Supply chain leaders helped companies navigate pandemic disruptions, e-commerce growth and geopolitical volatility, yet many CEOs still look elsewhere for guidance on AI and future growth initiatives. New Gartner research suggests operations executives must connect network expertise more directly to commercial outcomes if they want a larger voice in strategic decisions.
CEOs Want Growth, Not Another Risk Briefing
Gartner VP analyst Atul Dighe told attendees at the firm’s recent supply chain symposium that chief executives rank operations and supply chain leaders near the bottom of the internal roster when choosing partners to drive performance improvements and new initiatives such as artificial intelligence. Finance leaders sit at the top of that trust list, a signal that capital discipline and earnings resilience still carry decisive weight in boardroom debates.
The trust gap lands at a volatile moment. CEO tenure at large companies is shrinking, with Fortune 100 chiefs now lasting on average under nine years and about 40% exiting within five, according to Dighe’s analysis. Recent leadership surveys, such as the Conference Board’s CEO Confidence Index hovering around 50, show hesitation to commit to bold moves while economic signals, geopolitical tension, and regulatory flux remain elevated.
Risk appetite is already contracting. Gartner research cited by Dighe indicates almost half of CEOs have pulled back on risk tolerance, and roughly 40% are scaling down or withdrawing from specific countries or regions to avoid tariffs, trade friction, and political instability. Many are reshaping footprint and tax strategies, but they often do so without fully leveraging the insight buried in operations data and network models.
This is where expectations for supply chain leadership are shifting. Boards want tariff-efficient and capital-light networks, but they also want credible pathways to growth in uncertain markets. Operations teams have refined playbooks for continuity and cost control; CEOs now need the same teams to frame AI and network redesign as engines for new revenue, margin expansion, and customer relevance rather than as additional layers of risk to be managed.
From Spreadsheet Steward To AI Storyteller
Artificial intelligence is the sharpest edge of this tension. Dighe described AI as one of the boldest bets modern enterprises have made, yet many organizations still struggle to translate pilots into measurable return on investment. Industry reports echo that experience, noting that logistics, planning, and procurement groups often run isolated proofs of concept that never become embedded decision systems.
Gartner’s message is that operations leadership has the vantage point to change that trajectory. These teams sit on end-to-end data from demand signals through supplier performance and logistics execution, giving them a uniquely rich context for training models, testing copilots, and building digital twins. What is missing, Dighe argued, is not technical access but narrative influence inside the C-suite.
The prescription centers on influence as the mechanism for rebuilding trust. Dighe urged operations executives to reposition themselves as ‘chief future officers’, joining CEOs in setting the direction for AI-enabled transformation rather than arriving later to carry out a technology agenda defined elsewhere. That requires fluent translation between operational realities and growth narratives that resonate with boards and investors.
Story quality becomes a strategic skill. Instead of leading with dense dashboards or backward-looking variance reports, Dighe recommended forward-leaning stories grounded in customer impact, working capital velocity, and resilience metrics. For example, an AI-driven control layer that shortens disruption response time can be framed in terms of revenue preserved, premium service maintained, and exposure to trade barriers reduced, not only in terms of forecast error improvements.
Gartner’s research and broader market data indicate that AI investments gain traction when they are presented as integral to commercial strategy and capital allocation. That means supply chain leaders must arrive at the table with clear business cases that connect orchestration platforms, predictive risk sensing, and generative AI copilots to tangible outcomes such as market entry options, SKU portfolio decisions, or the ability to rewire sourcing around new tariffs.
Where AI Investment Decisions Will Be Won
As AI spending expands, competition for capital will increasingly depend on the quality of the business case rather than the sophistication of the technology. Operations leaders have access to some of the richest enterprise data on demand, inventory, suppliers and customer service, but data alone rarely secures executive support. Organizations that connect AI-enabled supply chain capabilities to revenue growth, market responsiveness and capital efficiency are likely to have greater influence over investment priorities than those presenting AI primarily through the lens of operational performance or risk reduction.
