CIOs face mounting pressure as AI costs and complexities threaten enterprise value

CIOs are under increasing pressure to deliver meaningful returns from generative AI initiatives, yet spiraling costs and complex governance challenges are undermining their efforts, according to Gartner.

Despite AI’s potential to transform businesses, many senior technology leaders find themselves wrestling with unpredictable expenses, uneven productivity gains, and growing risks as AI adoption scales, Gartner said.

“Because of the relentless innovation happening in the tech vendor race, CIOs feel like they are always living the hype, while the reality of their AI outcomes race — how tough it is to get value — makes it feel like they are also in the trough,” Mary Mesaglio, distinguished VP analyst at Gartner said in a statement.

In a survey of 451 senior technology executives conducted by Gartner in mid-2024, a striking 57% of CIOs reported being tasked with leading AI strategies. However, unlocking the full value of AI remains elusive, with four critical challenges standing in their way.

Uneven productivity gains create barriers

The first major challenge for CIOs is the uneven distribution of productivity gains from generative AI. While some of the surveyed employees in the US, the UK, Australia, India, and China reported saving an average of 3.6 hours per week by integrating generative AI into their workflows, these benefits are not felt equally across the workforce.

Gartner’s research shows that productivity improvements depend heavily on factors such as job complexity, employee experience, and personal engagement with AI tools.

“Here’s the real challenge with AI productivity,” Hung LeHong, distinguished VP analyst and Gartner Fellow said in the statement. “Productivity gains from GenAI are not equally distributed. Gains vary by employee, not just because of their personal interest and levels of adoptions, but according to the complexity of the job and level of experience.”

To address this, Gartner has recommended treating AI-driven productivity like a portfolio — balancing operational improvements with high-reward, game-changing initiatives that reshape business models.

AI costs spiral beyond control

The second, and perhaps most pressing, issue is the rising cost of AI implementation. Gartner’s data revealed that 90% of CIOs cite out-of-control costs as a major barrier to achieving AI success.

“Every enterprise must assess the return on investment (ROI) before launching any new initiative, including AI projects,” Abhishek Gupta, CIO of India’s leading satellite broadcaster DishTV said. “It’s essential to evaluate all AI initiatives using the same criteria. Once a specific business use case for AI is identified, a thorough cost estimation should be conducted and compared against the anticipated business outcomes to ensure alignment and value.

Without a precise understanding of how AI expenses scale, companies risk underestimating costs by as much as 1,000%, making financial missteps that could cripple broader technology initiatives, Gartner said.

“As a CIO, you need to understand your AI bill,” LeHong stressed. “You must understand the cost components and pricing model options, and you need to know how to reduce these costs and negotiate with vendors. CIOs should create proofs of concept that test how costs will scale, not just how the technology works.”

Governance and human challenges further complicate AI rollouts

Another formidable challenge is the governance and data management complexity brought on by the decentralization of AI capabilities. Gartner’s findings indicated that only 35% of AI solutions are built internally by IT, with the majority being developed outside traditional technology teams. This creates new risks around data privacy, security, and consistency, making it harder for CIOs to maintain control.

To navigate this, Gartner has advocated for a layered approach, describing it as a “tech sandwich.”

“This is where the concept of a ‘tech sandwich’ comes in,” LeHong said while describing the AI tech stack of the future. “On the bottom of the sandwich is all the data and AI from IT, typically centralized. On the top is all the data and AI coming from everywhere, typically decentralized. And the middle contains the trust, risk, and security management (TRiSM) technologies that make it all safe.”

It’s what you need to create to accommodate AI and data coming from everywhere,” he added.

“As CIO, your job is to design a tech sandwich that can handle the messiness of AI, but still keeps you open to new opportunities,” Mesaglio said.

Lastly, CIOs are facing the often-overlooked human impact of AI adoption. As AI reshapes workflows and roles, some employees may embrace it, while others could resist or even resent it — leading to workplace tensions that undermine productivity.

Gartner’s research shows that only 20% of CIOs are proactively addressing the behavioral risks AI poses to employee well-being, even though these risks can significantly impact performance.

“In today’s interconnected landscape, awareness of AI’s benefits is widespread, with tools like ChatGPT sparking significant interest,” Gupta stated. “This makes the CIO’s role in preparing business users for AI adoption much easier. In fact, business users are actively seeking ways to integrate AI into their workflows. However, the real challenge lies in identifying the right use cases where AI can enhance performance and deliver measurable project outcomes that justify the investment.”

These emerging challenges underscore the complexities of AI deployment at scale. For CIOs, success will depend not only on technological leadership but also on mastering cost control, governance, and the human side of digital transformation.