not enough to infuse intelligence into the organization in small pockets; they need to become a data-driven organization. “Discussing how you might want to leverage AI is actually the easy part. The hard part is the access to data, limitations of siloed and rigid legacy systems, cultural impacts, and the fact that AI is not additive and cannot be easily added to existing processes or applications. I think a lot of the early press on AI success focused on how magical the results felt and almost made it seem like it was possible to sprinkle ‘AI pixie dust’ around an organization and make everything more intelligent, but alas, that is very far from reality.”