Generative AI has taken center stage in today’s data-driven world, with 82% of C-suite and senior executives prioritizing scaling AI use cases, according to a new MIT survey. However, there’s one obstacle to achieving AI success, cited by 45% of executives in the study: data integration. Many organizations spend significant time and resources on manual data processes, resulting in inefficiencies and missing out on AI’s scalability and growth potential. That’s where the CIO comes in.

Strategic CIOs aren’t just overseeing IT operations — they’re increasingly playing a pivotal role in driving business success through effective data strategies, which include standardizing and maximizing data accessibility in order to pave the way for scaling AI.

In this blog, we’ll explore how CIOs can drive their organizations' AI success by building a strong data foundation.

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A strong data foundation drives AI value

If CIOs hope to have any meaningful success with AI, they need to first start with establishing a solid data foundation that’s built on data maturity, where organizations excel in seamlessly integrating and managing their data — both in terms of movement and transformation — while maintaining effective governance. Without this foundation, developing, testing and deploying AI — or any kind of analytics, for that matter — becomes highly challenging.

With a solid data foundation in place, CIOs can take additional steps to accelerate AI development while mitigating risks.

Manage costs by standardizing platforms and controlling infrastructure sprawl

Managing costs effectively is a crucial responsibility for CIOs, especially as infrastructure complexity grows with expanding AI initiatives. AI doesn’t operate well within organizational silos or fragmented strategies; it requires governed access to high-quality data from every area of the business. 

Organizations need one unified platform, rather than multiple disconnected systems designed for different purposes. By centralizing data and reducing the sprawl of multiple tools and systems, organizations can simplify operations, lower overhead and create a more reliable foundation for AI deployment. This approach allows businesses to allocate resources more efficiently while supporting innovation and ensures that their infrastructure remains flexible without draining budgets or productivity.

Take Saks, for example. The iconic luxury retail brand struggled with cumbersome, slow ETL data pipelines that prevented the business from adapting swiftly to market changes and delivering the online shopping experiences that their customers came to expect. Recognizing the need for rapid innovation, Saks’ CTO Mike Hite initiated a strategic overhaul of their data ecosystem by integrating Fivetran, Snowflake and dbt to set the stage for a more agile, responsive business model. By modernizing its data infrastructure, the Saks team freed up more time for high-value activities like in-depth analysis and adopting new technologies like AI, ML and GenAI.

“The beauty of Fivetran is that it solves a very complex problem very simply for us: ingesting lots of different data. It’s one of the fundamental pieces of our AI strategy and allows us to bring in new novel data sets and determine whether they’ll be useful for us.”
– Mike Hite, CTO at Saks

Drive culture shift for effective data stewardship and governance

While implementing the right technology is important for successful AI transformation, CIOs must also instill a culture that prioritizes data stewardship. This involves fostering a commitment to data governance across all departments, ensuring that everyone understands their role in maintaining data integrity and security.

In the MIT survey, when respondents were asked about their primary data readiness challenges, 39% cited organizational culture around data as a key challenge. It might seem surprising that data culture is a concern, given its well-established importance. A lack of cultural alignment around data can prevent executives from fully exploring new opportunities. In fact, according to the MIT insights, those who see culture as a key barrier to data preparation are 33% more likely to deprioritize AI scaling and cite budget constraints. This suggests that attitudes may limit data readiness investment as much as financial resources.

Organizations must go beyond simply recognizing the value of data — they need to continually reimagine how to create value as technology evolves. Suresh Venkatarayalu, Chief Technology and Innovation Officer at Honeywell, highlights how Honeywell is consistently innovating by leveraging data to benefit its customers. He notes, “As one of the largest manufacturers of sensors, Honeywell asks, ‘How can we use that data source to create meaningful outcomes for both our customers and the company?’”

By championing these values, CIOs can create a solid foundation for AI initiatives, ultimately driving more effective, innovative and responsible data use throughout the organization.

Align data strategies with impactful AI/ML use cases

According to a recent IDC report, spending on AI is expected to reach $26 billion by 2027. It’s no wonder two-thirds of IT organizations are gearing up to dedicate more than five percent of their budgets to AI projects. With that, CIOs must define clear missions that link data strategies to impactful use cases.

This starts with creating a governed, analytics-ready data environment where reliable data is readily available for AI/ML initiatives, and organizations can fuel innovation and deliver value faster. A high level of data maturity not only enhances decision-making but also accelerates the development of AI-driven solutions, helping companies stay competitive in a world where AI/ML is dominating conversations everywhere.

A strong data foundation future-proofs your business while providing a secure, scalable and reliable foundation. With it, your data is primed to unlock new opportunities and drive AI/ML innovations. CIOs are uniquely positioned to lead this transformative journey, steering their organizations toward a future brimming with potential and cutting-edge advancements.

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