Why did Manhattan Associates' stock price rise 5.92% despite being down 12% over the past year?

The stock jump was driven by significantly raised 2026 guidance (EPS $5.29–$5.37 vs. prior $5.04–$5.20, and revenue $1.147–$1.157B vs. $1.133–$1.153B). Strong Q1 results ($282.2M revenue, 24.2% cloud growth) and a $2.35B backlog (+24% YoY) demonstrated that go-to-market investments are paying off, reversing investor concerns about the company's competitive position. However, the stock remains down from 52-week highs ($247) and December 2024 peaks ($300+), reflecting broader market skepticism about software valuations.

What is driving Manhattan's market share gains against competitors?

Manhattan is winning through three levers: (1) aggressive cloud migration, with cloud revenue up 24.2% YoY and 55% of new bookings from new logos; (2) a unified platform strategy that competitors haven't matched, enabling win rates above 70%; and (3) agentic AI pilots showing rapid ROI. CEO Clark noted that some competitors have not invested adequately in cloud or unified platforms, allowing Manhattan to displace incumbents at scale.

How significant is agentic AI expected to be for Manhattan in 2026 and beyond?

Management guidance is conservative for 2026 but expects 'meaningful' financial impact in 2027. Early adopters are already justifying ROI through overtime reduction alone. Customers have moved quickly from pilot to subscription models, suggesting strong product-market fit. This emerging revenue stream could be a material upside driver if adoption accelerates.

What does a $2.35B remaining performance obligation (RPO) backlog mean for supply chain planners?

RPO represents contracted revenue not yet booked, indicating strong forward demand visibility and customer commitment. The 24% YoY increase signals that enterprise customers are doubling down on cloud and AI investments, creating a reliable multi-quarter revenue pipeline. This backlog is a leading indicator of sustained demand for supply chain software and services.

Should my organization consider migrating from on-premise WMS/OMS to Manhattan's cloud platform?

The strong momentum in cloud adoption, agentic AI capabilities, and win rates above 70% suggest that staying on-premise systems carries rising competitive risk. Early adopters report tangible ROI through labor optimization and visibility. However, migration decisions depend on current system health, budget, and organizational readiness. The 2026–2027 window may be optimal, as AI tools mature and the market leader consolidates further.

Technology & Innovation

Moderate

Manhattan Associates Raises 2026 Forecast on Cloud Momentum and AI

Apr 24, 2026

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The signal

Manhattan Associates, a major supply chain software provider, released stronger-than-expected first quarter results and significantly raised its 2026 financial guidance, signaling a turnaround in business momentum. 153 billion). This revision matters because Manhattan is capturing meaningful market share through cloud-first positioning and emerging agentic AI capabilities, which supply chain teams are deploying to reduce overtime and unlock ROI rapidly. 35 billion—up 24% YoY.

Critically, 55% of new cloud revenue is coming from new customers (new logos), indicating Manhattan is winning share against competitors in on-premise or legacy systems. CEO Erick Clark highlighted a consistent win rate above 70% and strong bookings across all regions and deal sizes, driven by strategic go-to-market investments throughout 2025. The shift toward cloud is compounded by agentic AI pilot adoption; early customers report ROI justification through overtime reduction alone, positioning Manhattan for a material uplift in 2027 as AI agents move from proof-of-concept to production across the customer base. For supply chain professionals, this signals accelerating industry consolidation around unified cloud platforms with embedded AI capabilities.

Organizations still running on-premise WMS, OMS, or legacy ERP systems face strategic pressure to migrate or risk competitive disadvantage on automation, real-time visibility, and labor cost management. The strong demand backdrop—new logos, high win rates, and committed bookings—suggests enterprise appetite for these solutions is resilient despite macro uncertainty, offering clarity on technology investment priorities for 2026.

#manhattan-associates

#supply-chain-software

#warehouse-automation

#logistics-tech

#earnings-report

#digital-transformation

Frequently Asked Questions

What This Means for Your Supply Chain

Simulation Suggestion

strategic

What if 40% of your WMS/OMS customer base migrates to cloud-native platforms by 2027?

Simulate the impact of accelerated cloud migration on your supply chain technology spend, workforce retraining needs, and visibility timelines. Assume 60% of your current on-premise systems are replaced with cloud platforms (like Manhattan) over 18 months, reducing IT maintenance overhead but requiring new data integration and change management costs.

Run this scenario

Simulation Suggestion

strategic

What if your supply chain visibility improves by 48 hours due to real-time cloud-based order and warehouse management?

Simulate the operational and service-level gains from migrating to a unified cloud platform with embedded AI. Assume end-to-end visibility improves by 2 days due to real-time data integration across OMS, WMS, and TMS, enabling faster exception resolution, reduced dwell times, and improved on-time delivery rates.

Run this scenario

Simulation Suggestion

this month

What if agentic AI reduces your overtime labor costs by 15-20% starting in Q2 2027?

Model the impact of AI-driven warehouse automation on labor scheduling, overtime spend, and capacity utilization. Assume agentic AI (similar to Manhattan's pilot programs) begins production deployment in your facilities in mid-2027, driving 15-20% reduction in overtime through optimized task allocation, predictive scheduling, and exception handling.

Run this scenario

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Supply Chain Intelligence: The 2026 Buyer's Guide

The four-layer stack (twin, simulation, sandbox, intelligence) and the framework for evaluating platforms.

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