CIOs Recast AI Transformation Around Growth, Value and Board Accountability
Enterprise technology leaders are facing mounting pressure to translate artificial intelligence investments into measurable financial and competitive gains as boards move beyond enthusiasm for experimentation and begin demanding evidence that transformation spending is improving performance.
The shift is altering how CIOs select projects, organize technology teams and communicate with boards and executive peers. It now increasingly appears that AI roadmaps and successful proofs of concept carry less weight when they cannot be connected to revenue, margins, customer experience, productivity or other measurable business outcomes.
Recent industry research supports that shift toward greater accountability. In an August 2026 research note, Gartner found that maintaining confidence in AI investments increasingly requires evidence of business outcomes rather than technical milestones. Meanwhile, ISG has documented a similar gap between adoption and results. Its study of 1,200 enterprise AI use cases found that 31% of prioritized initiatives had reached production, while only about one in four was meeting expectations for growth-related returns. The findings suggest that getting AI into production is becoming a less meaningful measure of success than demonstrating what those deployments actually contribute to business performance.
For CIOs, this trend raises the stakes surrounding an already expanding mandate. Technology leaders are being asked with increasing frequency to participate directly in growth and profitability initiatives while simultaneously controlling AI spend, reducing legacy technology costs and maintaining governance over systems that are widely distributed across the enterprise.
According to Eduard de Vries Sands, a veteran technology executive who recently discussed the changing CIO mandate during a BizTechReports executive vidcast interview, the last couple of quarters have seen board expectations move from fascination and FOMO with AI to an intense desire for documented accountability on its economic impact. De Vries Sands’ perspective comes from a front-row seat as a senior technology executive who has served as CIO at EVERSANA, and Axia Women's Health. He was also named a 2025 ORBIE Global CIO Award Finalist, a peer-nominated honor recognizing top technology executives.
From these roles, he has seen an evolution take place in which boards of directors that previously wanted to know whether their organizations had AI strategies increasingly want to know what those strategies have produced. That means technology leaders must demonstrate whether investments are improving profit-and-loss performance, strengthening competitive positioning or creating additional value for customers.
Business Outcomes Begin to Drive Technology Decisions
As a result, the traditional process of identifying a technology, developing a roadmap and selecting applications is giving way to a more market-driven approach in which technology teams begin with a business problem and work backward toward the capabilities needed to address it.
De Vries Sands contends that CIOs can strengthen that understanding by spending more time where customers and employees actually interact with the business. Sales ride-alongs, customer meetings and direct observation of frontline operations can expose opportunities that may remain hidden when transformation planning is conducted primarily through executive presentations and technology assessments.
He recalled observing employees in a veterinary clinic while working on what initially appeared to be an “order processing” problem. Watching a veterinary technician search through a large reference book revealed that the more important challenge involved identifying the appropriate diagnostic test as orders were planned and executed. Seeing the problem first hand, he says, changed the potential technology intervention from improving transactions to improving information discovery.
Direct exposure to operations, adds de Vries Sands, can also strengthen CIO credibility with boards. Technology executives who develop a “hands on” approach to understanding their business occupy a position that allows them to move across functional boundaries, observe workflows and connect operational problems with technology capabilities. That perspective is capturing the attention of boards that expect technology leaders to explain transformation in financial and operational terms.
Recent Gartner research reinforces that shift. The firm says CIOs increasingly need to co-own business results, develop a deeper understanding of how their organizations operate and communicate technology's contribution in business and financial terms as CEOs place greater emphasis on outcomes rather than technology outputs.
It also changes how organizations should measure AI initiatives. Rather than evaluating a project primarily according to whether a new application, feature or release is completed, de Vries Sands recommends establishing measurable business objectives such as reducing customer-order processing time by 10%. Cross-functional teams can then be given a defined period to demonstrate whether their approach produces the intended result.
From that point forward, a disciplined approach to keeping score becomes critical. Projects that fail to deliver should be stopped and resources immediately redeployed, he says. That discipline will help enterprises avoid the expensive consequences of widespread AI experimentation that result in enterprise technology portfolios of partially deployed pilots with limited, if any, value
AI Investment Raises Pressure to Retire Legacy Systems
The agentic-influenced economics of transformation have elevated technical debt to a critical business imperative from simply being an IT maintenance problem. While AI can potentially extend the usefulness of existing infrastructure, de Vries Sands argues that organizations need to connect modernization initiatives with deliberate efforts to retire obsolete systems in order to extract the full intended value of major transformation initiatives.
Technology leaders, he states, must become masters of turning things off. A migration is incomplete when the replacement platform is operating but the previous system remains active for some niche reason. Over time, it is a practice that will lead to enterprises accumulating hundreds of applications that require maintenance even though they contribute little operational value. The resulting expense can gradually shift technology budgets away from investments in growth and differentiation and toward value-neutral maintenance.
He suggests that one way to counter that pattern is to link the introduction of new business capabilities with the retirement of legacy technology. An AI-enabled capability, for example, can be implemented as part of a broader modernization effort that also eliminates an older application or workflow.
That pairing addresses an enduring prioritization problem. Business leaders generally have stronger incentives to fund capabilities associated with growth than projects dedicated primarily to shutting down aging systems. Without an explicit connection between the two, retirement programs can repeatedly be deferred.
Bundling tech debt retirement with growth-oriented transformation strategies can yield compounding effects. Fewer legacy platforms mean fewer systems to secure, integrate and maintain. This frees up resources for initiatives that increase the speed with which organizations can respond to changing business requirements.
That simplification can change how technology initiatives are organized. As platforms become more integrated and technology becomes more deeply embedded in business processes, traditional boundaries between IT and operating functions become less useful because transformation increasingly requires teams built around business outcomes rather than technology domains.
Organizational structures are beginning to reflect the same shift. AI agents could accelerate that evolution by assuming portions of routine work and allowing employees to concentrate on higher-value activities. De Vries Sands cautions, however, that it remains too early to determine how extensively agentic systems will reshape organizational structures.
Concluding Thoughts
AI has undoubtedly expanded the range of transformation opportunities available to enterprises, says de Vries Sands. It has also, however, increased technology spending, and with that, board scrutiny. It is a combination that will ultimately prove more consequential than the technology itself. For technology leaders, the emerging mandate is increasingly tied to the same measures that define the performance of the enterprise itself, he concludes.
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