Table of Contents
- Key Highlights
- Introduction
- The Burgeoning Focus on AI
- The Reallocation Dilemma
- Strategic Adaptation in IT Budgets
- Evaluating the Return on Investment
- Conclusion: The Way Forward
- FAQ
Key Highlights
- The percentage of IT budgets allocated for AI projects has nearly tripled in 2025, reshaping IT priorities across sectors.
- CIOs face mounting pressure to prioritize AI initiatives over traditional IT projects, leading to potential risks in areas like modernization and technical debt.
- Successful governance and strategic prioritization are essential for CIOs to balance AI investments with other critical IT needs.
Introduction
As 2025 dawns, the urgency for organizations to harness the power of artificial intelligence (AI) has surged, leaving many Chief Information Officers (CIOs) grappling with the implications of these swift changes. In a striking illustration of this trend, the latest edition of the 2025 CIO Playbook, published by Lenovo and IDC, reveals that nearly one-third of IT budgets is now earmarked specifically for AI projects—an increase of almost 300% from the previous year. This dramatic shift reflects not only the heightened corporate enthusiasm surrounding AI but also the significant recalibration of IT project priorities that such a surge necessitates.
As boards and executive teams intensify their focus on AI capabilities, many CIOs report facing a tough dilemma: how to balance this mounting AI enthusiasm with the essential long-term investments in legacy systems, architecture updates, and emerging technologies that could otherwise bring future benefits. This article dissects the current landscape, exploring the implications of aggressive AI investment strategies and the strategic recalibrations they demand from IT leaders.
The Burgeoning Focus on AI
The dramatic increase in AI funding signifies a shift in the competitive landscape, where staying ahead is synonymous with rapid deployment of AI solutions. This perception of urgency mandates that CIOs prioritize AI spending above other IT initiatives. According to Dhaval Moogimane, a consultant at West Monroe, “Budgets are finite... AI shrinks the dollars available for other initiatives, and so the line on priorities is being drawn differently.”
This sentiment is echoed across the board, with IT departments increasingly compelled to either deprioritize historically important projects or pause ongoing initiatives to redirect resources towards AI. For example, Marco Bill, the CIO at Red Hat, notes that this recalibration is not a new phenomenon; however, the explicit pressure to “do AI” has made it more pronounced. “There are always projects that are delayed,” he says, emphasizing the significance of maintaining a coherent project priority approach in the face of sudden shifts.
Risks of Deprioritizing Legacy Systems
With the spotlight firmly on AI, many CIOs have reported deferring crucial IT projects that would typically receive attention. Sumeet Gupta, a senior managing director at FTI Consulting, suggests that these decisions often lean toward the “low-hanging fruit” of AI, frequently at the expense of addressing technical debt or modernizing legacy systems and architecture. “This kind of longer-term investment that’s getting pushed off can be to their detriment,” Gupta warns.
Neglecting foundational technology maintenance for trendy AI initiatives can pose substantial risks. Ignoring modernization efforts could hinder an organization’s ability to leverage AI opportunities effectively, thereby allowing competitors who have prioritized data architecture upgrades to gain a significant market advantage.
The Reallocation Dilemma
The stark realization that organization-wide transformation is rarely feasible within a single budget cycle raises questions about the long-term sustainability of the current focus on AI. Companies may find themselves caught in a loop, where the need for AI experimentation overshadows the urgent need for broader technology upgrades. According to Fabien Cros of Ducker Carlisle, “Many companies are trying to leapfrog... but there’s no way they can leapfrog.” This “keeping everyone hostage” scenario to outdated technology can ultimately lead to exponential costs in future transformations.
Research from Softserve illustrates this concern; 73% of tech leaders report that resources devoted to the latest generative AI trends have come at the expense of more fundamental data and analytics initiatives. For CIOs, this pushing aside of essential groundwork raises fundamental questions about risk versus opportunity, exposing organizations to pitfalls down the road.
Innovations in Governance
Balancing AI initiatives with ongoing projects hinges on strong governance practices. As companies transition from reactive modes driven by hype to more strategic considerations, effective governance will play an increasingly critical role in determining investment outcomes. Gupta articulates this change, suggesting that organizations are moving toward a more calculated approach to funding decisions.
Kathy Kay, CIO at Principal Financial Group, stands as a testament to the need for strategic governance. Rather than capitulating to management's AI demands, she centers her team’s efforts around strategic objectives aligned with long-term growth. “AI is only one of the enabling technologies that will help get efficiencies for us and drive growth,” Kay asserts.
By continuing to address other essential IT projects alongside AI initiatives, Kay exemplifies a balanced approach where governance and strategic context remain paramount.
Strategic Adaptation in IT Budgets
As the market embraces AI-driven projects, CIOs are also recognizing the need for more robust portfolio management, enabling them to streamline project prioritization aligned with overarching business goals. “We were seeing a lot of people in a reactive mode... but I think companies are now getting smarter and trying to do more prioritization,” Gupta confirmed.
This evolution is not just operational but indicative of a broader cultural shift within organizations; IT leaders are tasked with addressing business problems rather than solely focusing on the technologies available to them. Yet, even with increased scrutiny in traditional initiatives, AI remains a primary focus, often sailing through budgetary approval processes due to its perceived potential for high ROI over more conventional IT projects.
Evaluating the Return on Investment
The necessity for CIOs to quantify the returns on their investments in AI has become more critical than ever. Despite the low bar for AI project approvals, many CIOs are aware that this can lead to inefficiencies and waste if not managed properly. “With AI, there is a big data investment required, and sometimes it’s hard to justify spending on data initiatives,” Moogimane explains.
CIOs must strike a balance between funding high-impact AI projects while ensuring foundational investments in data management continue. Initiatives such as data cleanup and infrastructure updates are foundational, and although they often face challenges in justification, they are essential for successful AI implementation.
Conclusion: The Way Forward
As this race to AI adoption accelerates, a recalibration of IT agendas requires a level of maturity in organizational governance and project management. CIOs are urged to remain vigilant about the balance between immediate AI ambitions and long-term technological investments. Navigating this landscape successfully hinges upon prioritization, robust management strategies, and a clear understanding of how best to leverage emerging technologies without neglecting the essentials.
In the face of substantial pressure for immediate results from AI investments, organizations and their CIOs must foster discussions that enable meaningful insights and strategies. By focusing on alignment with broader enterprise objectives and emphasizing sustainable governance practices, they can navigate the complex interplay of AI priorities and foundational IT needs.
FAQ
What percentage of IT budgets is now allocated for AI projects?
According to the 2025 CIO Playbook from Lenovo and IDC, nearly one-third of IT budgets is allocated for AI projects, reflecting a dramatic increase of approximately 300% from the previous year.
Why are some traditional IT projects being deprioritized?
The urgency to invest in AI has led many organizations to shift their budgets away from legacy system modernization and technical advancements, prioritizing AI initiatives at the expense of other essential IT projects.
How can organizations manage the risks associated with AI-focused spending?
Organizations can mitigate risks by implementing strong governance processes, maintaining open communications regarding project priorities, and ensuring that foundational technology needs do not get sidelined in pursuit of AI pursuits.
Are traditional IT investments still seen as valuable?
Yes, while the focus on AI has increased, there remains a critical need for traditional investments in data management, infrastructure, and modernization to support future AI advancements.
What governance practices can CIOs implement to ensure balanced IT spending?
CIOs should encourage stakeholder communication, align IT projects with overarching business goals, and enforce regular assessments of project ROI while ensuring that foundational initiatives are funded adequately.