McKinsey Warns Firms Must Trim Tech Spend as AI Budgets Surge

Why It Matters

The budget trade‑off highlighted by McKinsey signals a structural shift in how enterprises allocate technology spend. As AI projects consume a larger slice of limited budgets, the need for strategic guidance on prioritization becomes a growth engine for management consultants. This dynamic could accelerate the adoption of outcome‑based consulting contracts, reshaping revenue models across the industry. Moreover, the pressure on legacy systems raises systemic risk. Under‑funded maintenance can lead to outages, security breaches, and reduced operational efficiency, which in turn can erode the very productivity gains AI promises. Consulting firms that can help clients navigate these interdependencies will not only capture market share but also influence the broader trajectory of digital transformation across sectors.

Key Takeaways

• McKinsey senior partner Noshir Kaka says typical tech budget hikes of 6‑7% fall short of the 20% capacity needed for AI adoption
• Companies must cut spending on legacy systems and lower‑priority projects to fund AI, data modernization and digital work
• The AI Impact newsletter highlights a forthcoming webinar on May 28 titled “The Trillion‑Dollar Question: Who Wins and Who Loses in the Services Economy?”
• Consulting firms that can demonstrate ROI‑focused, outcome‑based services are poised to win new business as firms re‑allocate spend
• Budget constraints could push the consulting industry toward performance‑linked pricing and holistic portfolio optimization

Pulse Analysis

The McKinsey warning reflects a broader inflection point where AI is no longer a peripheral experiment but a core growth lever demanding disproportionate resources. Historically, technology budgets grew in line with overall corporate spending, allowing legacy systems to be maintained alongside innovation. Today, the AI surge is compressing that elasticity, forcing CEOs to make zero‑sum decisions. Consulting firms that have already built AI‑ready frameworks—combining data strategy, change management and KPI‑driven delivery—will capture the lion’s share of advisory spend. Those still anchored in traditional, siloed implementation models risk being sidelined.

From a market perspective, the budget squeeze could catalyze consolidation among consulting players. Larger firms with deep bench talent can bundle AI strategy, legacy modernization, and risk management into a single offering, creating economies of scale that smaller boutiques cannot match. Yet, niche players that specialize in rapid AI prototyping or industry‑specific AI use cases may thrive by offering lean, outcome‑based contracts that appeal to cost‑conscious clients. The upcoming AI Impact Forum will likely surface concrete pricing models, such as shared‑risk or success‑fee structures, that could become the new norm.

Looking ahead, the tension between AI investment and legacy upkeep will shape the consulting agenda for the next 12‑18 months. Firms that help clients quantify the true cost of deferred maintenance—potentially in terms of downtime, security incidents, or lost productivity—will provide the data‑driven justification needed to balance AI spend. In turn, this could spur a wave of hybrid consulting engagements where AI pilots are tightly coupled with modernization roadmaps, ensuring that short‑term AI wins do not undermine long‑term operational resilience. The firms that master this balance will define the next generation of management consulting services.