Manhattan Associates: Assessing the AI Agent Infrastructure Play

Manhattan Associates is making a clear pivot. It is no longer just selling supply chain software. The company is embedding AI agents directly into its core platform, positioning them as the foundational infrastructure for next-generation operations. This move is a strategic bet on becoming the operating system for agentic supply chain commerce.

The company announced the commercial availability of its AI Agents last month, integrating them directly into all Manhattan Active® solutions. Unlike add-on tools that sit on top of legacy systems, these agents live within the platform, giving them real-time operational context to take action. The initial rollout includes purpose-built agents for store associates, contact centers, and shipment tracking, designed to guide decisions and automate tasks. This deep integration is critical. It means the AI isn't an external layer but the new default mode of interaction, fundamentally changing how users work.

This strategic shift is built on a strong underlying platform. In its third quarter, the company's 21% cloud revenue growth provided the financial and technological foundation for this AI monetization play. That robust cloud base ensures the company has the scalable infrastructure and customer access needed to deploy and bill for these new intelligent services.

The timing of this bet is also telling. Industry surveys show most organizations are still in the early stages of scaling AI. While nearly all companies are using AI, two-thirds have not yet begun scaling it across the enterprise. This creates a large, untapped market. Manhattan is positioning itself to capture a significant share of the early, high-value adoption curve by offering a platform where AI agents are not just tools, but the core workflow.

The bottom line is that Manhattan is attempting to build the infrastructure layer for a new paradigm. Success hinges on whether its embedded, operational AI can move beyond experimentation and become the essential rails for supply chain execution.

The Infrastructure Layer: Why Platform Embedding is Critical for Exponential Adoption

The path to exponential adoption in any new technology paradigm is paved by infrastructure. For agentic AI in supply chains, the critical question is where the intelligence lives. Manhattan Associates' strategy of embedding agents directly within its platform is a superior infrastructure layer for achieving that scale, as opposed to overlay solutions that sit on top of legacy systems.

The market opportunity is massive and accelerating. The global AI-powered supply chain planning market is expected to grow at a 38.8% CAGR to $41.23 billion by 2030. Capturing a share of this exponential curve requires a platform that can move beyond pilot projects and into core operations. Overlay solutions, which often rely on data lakes and siloed systems, struggle to achieve this. They face significant integration hurdles and lack the real-time operational context needed for autonomous action. As one industry analysis notes, true competitive advantage can only be achieved when supply chains integrate and engage AI as a transformative agent, not as a sidecar tool.

Manhattan's embedded approach directly addresses this friction. Its agents live within the Manhattan Active® Platform, giving them full visibility into live operations. This allows them to take real-time action, like the Shipment Tracking agent that identifies issues and recommends fixes, or the Labor Agent that guides workforce deployment. This deep integration is the difference between an AI that observes and one that acts. It provides the necessary operational context for agents to function responsibly and transparently, a key requirement for enterprise adoption.

More importantly, this architecture is primed for workflow redesign-the key success factor for capturing enterprise value. The McKinsey survey found that half of those AI high performers intend to use AI to transform their businesses, and most are redesigning workflows. When agents are built into the core operating system, they become the default mode of execution. This makes it far more likely that users will fundamentally change how they work, moving from process automation to operational intelligence. The platform doesn't just add a new tool; it redefines the workflow.

The bottom line is that Manhattan is building the rails for the next paradigm. By embedding AI agents as the foundational layer, it is creating an infrastructure that is not only technically superior but also more conducive to the radical workflow changes needed to unlock exponential value. The company is betting that the path to scale runs through the platform, not around it.

Financial Metrics and Valuation: Growth vs. Premium Pricing

The market is sending a clear signal about Manhattan Associates. The stock has declined 21% over the last 120 days, trading near $173. This skepticism reflects a classic tension: the company is betting on a future exponential growth curve driven by AI agents, but the current financials and valuation suggest the market is waiting for proof of that paradigm shift.

On paper, the valuation is a premium one. Manhattan trades at an enterprise value multiple of 36x EV/EBITDA. That's a high multiple, justified only if the AI infrastructure play delivers a clear acceleration in both growth and profitability. The company's recent financial health, however, shows a business in transition. Its rolling annual return is down 34%, and the stock is trading well below its 52-week high. This sets up a binary outcome: the premium valuation will be validated if AI agents drive rapid adoption and enterprise-wide impact, or it will be punished if the rollout stalls in the pilot phase.

The key uncertainty is the path from use-case benefits to enterprise-level EBIT impact. Industry surveys show a stark gap. While nearly all companies are using AI, two-thirds have not yet begun scaling it across the enterprise. More critically, only 39% report EBIT impact at the enterprise level. This is the critical inflection point for Manhattan's strategy. Its embedded agents are designed to bridge this gap by becoming the default workflow layer, but the market is rightly asking if this architecture will be enough to move the needle for most customers. The company's success hinges on converting its platform's operational context into measurable, bottom-line value that spreads beyond isolated functions.

The bottom line is that Manhattan's valuation is a bet on execution. The stock's decline signals that the market is pricing in risk, not just growth. For the premium to hold, the company must demonstrate that its AI agents are not just tools for experimentation but the essential infrastructure that unlocks the exponential value the market expects. Until then, the financials and the stock price will remain in a holding pattern, waiting for the adoption curve to steepen.

Catalysts, Risks, and the Adoption Curve

The investment case for Manhattan Associates now hinges on a clear set of near-term milestones. The primary catalyst is the commercial adoption rate of its new AI agents. Success will be validated not by the number of pilots, but by evidence that these agents are being integrated into core customer workflows and driving measurable productivity gains. The company has already announced the commercial availability of three initial agents for store associates and contact centers within the Manhattan Active Omni user interface. The next phase is to see these tools move from being "digital assistants" to becoming the default layer for operational decisions.

A major risk is that the AI agents remain siloed tools rather than becoming the core decision layer, failing to achieve the promised "operational intelligence" vision. Industry surveys show a stark gap: while nearly all companies are using AI, two-thirds have not yet begun scaling it across the enterprise. The company's embedded architecture is designed to overcome this, but the market is rightly skeptical. The real test will be whether Manhattan's platform is used to fundamentally redesign workflows-a key success factor for capturing enterprise value. The McKinsey survey found that half of those AI high performers intend to use AI to transform their businesses, and most are redesigning workflows. If Manhattan's agents are only used for incremental task automation, they will struggle to justify the premium valuation.

Watch for evidence that the company's platform is being used to redesign workflows, a key success factor for capturing enterprise value. The initial rollout focuses on specific roles like store associates and contact centers, which is a logical start. The critical next step is to see these agents expand into broader operational planning and execution, moving from guiding individual tasks to shaping entire processes. This is where the "autonomous" agents, which continuously monitor operations and automatically remedy issues, must demonstrate their value. Their ability to function as "digital co-planners" that work reliably and consistently will determine if they become essential infrastructure or remain niche add-ons.

The bottom line is that Manhattan is on a binary path. The catalysts are clear: deeper workflow integration, measurable productivity gains, and expansion into planning functions. The risks are equally defined: agents getting stuck in the pilot phase, failing to achieve enterprise-wide EBIT impact, and being perceived as just another tool rather than the new operating system. The coming quarters will show whether the company's embedded AI architecture can bridge the gap between experimentation and exponential adoption.