If Ian Fleming were alive and writing today, James Bond would likely be “Agentic AI 007,” a fully autonomous software intelligence officer powered by a British Large Language Model (LLM).
Or Bond might be a supply chain software agent, considering all the rage with Agentic AI in the industry today.
For example, at Momentum 2025 last week, Manhattan Associates “announced sweeping Agentic AI support within Manhattan Active solutions that includes intelligent, autonomous digital agents to revolutionize supply chain commerce execution, optimization, and user experiences.” Here are more details from the press release:
These out-of-the-box AI agents, powered by large language models (LLMs) and Manhattan’s cloud-native, all-microservice API architecture, will autonomously perform tasks, adapt to changing conditions, and dynamically orchestrate workflows. This breakthrough marks a generational leap from traditional chatbots and static workflow configurations to dynamic, intelligent, and situationally aware orchestration across the entire supply chain and commerce lifecycle.
Among the first groundbreaking AI agents announced are the Intelligent Store Manager, Labor Optimizer Agent, Wave Inventory Research Agent, Contextual Data Assistant, and Virtual Configuration Consultant. These digital agents allow users to interact with Manhattan applications using natural language, understand complex requests, bypass traditional interfaces to surface data, drive optimization, and efficiently resolve disruptions in real time across critical supply chain commerce operations.
Manhattan Associates also launched Manhattan Agent Foundry, a platform which will allow companies to “rapidly build and deploy their own agents within the Manhattan ecosystem. Customers can now create specialized agents tailored to their unique processes and preferences, drastically reducing time-to-value, increasing automation scalability, enhancing productivity, and delivering tangible business value.”
In other words, you can be like Ian Flemming and create your own special agent.
Also last week, Uber Freight announced “the launch of the industry’s first scaled AI logistics network, powered by its proprietary logistics-specific large language model (LLM) and embedded directly into its transportation management system (TMS) and logistics platform.” Here are more details from the press release:
Uber Freight’s logistics platform’s latest advancements bring to market more than 30 AI agents automating execution across the shipment lifecycle, while Insights AI delivers always-on recommendations to help shippers using the TMS to proactively navigate disruption, reduce cost, and improve service across their networks.
Over the past year, more than $1.6 billion in freight has moved through Uber Freight’s AI logistics infrastructure, with five enterprise brands leveraging early access to test and validate the technology. Trained on real logistics data from nearly $20 billion in freight under management––including 30% of the Fortune 500––Uber Freight’s LLM unlocks deep operational context and delivers not just answers, but actionable recommendations grounded in real-world complexity.
While Insights AI equips shippers with proactive intelligence, Uber Freight’s 30+ AI agents automate critical tasks across the end-to-end shipment lifecycle. These agents now manage procurement, execution, tracking, payments, and analytics––freeing logistics teams to focus on strategic priorities such as exception management, cost control, and network optimization.
“With the scale and complexity of our operations, the collaboration with Uber Freight on Insights AI has helped empower our team to access timely information, analyze our network, and make strategic decisions that drive faster growth,” says Tatiana Martinez, Vice President, North America Customer Service & Logistics, North America, Colgate-Palmolive in the press release. “Insights AI has helped us plan with greater confidence and respond more effectively to disruptions, all in service of our ongoing commitment to customer centricity and operational efficiency.”
Remember the “crawl, walk, run” approach to technology implementation? It seems like in the past 18 months, when it comes to AI agents, we’ve leaped over the crawl and walk phases and have gone straight to a running sprint.
In reality, however, the majority of companies — especially small and mid-sized ones — are still unfamiliar with or skeptical about AI. As has happened many times before with other technologies, AI is miles ahead of where most companies are today in their readiness to use it.
(Stay tuned for some research we recently completed on AI in logistics).
That said, I see AI agents as the more advanced version of Robotic Process Automation (RPA), which companies have been using (knowingly or unknowingly) for a long time already. Eventually, the noise and hype surrounding Agentic AI will die down, the market will become better educated about what it is and isn’t, and more companies like Colgate-Palmolive will share their success stories. And when that happens, Agentic AI will just be software again.
The open question is where do we draw the line with these AI agents? How much of the work done by supply chain professionals today do we hand over to these agents (who are given human names like Tracy, Sam, and Adam by vendors) that can supposedly “analyze situations, develop strategies, and execute tasks independently?” Will there be anything left for us humans to do other than sit, watch, and eat processed foods all day?
