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Retail’s dirty little secret? Most of our systems don\u2019t talk to each other.<\/p>\n
For years, we\u2019ve bolted on new tech in hopes it would create clarity. Instead, we ended up with disconnected software\u2014each tool with its own data, interface, and logic. The warehouse couldn\u2019t see labor needs. POS had no idea what was stuck in the receiving area. Scheduling was a guessing game.<\/p>\n
Want to know retail’s dirty little secret? Most of our systems don\u2019t talk to each other.<\/p>\n
For years, we\u2019ve bolted on new tech in hopes that it would create clarity. Instead, we ended up with disconnected software\u2014each tool with its own data, interface, and logic. The warehouse couldn\u2019t see labor needs. POS had no idea what was stuck in receiving. Scheduling was a guessing game.<\/p>\n
At Manhattan Associates\u2019<\/span> annual conference, Momentum 2025<\/span>, Sanjeev Siotia, CTO of Manhattan Associates, put it simply, \u201cYou\u2019ve got amazing software. But they\u2019ve each been built like highly intelligent people sitting in separate rooms with the door closed.\u201d<\/p>\n That\u2019s the real pain point AI must solve\u2014not just automation, but integration.<\/p>\n Retail has evolved from simply stocking shelves to orchestrating vast ecosystems\u2014from vendors to delivery docks to customer doorsteps. And today\u2019s consumer expects real-time answers and frictionless service at every step.<\/p>\n The problem? Legacy systems weren’t designed to handle this level of real-time complexity. And worse, each department runs its own tech stack, unable to collaborate beyond CSV exports or Slack messages.<\/p>\n \u201cHuman-computer interactions have come a long way,\u201d Sanjeev said, \u201cbut they\u2019ve remained largely transactional. What we need now are systems that can reason with us, act with us, and grow with us.\u201d<\/p>\n In a fragmented world, solving one customer issue would require four disconnected tools:<\/p>\n Sanjeev explained that Manhattan sees it differently: rather than separate tasks handled by different systems or people, they treat it as a single, intelligent action. \u201cInstead of one system alerting the customer, another creating a shipping label, and another updating inventory,\u201d he said, \u201can agent can now handle it all automatically, reliably, while always looking for the next best way to help.\u201d<\/p>\n That shift\u2014from \u201cmany tools doing a single job\u201d to \u201cone agent designed to help\u201d\u2014is the breakthrough. It\u2019s not automation. It\u2019s coordination<\/em>.<\/p>\n \u201cAI isn\u2019t helpful if it lives in a bubble,\u201d Sanjeev warned. \u201cAn agent needs to think, see, and do\u2014all in the context of your entire operation.\u201d<\/p>\n He explained this as the three required proficiencies of AI agents:<\/p>\n This holistic capability isn\u2019t available from bolt-ons. It\u2019s only possible when your AI lives inside your platform, not bolted onto it.<\/p>\n Manhattan didn\u2019t just add AI to their platform\u2014they rearchitected their platform to become truly agentic.<\/p>\n These agents don\u2019t just suggest\u2014they act. They don\u2019t wait for a human to interpret a dashboard\u2014they execute in real time. And more importantly, they work seamlessly together.<\/p>\n Sanjeev showed a live demo featuring Agent Joe, a labor optimization agent that could dynamically reassign employees based on shifting work volumes:<\/p>\n He asked the computer, \u201cCan you tell me if any departments are running behind?\u201d It then took stock of who was on the schedule, and then automatically sent them a note when they were finished to go help with packing.<\/p>\n That wasn\u2019t science fiction. That\u2019s production-ready software that many Manhattan clients are already using. Natural language. No prompt necessary, just the goal of what you want to know.<\/p>\n Manhattan\u2019s customers will get access to Agent Foundry, the same environment Manhattan uses to build its AI agents.<\/p>\n \u201cIf you know your business, you can build an agent,\u201d he said. \u201cAnd if you don\u2019t know how? We can build agents for you.\u201d<\/p>\n That democratization of AI is critical. It means innovation isn\u2019t bottlenecked by developers or Manhattan\u2019s roadmap. If your floor team wants a packing assistant who knows their workflow, they can build it.<\/p>\n One load planning team used this to cut a 3-hour daily task down to minutes by defining simple rules in natural language.<\/p>\n \u201cThat\u2019s the power of platform-native intelligence,\u201d Sanjeev said. \u201cAgents inherit the entire ecosystem they\u2019re built in. They\u2019re born integrated.\u201d<\/p>\n Sanjeev also revealed consulting agents that can read a business requirements document and configure the system accordingly.<\/p>\n \u201cWe want our systems to understand your business like a consultant,\u201d he said. \u201cEventually, you\u2019ll just describe what you want\u2014and it\u2019ll build itself.\u201d<\/p>\n That\u2019s not a fantasy. It\u2019s a roadmap that\u2019s already in progress.<\/p>\n Unified AI doesn\u2019t just help your teams behind the scenes- it enhances the shopper\u2019s experience at the point of sale, too.<\/p>\n Manhattan showcased a new customer-facing display that syncs directly with the POS. As shoppers check out, they can see their:<\/p>\n That visibility creates confidence. No guesswork. No surprises. No more squinting at receipts or guessing what promotion applied. It\u2019s trust, built in real time. When systems are unified, the customer\u2019s experience becomes unified too. Just a clear, trust-building interaction at a moment that too often feels rushed or opaque.<\/p>\n When systems are unified from warehouse to front-end checkout, you create harmony across the whole experience. And it\u2019s small details like this that reinforce a big transformation.<\/p>\n I\u2019ve been in retail for decades. I’ve seen every so-called breakthrough: barcode scanners, ERP rollouts, cloud POS. But most of them still relied on humans pulling the right levers.<\/p>\n This feels different. Unified AI agents don\u2019t just reduce effort\u2014they reduce friction. Between departments. Between platforms. Between decisions.<\/p>\n You don\u2019t need more dashboards.<\/p>\n You need intelligence that acts in real time.<\/p>\n You need agents that learn and operate as one.<\/p>\n And Manhattan is building the tools that finally make that possible.<\/p>\n Sanjeev put it best: \u201cWe\u2019re not here to replace your people. We\u2019re here to elevate them\u2014to give them tools that can think and act so they can focus on what matters most.\u201d<\/p>\n If you’re still using systems that can’t talk to each other, can’t learn, and can’t act without intervention, you\u2019re operating at a disadvantage.<\/p>\n Unified AI agents are here. They work together. And they\u2019re already being used to reduce cost, save time, and unlock agility at scale.<\/p>\n And the benefits aren\u2019t limited to back-end teams. Shoppers feel it too.<\/p>\n At Manhattan\u2019s Discovery Center, a customer-facing display showed shoppers their loyalty points, usable coupons, and their basket being rung up\u2014live, in real time.<\/p>\n Ask: What repetitive decisions are eating up our team\u2019s time?<\/p>\n Evaluate: Are your systems built to think, see, and do, or just display?<\/p>\n The days of \u201csee no data, hear no signals, speak no solutions\u201d are over.<\/p>\n It\u2019s time for your systems to start working together.<\/p>\n And with AI, they finally can.<\/p>\n<\/div>\nRetail Complexity Outpaced Retail Tools<\/span><\/strong><\/h2>\n
Fragmented AI Is Just Another Silo<\/span><\/strong><\/h2>\n
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Unified AI Agents Built into Manhattan Active<\/span><\/strong><\/h2>\n
The computer responded, \u201cYes, packing is one hour behind. You can reassign three pickers finishing early.\u201d<\/p>\nAgent Foundry: Retailers Get to Build Their Own Intelligence<\/span><\/strong><\/h2>\n
Consulting Agents: Removing Complexity<\/span><\/strong><\/h2>\n
Customer-Facing Displays: Transparency That Builds Trust<\/span><\/strong><\/h2>\n
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Why This Is a Turning Point for Retailers<\/span><\/strong><\/h2>\n
Here\u2019s the big idea:<\/span><\/strong><\/h2>\n
The Next Great Supply Chain Revolution Isn\u2019t Faster. It\u2019s Frictionless<\/span><\/strong><\/h2>\n
Your Next Steps<\/span><\/strong><\/h2>\n