CIOs: Collect the right data now for future AI-enabled services

AI requires a gut-busting diet of data. Whether it’s structured or unstructured information, CIOs must create the technological foundations to ensure their organization has the data its AI-enabled services require.

Global IT spending is expected to total $5.61 trillion by the end of the year, an increase of 9.8% from 2024, according to Gartner’s annual forecast, adding that investments in data center systems, devices, and applications will see double-digit growth this year as well, due largely to upgrades in response to the business demand for gen AI projects.

However, while companies invest in the kit to exploit AI, establishing a reliable and trusted information feed is far from straightforward, especially given tight governance requirements and flexible customer demands. Add in the rapid pace of business transformation and collecting future-ready information becomes an even tougher prospect.

In its Technology Trends Outlook for 2025 report, McKinsey suggests the technology landscape continues to undergo significant innovation-sponsored shifts. The consultant says success will depend on executives identifying high-impact areas where their businesses can use AI, while addressing external factors such as regulatory shifts and ecosystem readiness. 

CIOs, as the guardians of enterprise technology, will be expected to embrace this challenge, but how? For Steve Lucas, CEO at technology specialist Boomi, digital leaders must start with a recognition that the surfeit of data held in modern enterprises is simply a starting point for what comes next.

“There’s plenty of data,” he says. “In fact, there’s too much of it. We worry about collecting, storing, and accessing data. I think a successful approach is about determining the data that matters. As a CIO, do you understand what data matters today and what emerging technologies will matter tomorrow?”

Our conversations with digital leaders suggest that organizations with a firm grip on their data take a structured approach. They focus on business strategy and think carefully about the information the business needs. Then they refine the data the organization collects for its current initiatives before addressing long-term objectives.

Connecting data to the business strategy

What’s crucial when it comes to collecting the right information, says Kenny Scott, data governance consultant at energy specialist EDF Power Solutions, is engaging with the people who run the business. Digital leaders must ensure their data projects are connected to and driven by the business strategy.

“Look at the business plan from your C-suite,” he says. “Where does the business need to be, and then, how does data enable that journey? Your board will sort out the people and the budget. But what do you need to do to help them deliver their strategic goals?”

At EDF, Scott has helped to create a data infrastructure, which he refers to as the engine room, that includes Informatica as the foundation, Snowflake as the core, and Power BI as the cockpit, through which users turn information into insight. With data sifted and sorted, it’s easier to run data-powered projects that solve strategic business challenges.

Scott says this problem-first approach to data is a significant break from the past. He refers to earlier stages of his career in financial services, when people would buy technology and then look for a problem to solve. Yet even today, when the value of data is recognized across organizations, too many data projects are still led by the desires of IT professionals.

“I saw the tail wagging the dog in banking back in the 1990s, where IT told the business what they needed to do, but you can still see that approach now,” he says. “People will come up with a requirement. They’ll buy a tool that’ll do it, but there’s no consideration given to the mapping, provision, and ownership of data. Instead, digital leaders should start with the business strategy.”

That approach resonates with Fausto Fleites, VP of data intelligence at ScottsMiracle-Gro, who says his company has a clear business strategy to be the “sommelier for every consumer in the lawn-gardening space.” With that broad goal in mind, Fleites and his team then ask specific questions about the information required.

“If I want to use AI for that goal, what data do I need?” he says. “I’ll need a lot of content in the right format about troubleshooting, likely questions from consumers, and product recommendations. That strategic focus is an easy guide for us into what data we need. We have most of that information, and success is just about structuring data the right way.”

Fleites suggests the fine details of this tailored approach vary with industry and business. However, the overarching principle is the same: “Start with the vision of how you want to engage or change your operations,” he says, “and that should drive the type of data you’re collecting.”

Exploiting your existing assets

With a clear sense of business strategy in mind, digital leaders should turn to the information that’ll help the organization meet its objectives. However, Richard Corbridge, CIO at property specialist SEGRO, recognizes that collecting the right data now for future projects is far from simple.

“How do you know you’re collecting the right stuff, particularly in property?” he says. “We’re 120 years old so imagine the amount of data on billions in assets.”

While it can be tough to find the wood for the trees, Corbridge suggests CIOs should search for established data roots within the enterprise. “It’s about going back to the huge volumes of data you’ve got already and working out how you put that information in the right place so it can be used in the right way for your AI projects,” he says.

Focusing on the fine details is an approach that chimes with Ian Ruffle, head of data and insight at UK breakdown specialist RAC. He suggests it’s far too easy for complex organizations to collate data that’s rarely used. Rather than taking a liberal approach to information collection, focus on what’s important to your business now.

“A data science model, where you throw 60 variables into it, isn’t going to say every insight is useful,” he says. “It’s going to say four or five variables make the difference. I think that same principle applies to data collection. Don’t focus on the quantity of data collection, but the quality and what’s truly important, and do those things brilliantly.”

Ultimately, suggests Dominic Redmond, CIO at recruitment firm PageGroup, digital leaders must work with their existing data assets. Rather than struggling to collect information that might be valuable in the future, CIOs should focus on sifting for valuable nuggets from existing data sets.

“That’s probably the more important question than what data are you gathering, because you’ve already got all your data, whether it’s structured or unstructured,” he says. “Focus on the areas of that data you’ll need in the future to create value and benefit.”

Concentrating on long-term outcomes

Chris Belasco, chief data officer at the City of Pittsburgh, said municipal organizations have a long history of constraining their data efforts to ensure costs are controlled and data is saved securely. Enterprise digital leaders should aim to create a similarly focused approach.

“Try to be thoughtful about the desired outcomes and make sure you’re intending to achieve the things you want to realize,” he says. “If you lead your data efforts with your outcomes in mind, you’ll be thinking forward about what you need to collect in terms of information today for five years from now.”

The rapid pace of technological innovation we’ve witnessed this decade will only accelerate. CIOs can’t know with certainty the data that’ll be most valuable five or 10 years from now, so the only option is to be guided by senior executives who understand the finer details of business functions.

Sacha Vaughan, chief supply chain officer at homeware manufacturer Joseph Joseph, says her firm utilizes its SAP-based data foundations to help surface important insights. While she’s interested in exploring the potential of AI for the business, the current priority is to identify data points that point to new trends.

“We’re interested in mining any interaction point with customer satisfaction ratings,” she says. “We want to sort that data in a way so it’s not just numbers about how many people are happy, but that we know what they specifically mean, which gives us insights into how we can show up differently and engage them with the brand in the future.”

Inevitably, suggests Gro Kamfjord, head of data at paint manufacturer Jotun, the key to successful data collection is building a tight bond with the board. To reiterate, digital leaders who link data initiatives to business strategy will be more likely to achieve long-term outcomes than being tied to isolated use cases in the present.

“Data isn’t a by-product or something you do on the side, it’s the core of what your business is doing,” she says. “So get senior executives to focus on that relationship and keep the people making the decisions accountable for the outcomes and the costs.”