The Changing Role of CDAOs in the AI Era

Leadership Profile
Written by Leslie Lang

Matt Smith

Chief Data Officer - West Enterprise Operating Unit

Microsoft Corporation

JULY 2024

Matt Smith, Chief Data Officer - West Enterprise Operating Unit at Microsoft Corporation, says that his whole career has revolved around data. He calls himself a “numbers and computer person,” who studied computer engineering in college. “After I graduated, all of the roles throughout my career have been this hybrid role, where I put on a business hat, and I put on a data hat,” he explains. 

After graduating, an internship and a few different roles, he started consulting and found that it was a great way to learn a variety of skills early in his career. “You're getting exposure to new problems and people and building your network all along the way,” he says.

In addition, his work on long, complex technology and transformation projects were strategically important to customers and increased his exposure to senior leaders. This consulting experience, Matt believes, “married my technical skills with my business skills.” He continues, “I call it being able to speak multiple languages. Those facilitation and communication skills are what helped me get the roles I've had.”

Matt first worked for a Microsoft partner and then joined Microsoft as a sales engineer and then a solution specialist, both in the data and AI space. He shares that he is always looking to answer the question, “How do I navigate and enable business outcomes through technology that are manifested in data?”

I'm really passionate about technology and solving my customer's problems, and that's what fills my cup.”

His work at Microsoft involved establishing a framework for transformational partnerships with customers that were rooted in business outcomes through data. That led to the creation of a new role at Microsoft -- Field Chief Data Officer. He describes it as “aligning with the executive leadership at our customers’ organizations to build trust, understand their challenges, and identify what a road map looks like -- so that we can both benefit and both achieve our goals.”

Challenges and Opportunities for the CDAO Role

Working in the data and technology space with customers, Matt has a lot of exposure to Chief Data and Analytics Officers and their current challenges. He believes that now that we are almost two years into generative AI, there is a lot of pressure on CDAOs. 

“It’s never been done before, and you're asking these leaders to go solve a very challenging project or strategy, in a very short time frame, on something that is ambiguous and undefined,” he explains.

He says that’s both the biggest challenge and the biggest opportunity for CDAOs right now. “It’s probably the area that’s going to see the most shaping. We’ve seen a heavy focus on, ‘Let's create a cross-functional committee that can help us review how we should use AI, how should we quantify the value of AI, and how we ensure we're asking the right questions to safeguard that.’”

The result? AI is elevating CDAOs in terms of their strategic importance to an organization. “It's giving them the ability to be a facilitator across multiple lines of business.”

This wave of AI has truly reduced the technical barrier to get into AI, and it's also significantly scaled the potential.”

Matt says working at the intersection of data and AI is exciting right now because of the democratization of data and the acceleration of pace. He explains, “It’s a lot easier for a company to test or pilot and evaluate and learn from it and throw away the product if it's not good, and then move on to the next use case. I think that's the AI breakthrough.”

CDAO Priorities as AI Keeps Moving the Meter 

This year, he sees three key priorities for data leaders. The first is to have a single view of their business to do analysis against and use to make business decisions. The second piece is around data governance because “your AI is only as good as your data,” he says. 

“That's a challenge right now because you've got legacy systems, you have new age systems, and you have new architectures that don't necessarily work well with the data governance products that have been out there.”

The third key priority is about how businesses are implementing AI. “It's moving from, ‘I have an internal Chat GPT that my team can ask questions against’ to, ‘I'm creating a rich, personalized experience for my customer-facing employees to have about their customers, and it's within the context of the customer’s journey.’”

Moving from kicking the tires on Gen AI to productional AI and use cases that scale across an enterprise has really, really moved the meter.”

One CDAO challenge on the horizon is how to responsibly democratize access to data, according to Matt. “How do we prevent someone who shouldn't have access to that data from having access when our data custodians are really not as up-to-speed as they should be?”

“That's scary because it's one thing to have bad actors that are intentionally trying to [access proprietary customer information]. It's even scarier when the person behind the keyboard or talking to the customer is ignorant of the fact that this data shouldn't be offered up to the person they're talking to.”

The Importance of Change Management 

While presenting at the recent Southern California CDAO Executive Summit focused on data analytics and AI, Matt says he had an “aha” moment concerning change management.

“I had just met a large customer who said, ‘We can't take on new AI projects right now because we're so busy keeping the lights on.’ You have these legacy platforms and applications and processes that require people to manage and maintain. How do you focus on innovation when their time is completely spent?”

He explains that made him pause and think about legacy systems. “Can we be better about maintaining our business processes and applications, so they don't have to be archived and sunset? Do we adopt a software-as-a-service strategy more prominently so it's always up to date and you don't have to invest the time upgrading and patching?”

Matt continues, “Or, do we create a bimodal team, or a smaller team that’s focused on innovation while the other team is focused on the operation? Technology decisions and now technology is changing so much, do I need to pause and restart? Or, how do I best navigate that?”

In conversations with CDAOs at the Executive Summit, Matt realized that dealing with legacy and change will continue to be pivotal in the years ahead. “Throughout the event, it felt like data leaders were in this position like, ‘I’m on my water skis and they're kind of going apart from each other because I can't innovate and do this at the same time.’”

To join the conversation on AI and the evolving role of the CDAO, apply to join an Evanta CDAO Community. If you are already a member, sign in to MyEvanta to register for your community’s upcoming CDAO events.

Special thanks to Matt Smith and Microsoft.

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