Many moons ago as a young engineering student I was enthralled by a lecture from my Operations Research (OR) professor. He introduced the topic of the Traveling Salesman problem (TSP) that day. He said the Traveling Salesman problem was “NP-hard,” Translation: impossible to solve at scale with classical computing. And it was also the first time I heard the word Heuristics and how it applied as a near optimal method to best solve the TSP. I’d call this my first lessons in SCM optimization and AI.
Supply chain Disruptions come in many avatars today and the world has suffered and healed from quite a few of them. AI and its agents are already at work solving critical SCM problems. But can the recent advances do one better and take on the deluge of disruptions too?
Disruptions – Everything everywhere all at once
Even before we arrive at how AI could spot and fix the disruptions let’s consider a few parameters that are well beyond established patterns that algorithms seek and solve-
Optimization isn’t just about routing ships anymore, it’s about resilience in a world that seems to thrive on chaos and uncertainty
Where AI shines today
Today AI is the SCM SME and Co-Pilot rolled into one tackling things such as
- Predictive analytics crunch signals from weather satellites, news feeds, and IoT sensors to forecast disruptions.
- Digital twins run “what-if” scenarios, like SimCity, but for containers and trucks.
- Dynamic routing recalibrates logistics when canals clog or ports shut down.
This isn’t theoretical. Companies are already using AI to spot risks earlier and recover faster.
And that’s not all, There are terms like “Friend-Shoring” where AI can help transition by identifying and vetting new suppliers in politically stable regions, analyzing their performance, and ensuring compliance with a new patchwork of regulations
Despite these advances it is clear that Supply Chain challenges are not easily solved by AI and its minions of bots and agents.
Where we’re going, we don’t need roads: SCM with AGI and quantum computing
And hence my bold foray into a not-so-distant future where I believe we are anyway heading – AGI!!!! And to this mix I want to add quantum computing!!
So, let’s hop into my SCM DeLorean time machine (yep, couldn’t resist the Back to the Future nod) and tackle optimization challenges in supply chain management, no matter the size, complexity, or curveballs thrown our way. Buckle up!
Now let’s fire up the DeLorean.
Quantum: the math buster
Remember the Traveling Salesman Problem? Quantum computing could finally crack those NP-hard optimization puzzles at scale. Routing thousands of ships, planes, and trucks across millions of constraints. Quantum could handle it in seconds – perhaps.
AGI: the autonomous strategist
Now add Artificial General Intelligence (AGI). Unlike today’s narrow AI, AGI wouldn’t just suggest, it would act.
- Autonomously reroute thousands of shipments.
- Negotiate new supplier contracts mid-crisis.
- Adjust global production schedules on the fly.
- Spot subtle interdependencies across politics, climate, and consumer behavior.
An AGI-powered supply chain wouldn’t just respond to disruption. It would avoid becoming a self-healing organism
Imagine this:
A political crisis erupts in one region. An AGI instantly sees its ripple effects on raw materials, reroutes shipments globally, finds alternative suppliers, and rebalances inventory, all before you take that first sip of that your Americano in the morning
Meanwhile, a quantum system solves the TSP across millions of nodes, continuously keeping logistics optimized. The supply chain doesn’t just survive disruption, it flows around it like water.
Why Kannan still matters!
Now, a confession. I didn’t write this blog alone. AI tools helped. They fed me structure, lists, and angles. But without my memories of that Bangalore lecture, my not so funny Back-to-the-Future jokes, my own perspective on AI + SCM , this would just be another AI-generated post and YOU would have spotted it
And that’s the catch. Until AGI truly takes over, if it ever does, human-in-the-loop remains vital.
- Humans set the priorities: efficiency vs. resilience, cost vs. ethics.
- Humans ask the “why,” not just the “how.”
- Humans bring creativity, judgment, and yes, humor to the mix.
AI can predict, optimize, and even execute. But it can’t (yet) tell us what kind of supply chain future we want.
Drive that DeLorean back to 2025
Okay, so quantum-AGI-DeLoreans sound fun (and they are), but what about the real world of today? You don’t need a time machine to start making supply chains smarter right now. Here’s the pragmatic playbook if you have already got AI managing SCM for you:
And to bring it all back to where we started – The Traveling Salesman – I hope he will return home someday soon using the shortest cost-effective path that AI can choose for him.
“Here he lies where he longed to be;
Home is the sailor, home from sea,
And the hunter home from the hill”
-Robert Louis Stevenson
