Gartner: Why Do Supply Chain Firms Lack AI Strategies?

Pressures to demonstrate rapid benefits are causing Chief Supply Chain Officers (CSCOs) to potentially undermine the long-term possibilities of AI transformation within their operations.

A new survey from Gartner highlights that merely 23% of supply chain leaders report having a well-defined AI strategy actively in place across their organisations.

Benjamin Jury, Senior Principal, Research in Gartner’s Supply Chain practice, emphasises the need for a balanced approach.

“CSCOs feel pressure to achieve short-term ROI from their AI investments, but they must ensure these quick wins don't create future constraints.

“Without a structured approach, organisations risk creating inefficient systems that struggle to scale and adapt to evolving business demands.”

Expectations vs reality

Gartner’s analysis, based on a survey of 120 supply chain leaders who had implemented AI in their companies between December 2024 and January 2025, identifies significant discrepancies between the expectations surrounding AI and the actual outcomes witnessed within their supply chain functions.

One key variance lies in how investment decisions were made.

Most CSCOs confessed to adopting a "project-by-project" approach geared toward achieving immediate wins, rather than pursuing more comprehensive and strategically aligned, long-term approaches to investment and transformative initiatives.

This fragmented investment strategy presents a considerable risk.

By concentrating primarily on short-term gains, CSCOs risk sacrificing the complete, transformative potential of AI.

They may also deviate from the overall strategic aims of leveraging AI to stimulate broader organisational expansion.

The issue boils down to building effective, scalable systems that truly move the needle for digital transformation.

Benjamin notes the sporadic AI investment approach often results in "franken-systems”, or inefficient, complex and layered architectures that extend the payback period for AI transformations and hinder scalability.

While initial gains are attractive, prioritising immediate ROI can lead to less desirable long-term benefits and a technically fragile architecture.

The survey underscores that supply chain leaders are heavily focused on bottom-line metrics when evaluating AI success.
Gartner’s findings show that efficiency, decision-making speed and cost reduction are prioritised over factors such as innovation or revenue growth.

Fundamentally, this indicates that CSCOs often frame AI as primarily a tool for cost savings and enhanced efficiency, rather than a powerful engine for innovation, transformational change and novel business approaches.

This is further evidenced by the metrics leaders use to evaluate the success of their AI deployments.

The emphasis is heavily weighted toward those areas where immediate financial quantification is easily achievable, possibly overlooking the less immediately measurable but ultimately more important advantages gained from innovation and strategic reinvention.

Strategies for balancing AIinvestment

To fully harness the transformative power of AI, it's imperative that supply chain leaders diversify their approaches to investment.

By overlooking higher-risk endeavors with lengthier payback times, companies frequently fail to fully develop their abilities.

Gartner advises CSCOs to cultivate an AI investment portfolio that balances immediate and future goals.

This balanced strategy ensures that investments not only deliver rapid value, but also support long-term transformational initiatives that will shape the company's future. Key strategies for CSCOs to consider include:

1. Develop a formal supply chain AI strategy 

Develop a clear, documented AI strategy outlining short- and long-term objectives.

This documentation should include defining what success looks like and detailing the steps necessary to achieve it, along with associated timelines.

2. Adopt the Run-Grow-Transform framework

Construct an AI investment portfolio that incorporates "run," "grow," and "transform" projects.

This method allows for strategic allocation of resources, delivering not only immediate operational efficiencies but also mid- to long-term strategic advantages.

These phases would contain:

• Run: Focus on enhancing operational efficiency and cost optimisation through AI- automation and predictive maintenance
• Grow: Foster cross-functional alignment and enhance decision-making capabilities by integrating AI into key processes, such as sales and operations planning
• Transform: Prioritise AI projects that position the supply chain as a strategic partner in business growth, leveraging AI for insights and proactive demand shaping

3. Invest in AI-Ready infrastructure

Collaborate with the CIO and other executive leaders to ensure that the infrastructure supporting AI initiatives is scalable and adaptable to evolving business demands.

This is about guaranteeing your systems can keep pace with future requirements.

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