As organizations across industries accelerate digital transformation, the role of data leaders has become more central than ever. Enterprises are not only tasked with managing massive data volumes but also ensuring that data strategies align with business goals, enable responsible AI adoption, and build trust across stakeholders.

In this first part of a two-part series, CDO Magazine and Informatica bring together two leading voices in the field: Michelle Boston, CIO, Head of Data Management Technology & Enterprise Architecture at Bank of America, and Adita Karkera, Chief Data Officer for Government and Public Services at Deloitte. The conversation, moderated by Amy Horowitz, Group Vice President at Informatica, explores their professional journeys, leadership influences, and perspectives on advancing AI responsibly.

Path into data leadership

Boston shares how her career journey combined technical expertise with business alignment, eventually leading her into CIO responsibilities. “I probably have one of the most traditional paths to a CIO, although I don’t think I ever expected to be a CIO when I started,” Boston explains. With a degree in Computer Science and Management Information Systems, she began her career as a programmer before transitioning into consulting, transportation, and insurance.

Her entry into the data space came at a pivotal time in the late 1990s. “I led their data warehousing and business intelligence strategies during the boom in online analytical processing and business-oriented capabilities in the business intelligence space,” she recalls.

At Bank of America, Boston’s responsibilities expanded to cover data protection, privacy, and regulatory compliance, while ensuring data delivered real business impact. “We unlock the power of data for strong risk management, responsible growth, and business enablement — to give customers a differentiated experience and deliver great data-driven decision making to our associates.”

Bridging technical depth with business outcomes

Reflecting on her leadership style, Boston emphasizes the importance of balancing technical expertise with business value. “One of the most rewarding parts of being in the data space is that you bridge both,” she says. “What are the business outcomes we’re trying to achieve, and how are we driving value in a way that resonates with our executives and our clients? At the same time, you’re still steeped in the technical — delivering at scale, building enterprise platforms, and meeting diverse business demands.”

From analyst to public sector CDO

Karkera’s path into data leadership, while less traditional, highlights the importance of resilience and mentorship. “If you went back and asked me when I was a high schooler, would she be a CDO today? The answer would surely have been no,” Karkera admits. “But mentors shaped the way for me, colleagues helped me grow, and of course, hard work and data skills were the baseline.”

With over 25 years in the industry, she began as a database analyst and was later appointed Deputy Chief Data Officer for the state of Arkansas in 2017 — one of the first such roles in government. That experience inspired her doctoral studies in data, CDO practices, and AI.

Her work during the COVID-19 pandemic further cemented her commitment to public service. Today at Deloitte, she serves as CDO for Government and Public Services, helping agencies maximize data and AI investments while also leading Deloitte’s internal data strategy.

Asking the right questions about data

Karkera reflects on a pivotal moment in her leadership journey: realizing that government agencies often collected vast data without fully leveraging it. “What got to me was: are we just collecting data, or are we investing in getting actionable and intelligent insights from it?” she says. “That curiosity led me to ask — are we using this data to make citizens’ lives better? That was a turning point, and I knew I needed a seat at the table to influence this.”

AI: Beyond the shiny object

The conversation further turns toward AI, a subject dominating both boardroom and public discourse. Karkera notes that organizations must move beyond seeing AI as a novelty. “Even though you have an AI strategy in place, unless it’s actionable with milestones and KPIs, it’s hard to see success,” she warns. “Add siloed systems and the lack of AI literacy, and the challenge multiplies.”

She argues that data literacy is no longer optional: “The lack of AI-fluent, AI-literate organizations is definitely a challenge. Data literacy is an inherent skill needed for any person today, not just practitioners.”

At the same time, she stressed the foundational importance of data quality. “Garbage in, garbage out still rings true. If you don’t trust the data you’re feeding into your AI models, it’s going to be hard to trust the solutions coming out.”

Aligning AI with business strategy

For Boston, the key to AI success lies in alignment with business needs. “AI is not new,” she points out. “We have 7,800 patents for software, 1,400 of those are AI patents for things we’ve been using for years — machine learning, robotic process automation, chatbots, automated workflows.”

Generative AI is the newer frontier, but Boston emphasizes it must serve business strategy. “Building an AI strategy in the absence of a business need is where companies go wrong.”

Instead, she explains, organizations must understand their processes and identify where AI can re-engineer them. “If you start with a focus on business outcomes — client experiences, personalization, efficiency, elimination of toil — then we can find the right technology to deliver those outcomes.”

Stay tuned for part 2.

CDO Magazine appreciates Michelle Boston and Adita Karkera for sharing their insights with our global community.