Agentic AI in supply chain planning: Prepare now to unlock competitive advantage

Planning leaders face mounting pressure to deliver timely, informed decisions to ensure the supply chain is supporting business objectives in a reliable and cost-effective way. While many organizations have started investing in artificial intelligence (AI) to drive competitive advantage, the emergence of Agentic AI marks a pivotal shift, one that has the potential to redefine the boundaries of autonomous planning and execution.

Gartner predicts that 50% of cross-functional supply chain management (SCM) solutions will use intelligent agents to autonomously execute decisions in the ecosystem by 2030. For organizations prepared to harness its potential, Agentic AI offers not just the promise of incremental improvements, but a strategic lever for sustainable competitive advantage. This is accomplished by moving beyond the automation of routine tasks, enabling autonomous agents to execute complex, goal-driven planning activities.

For example, AI agents can orchestrate multi-step processes, such as demand-supply balancing or scenario planning, while learning and adapting in real time. The result is a step-change in planning velocity and agility: organizations can respond to market shifts, supply disruptions, and demand fluctuations with unprecedented speed and precision.

However, it’s early days for the technology, which Gartner expects is five to 10 years from mainstream adoption in supply chain. Most advanced cases of agentic planning systems today are limited to orchestrating predefined subagents within structured processes. This reduces its potential to independently make decisions, take actions and refine its strategies.

As the technology continues to mature in the coming years, supply chain planners should begin to take steps now to explore use cases for the technology, with an emphasis on preparing the organization to achieve maximum benefit.

Building a foundation: Seamless integration for Agentic AI

While the promise of agentic AI in supply chain planning is compelling, its value will only be realized when it can interact dynamically with the broader supply chain technology landscape, including legacy systems, composable planning platforms, advanced analytics tools, and digital twins.

A modular, composable approach will be essential. Rather than rip-and-replace, organizations will want to look for opportunities to “plug in” agent-based capabilities where they can deliver the most impact. For example, elevating demand sensing into a real-time demand agent that autonomously integrates with an inventory policy agent as well as a scenario testing agent will allow for much higher inventory turns than ever before, while continuously mitigating risk and capturing revenue growth opportunities.

Consideration will also need to be given to developing robust governance frameworks to ensure Agentic AI actions align with business objectives and risk tolerances. This means establishing clear guardrails, such as approval workflows, exception management protocols, and audit trails, to balance innovation with operational control. Cross-functional collaboration between IT, supply chain, and risk management teams will be vital to define these boundaries and to ensure Agentic AI operates within a framework that supports both agility and accountability.

Measuring success at this stage will go beyond system uptime or deployment metrics. Leaders should plan to track reductions in manual interventions, improvements in planning cycle times, and the percentage of planning decisions executed autonomously. These KPIs provide tangible evidence that Agentic AI is not just present, but actively driving value.

Fostering an AI native planning culture

The second, and often more challenging, priority will be fostering the organizational and cultural shifts required to fully capitalize on Agentic AI. Agentic AI offers a possible solution for SCP leaders struggling with finding and keeping talent in their organization, but implementing this technology will require diligent planning to ensure successful adoption.

As autonomous agents take on standardized, repeatable tasks, the role of human planners will evolve. Their focus will shift from transactional work to strategic analysis and cross-functional collaboration. Upskilling will be essential, and not just in technical skills, but in analytical thinking, scenario evaluation, and the ability to interpret and act on AI-driven recommendations.

To encourage adoption, leaders must foster an AI-native culture that values data-driven decision-making and is open to new modes of collaboration between humans and AI agents. A common barrier is the “black box” effect, where stakeholders may be wary of delegating decisions to AI without understanding how those decisions are made.

Addressing this challenge requires investment in explainable AI capabilities and transparency initiatives. Regular communication, training, and stakeholder engagement are also critical to building trust and helping drive adoption. However, success here should not solely be measured by adoption rates, but by the organization’s ability to respond faster, make better decisions, and achieve improved business outcomes.

Unlocking the full promise of Agentic AI

Agentic AI is poised to become a cornerstone of next-generation supply chain planning, offering organizations the ability to outpace competitors through speed, agility, and intelligent autonomy. Unlocking its full potential though will require more than investment in technology. Supply chain planning leaders who act decisively and develop a strong organizational muscle for transformative change will be best positioned to capture the sustainable competitive advantage that agentic AI promises.

Join Gartner experts and supply chain planning leaders at the Gartner Supply Chain Planning Summit in London, U.K. on November 3-4 and in Denver, CO on December 2-3 to learn more about this topic and other trends in supply chain planning.

About the author

Jan Snoeckx is a director, analyst for supply chain strategy and planning at Gartner.

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