Balancing the costs and opportunities of GenAI adoption

Generative AI (GenAI) is reshaping how businesses operate, offering unprecedented opportunities for greater efficiency, streamlined operations, revolutionized customer service, and enhanced decision-making. But alongside its promise of significant rewards also comes significant costs and often unclear ROI. For CIOs tasked with managing IT budgets while driving technological innovation, balancing these costs against the benefits of GenAI is essential.

In this article, we will explore the cost-related barriers to GenAI adoption, including high implementation expenses, ineffective cost management, and infrastructure demands. We’ll also examine strategies CIOs can use to address these challenges, ensuring their organizations can recognize the rewards of GenAI without compromising financial stability. While the article’s focus is on GenAI, many of the strategies discussed here are broadly applicable to other innovations in IT, as they provide CIOs with a flexible framework for balancing costs and opportunities presented by emerging technologies.

Let’s begin by examining the specific cost-related concerns CIOs face when adopting GenAI technologies.

Cost-related concerns

IDC’s Future Enterprise Resiliency and Spending (FERS) Survey, Wave 10, October 2024, highlights key barriers of evaluating or expanding GenAI use:

Credit: Future Enterprise Resiliency and Spending Survey, Wave 10, October 2024 (n = 70 IT C-level executives)

In the graph above, three of the top eight primary concerns voiced by IT executives about GenAI adoption are cost-related:

• High adoption costs: Topping the list of concerns, 33% of IT executives cite the excessive costs of adopting GenAI-enhanced applications as a significant barrier.
• Ineffective cost management: Over 22% of IT executives highlight challenges in managing costs and developing clear ROI methodologies. This emphasizes the difficulty in justifying new technology investments without clear, tangible financial returns.
• Excessive infrastructure costs: About 21% of IT executives point to the high cost of training models or running GenAI apps as a major concern. Upgrading systems to accommodate advanced workloads can be especially prohibitive for organizations trying to scale AI initiatives across multiple business units.

These concerns emphasize the need to carefully balance the costs of GenAI against its potential benefits, a challenge closely tied to measuring ROI. Unlike traditional IT investments, the benefits of initiatives like GenAI can be hard to quantify in the early stages. CIOs must develop a clear strategy for projecting and demonstrating ROI to ensure that innovation investments align with organizational goals. See also: Gen AI in 2025: Playtime is over, time to get practical.

The challenge of ROI in innovation

The same IDC survey reveals that 58% of IT executives anticipate higher IT spending in 2025 compared with 2024. Among these, 21% attribute GenAI as the dominant driver of the increase in IT spending, while another 44% see it as a significant factor.

Credit: Future Enterprise Resiliency and Spending Survey, Wave 10, October 2024 (n = 36 IT C-level executives who indicated higher IT spending in 2025 than 2024)

This trend is expected to only intensify in 2026, where IT executives project GenAI budgets will more than double — from an average of $3.45 million in 2025 to $7.45 million in 2026, covering infrastructure, models, applications, and services.

Credit: Future Enterprise Resiliency and Spending Survey, Wave 10, October 2024 (n = 70 IT C-level executives)

While these rising budgets reflect optimism about GenAI’s potential, they also create pressure to justify every dollar spent. Some of GenAI’s most transformative advantages, such as improved decision-making or enhanced customer experience, can be difficult to quantify, making ROI calculations complicated. At the same time, organizations must maintain a realistic understanding of their AI maturity to avoid overestimating readiness or scaling too quickly. CIOs, therefore, need a clear strategy for aligning GenAI investments with organizational capabilities and business objectives to justify both current spending and future growth.

Practical strategies for CIOs

To manage costs effectively while fostering innovation, CIOs can implement the following strategies:

• Start small: Pilot programs minimize financial risk while providing insights into the feasibility and impact of new technologies. Focus on small-scale initiatives with clear objectives to demonstrate value early.
• Examine integration requirements with existing applications: Integration can be a significant cost driver, but when done well, it also maximizes the value of GenAI by seamlessly embedding it into business processes.
• Optimize existing infrastructure: Evaluate whether current IT systems can support new projects before pursuing upgrades. Strategic enhancements to existing systems, coupled with cloud-based platforms, can reduce costs and improve scalability.
• Prioritize high-impact use cases: Identify projects with measurable benefits that can give quick wins. For example, AI-powered customer service chatbots or automation tools often deliver immediate, noticeable benefits and can help justify further investment. 
• Engage stakeholders: Work with finance and operations teams to align on budgets, shared goals, and success metrics.
• Leverage external expertise in the short term: Partnering with consultants or cloud providers can help move projects forward faster than waiting to build up internal skills. However, relying on external expertise over the long term can drive higher costs and increase the risk of vendor lock-in, making it essential to plan for internal knowledge transfer.

Conclusion

Balancing the costs and opportunities of GenAI adoption is among the most significant challenges faced by today’s CIOs. This technology offers transformative potential, but it also demands thoughtful financial management and strategic planning. By adopting a measured approach — starting small, optimizing existing resources, and aligning initiatives with organizational goals — CIOs can unlock the full power of these technologies without jeopardizing fiscal stability.

As IT budgets expand and GenAI drives strategic priorities, CIOs must seize the opportunity to lead their organizations into a future defined by innovation and sustainable growth. With careful planning and a commitment to measurable outcomes, businesses can thrive in this era of rapid technological advancement.

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Mona Liddell is a research manager for IDC’s CIO Executive Research team. She is responsible for leading the creation, analysis, and delivery of quantitative-based research and related marketing content for business and technology leaders. This research provides guidance on how to leverage technology to achieve innovative and disruptive business outcomes. Mona has over 10 years of experience using data to drive actionable insights and recommendations. Prior to joining IDC, Mona served as a market insights advisor for the IBM infrastructure team. She led large-scale primary research studies and advised the IBM Systems and IBM Cloud teams and executive leadership on strategy, market dynamics and trends, and competitors.