Technical Leaders Own 72% of Enterprise AI Purchasing Power

Austin, Texas, USA, November 11, 2025

Futurum Research reveals CTOs lead AI purchasing decisions at 25%, with technical roles controlling 72% of authority as organizations prioritize technical expertise over traditional business leadership.

Futurum Group today released groundbreaking research mapping AI decision-making authority across enterprises, revealing that Chief Technology Officers (CTOs) have emerged as the dominant force in AI purchasing decisions at 25%—more than double the authority of any other single role.

A comprehensive study of 838 organizations reveals that technical roles collectively control 72% of AI decision-making power, signaling a fundamental shift in how enterprises approach AI investments and reflecting the technology’s increasingly strategic importance.

The research revealed a striking concentration of power, with C-suite executives controlling 77% of all AI purchasing decisions. However, within this group, technical expertise clearly supersedes traditional business authority. While CEOs maintain influence at 11%, they now share equal decision-making power with Heads of AI/ML, and both trail significantly behind CTOs. This distribution suggests that organizations recognize AI implementation requires a deep technical understanding, rather than purely strategic business oversight.

Figure 1: Primary Decision-Making Authority for AI Software Tools and Infrastructure

Nick Patience, VP & AI Platforms Practice Lead at Futurum, said, “The CTO’s commanding 25% share of AI decision authority represents a watershed moment in enterprise technology governance. This isn’t just about who signs the purchase orders – it’s a clear signal that organizations view AI as a fundamental technical architecture decision rather than a traditional business software purchase. The fact that technical roles collectively control 72% of these decisions underscores that successful AI implementation is seen as primarily a technical challenge requiring deep expertise.”

The research reveals several critical patterns reshaping enterprise AI governance:

• Technical Supremacy: Technical roles (CTO, CIO, Head of AI/ML, CDO, VP Engineering, CISO) collectively control 72% of AI purchasing decisions, demonstrating that organizations prioritize technical expertise and implementation capability over traditional business considerations in AI investments.
• CTO Dominance: At 25%, CTOs hold more than double the decision-making authority of CIOs (12%), marking a shift from IT management to technology innovation leadership in AI adoption, and suggesting AI is viewed as a competitive differentiator rather than an operational tool.
• Emerging AI Leadership: The Head of AI/ML role, although relatively new in many organizations, already commands 11% of decision-making authority—equal to that of the CEO—indicating the rapid institutionalization of dedicated AI leadership and the recognition that specialized expertise is essential.
• Diminished CFO Influence: CFOs control only 7% of AI decisions, despite their typical involvement in major technology purchases, suggesting that AI investments are driven more by strategic capability needs than traditional ROI calculations, reflecting AI’s transformational rather than incremental nature.

The concentration of authority in technical roles has profound implications for AI vendors and implementation strategies. With 77% of decisions made at the C-suite level but heavily skewed toward technical executives, successful AI adoption requires both executive sponsorship and deep technical credibility. The data suggests organizations have learned from earlier digital transformation efforts that technical leadership is crucial for successful implementation.

“The tie between CEOs and Heads of AI/ML at 11% each is particularly telling,” Patience added. “It shows that while CEOs remain engaged in AI strategy, organizations are equally empowering specialized AI leaders with direct decision authority. This dual approach—strategic vision from the CEO combined with technical expertise from dedicated AI leadership—may represent the optimal governance model for AI success.”

The findings also highlight potential challenges for AI vendors accustomed to selling through traditional business channels. With technical leaders controlling the majority of decisions, vendors must adapt their sales strategies to address technical depth, architectural implications, and implementation complexities rather than focusing solely on business outcomes and ROI metrics.

Read more in the 1H 2025 AI Platforms Decision Maker Survey Report on the Futurum Intelligence Platform.

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