Gartner Predicts AI Agents Could Take Over Half of According to Ga Tasks by 2030

According to Gartner, AI could be running half of all supply chain software by the end of this decade. At the Gartner Supply Chain Symposium in Barcelona this week, experts said AI is quickly moving from just helping people make decisions to actually making decisions on its own.

One big idea from the event was something Gartner calls “agentic AI.” This means using smart AI assistants that can do supply chain work without needing someone to watch over them all the time. These AI helpers could order supplies, manage inventory, respond to changes in demand, and even come up with new ways for companies to do business.

Kaitlynn Sommers, a senior analyst at Gartner, said companies today need supply chain tech that saves time or helps them make more money, especially with how uncertain things are. Agentic AI can do both, it can make things more efficient, take over complex tasks, and even create new business opportunities.

The first version of agentic AI includes simple digital assistants, like an AI buyer that automatically places orders based on stock levels, demand forecasts, and market prices. Over time, these AI tools will get smarter, take on more complicated tasks, and make more decisions on their own to meet the company’s needs.

Sommers said this is different from old systems that just followed fixed instructions. Agentic AI works on its own, learns from real-time data, and adjusts to whatever’s happening in the business. It doesn’t need someone to tell it exactly what to do every time.

To help companies get started, Gartner gave three tips for supply chain leaders:

1. Start small – Pick a simple task where AI can help, use clean data, and make sure it brings a good return on investment.
2. Include AI in your team – Treat AI like a team member and give it a specific role. You might need to change how your team works to fit AI in.
3. Set clear rules – Make sure the AI knows what it can and can’t do, so it doesn’t make any costly mistakes.

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