3 things cost-optimized CIOs should focus on to achieve maximum value

CIOs must do more with technology than ever before, and in challenging circumstances. As reported last year, digital leaders are being told to spend less on IT, but are still expected to drive innovation and keep the business thriving — a tough combination to achieve in an era when rapid AI-enabled transformations have become new norms.

Gartner reports that more than half of CIOs face pressure to improve productivity, and 52% are being asked to reduce costs. The message is clear that IT leaders must be radically outcome-focused, prioritizing initiatives that align with C-suite goals to deliver measurable impact.

Pioneering executives recognize that AI can help organizations reach these goals. Diana Schildhouse, chief data and analytics officer at Colgate-Palmolive, is focused on developing deep enterprise connections to ensure the solutions her team creates, whether through gen AI, advanced analytics, or something else, are tied to business requirements.

“We find key pain points of the business and then consider how we can help,” she says. “So it’s not a tech-first approach we’re taking. It’s about looking at the business, its processes, what people are doing, and exploring how we can apply our new technologies to the challenges they face.”

For Gartner, this focus on business value is a shortcut to success and suggests CIOs who implement strategic cost optimization, and strategically manage expenses to maximize business value and not just cut costs, will be 65% more successful in elevating their contribution to the organizational mission.

The challenge now is for CIOs to deliver long-term value from their AI and data investments, and evidence points to cost-optimized digital leaders creating a competitive advantage will concentrate on three key areas.

1. Shifting spend management tactics

Paul Neville, director of digital, data, and technology at UK agency The Pensions Regulator (TPR), says the importance of focusing on cost optimization shouldn’t be underestimated. IT departments don’t always have the best reputation for creating value from their technology investments, and that’s something that must change in an age of AI.

“I think, generally, digital leaders in the past have tended to talk about ‘the thing’ rather than the outcome they’re trying to achieve,” he says. “We haven’t been our own best friend, and I’m sure I made that mistake in the past. I’ve tried to learn that lesson.”

Neville has honed his cost-optimization capabilities during his digital leadership career. After working in the commercial sector at blue-chip companies such as Sky and BT, Neville decided to apply those skills for public benefit, working as a consultant for two major charities before taking on IT chief roles in local government.

In collaboration with the London Office of Technology and Innovation, he developed a toolkit of guidelines, templates, and best practices for digital leaders to navigate obstacles that prevent optimized technology procurement. And at TPR today, Neville continues to ensure users who demand emerging technologies ask the right questions.

“My job is to ask what are you trying to achieve,” he says. “By doing so, technology becomes part of the solution. Yes, emerging technology offers new opportunities, but we need to talk about those in business terms.”

For Lenovo CIO Art Hu, optimization involves managing a funnel of business-focused ideas. His company’s portfolio-based approach to AI includes over 1,000 registered projects across all business areas. Hu has established a policy for AI exploration and optimization that allows thousands of flowers to bloom before focusing on value.

“It’s important I don’t over-prioritize on quality initially, because we have so many projects,” he says. “If you’re too focused on the quality of every project, I think it slows things down. Then, when we’ve got projects to a certain scale, or we can combine them in certain ways that they can absorb true capital deployment in the millions or tens of millions at the group level, that’s when we think about quality.”

Lenovo supports a mix of AI initiatives that use off-the-shelf and bespoke models. Key use cases include conversation summarization to assist support specialists, applying agentic AI to enterprise-grade software engineering, and using gen AI to create marketing collateral. Hu says the key to harvesting the right projects is to manage risk and balance capital allocation.

“AI is no different than any other tool; it’s an additional parameter,” he adds. “You’ll have a budget, and you’ll want speed to market, but you have compliance, security, and other issues to deal with. AI is just one more thing to consider, but then it’s so high-profile that the challenge is accentuated right now.”

2. Integrating technologies

Even once you’ve created a longlist of AI projects, there’s no guarantee you’ll find gold. Careful guidelines for projects can help CIOs and their business peers identify use cases. However, turning AI explorations into valuable production services can be a challenging task that requires a focus on integration to ensure costs don’t spiral upward.

Fausto Fleites, VP of data intelligence at gardening specialist ScottsMiracle-Gro, has prioritized underlying foundations. His work at the company, which began in 2023, has involved deploying AWS technologies, Google services, and deep-learning models to create decision-making insights for the executive team.

Over the past year, Fleites has explored customer-focused use cases for generative and agentic AI. AI-enabled search, for example, runs via a RAG application in Google Vertex AI, where customers can use natural language to find answers to their questions. The company is also working with tech specialist Sierra to improve conversations in its web-based chat agent.

In addition, Fleites is exploring how staff can use AI as a copilot for work tasks. His organization has developed a production service, known as Email Rewrite, which takes text from internal Salesforce knowledge articles and creates coherent responses in seconds. Fleites says these kinds of initiatives can deliver high ROI, but integration is crucial to success.

“Right now, back-office automation isn’t a question of data,” he says. “If you look at an agent, for example, it’s an LLM that has instructions, but it needs access to tools to act. So to re-envision processes, that layer of tools is where the scalability needs to happen. The difficult part is integration with enterprise systems, such as ERP. That layer needs to grow.”

Research suggests integration is a common concern. Gartner reported last year that 77% of engineering leaders identify AI integration as a major challenge. Rupal Karia, SVP for North America, UKI, and MEA at technology firm Celonis, recognizes the importance of integration for cost-optimizing CIOs who aim to deliver valuable AI services.

“There’s a technology thing, where you probably need multiple types of models and tools to work together,” he says. “So Microsoft or OpenAI on their own probably won’t do very well. However, when you combine Databricks, Microsoft, and your agents, then you get a solution.”

That’s a suggestion that chimes with David Walmsley, chief digital and technology officer at jewelry specialist Pandora. He suggests the key to unlock value from AI-enabled services is the orchestration between different packages.

“You can sit with any one of these tech companies and they’ll tell you their version of AI,” he says. “But I’m not going to base my business around that vision. I need to consider how their technology works with all my systems.”

3. Achieving business value

Walmsley works with Pandora’s senior leadership team and its vendor partners, including Salesforce, SAP, and Microsoft, to develop use cases for emerging technologies. His key lesson for other CIOs is straightforward: focus on your points of competitive advantage.

Pandora is making three big bets in AI. The first is using agentic AI to improve customer service. The company has developed a partnership with Salesforce to use its Agentforce technology to manage an increasingly large proportion of online customer service requests. The second is new product development, says Walmsley.

“So how do we apply AI, tooling, thinking, and whatever machinery to how we take new products to market?,” he asks. “Then there’s automation across the whole back end of the organization, and what it can do in terms of shaping the operating model. For me, exploiting AI optimally is about creating a smarter business.”

At Colgate-Palmolive, Schildhouse has developed a framework to ensure the organization focuses its AI endeavors effectively. The framework includes horizontal elements, which are the tools and foundations that power AI efforts, and vertical elements, the organization’s priority areas for exploration, including innovation.

But another key area is revenue growth management. Schildhouse’s team has developed an in-house diagnostic and predictive tool to help employees make pricing decisions quicker. They tracked usage to ensure the technology was effective, and the tool was scaled globally. This success has sponsored AI-powered developments in related areas, such as promotion and calendar optimization technology.

“Scale is important at a company the size and breadth of Colgate-Palmolive, because one-off solutions in individual markets aren’t going to drive that value we need,” she says. “I travel around to our key markets, and it’s nice to be in India or Brazil and have the teams show how they’re using these tools, and how it’s making a difference on the ground.”