Generative AI in Retail Demand Forecasting and Merchandising - Market Share Analysis, Industry Trends & Statistics, Growth Forecasts (2026-2031)

The generative AI in retail demand forecasting and merchandising market size was valued at USD 3.72 billion in 2025 and estimated to grow from USD 4.69 billion in 2026 to reach USD 16.41 billion by 2031, at a CAGR of 28.47% during the forecast period (2026-2031). This report is Segmented by Component (Software, and Services), Deployment Mode (Cloud, On-Premise, and Hybrid), Genai Capability (Conversational AI, and More), Application (Demand Forecasting, and More), End User (Specialty Retail, and More), Enterprise Size (Large Enterprises, and SMEs), and Geography. The Market Forecasts are Provided in Terms of Value (USD).

Global Generative AI In Retail Demand Forecasting and Merchandising Market Trends and Insights

Rapid Shift From Static Forecasting to Continuous Demand Sensing

Consumer demand can shift quickly in response to social media activity, weather events, and local competition. Retailers relying solely on historical sales patterns can struggle when their planning cycle moves more slowly than the pace of available demand signals. Amazon Science reported that its Anchored FLoE framework improved sales-weighted MAPE by 11 percentage points against production baselines across 524 product-market segments. The reported result linked better demand forecasts with a multi-million-dollar effect on free cash flow. AWS launched Connect Decisions in April 2026, making Amazon’s foundational forecasting capability available to third-party retailers. As this capability becomes easier to access, proprietary data and retailer-specific controls become more important than model architecture alone.

Rising Need for AI-Assisted Assortment and Merchandise Planning

Quarterly reviews, spreadsheets, and buyer judgment are becoming less sufficient for fast-moving assortment decisions. AI-assisted planning can process product attributes, demand signals, and competitive pricing more frequently than traditional planning routines. Invent.ai reported in April 2025 that every surveyed retailer planned to investigate or invest in AI-enabled merchandise planning within 12 months. The generative AI in retail demand forecasting and merchandising market benefits when retailers use these tools to connect assortment choices with replenishment and promotion decisions. These systems can reduce the time spent compiling inputs, leaving planners more time for supplier discussions and product selection. They also shift decision-making responsibility to AI-supported category teams, which requires organizational changes that technology budgets may not fully cover.

Hallucination Risk in Forecast Narratives and Planning Recommendations

A planning model can produce a plausible explanation or recommendation that does not match the underlying retail data. This risk is particularly serious when users accept markdown guidance or demand explanations without review. Research published in 2026 described hallucinations as an operational, financial, legal, and strategic enterprise risk. Fragmented product data can exacerbate the problem, as models have fewer reliable attributes for long-tail stock-keeping units. Retailers can reduce this exposure through structured retrieval, business controls, audit processes, and human review. The European Union’s AI Act also creates governance requirements that make transparent controls more relevant for retailers using generative AI.

Other drivers and restraints analyzed in the detailed report include:

• Omnichannel Complexity Requiring Unified Inventory and Pricing Decisions
• Growing Demand for Natural-Language Planning Interfaces and Retail Planning Copilots
• Limited High-Quality Retail Data and Data Fragmentation Across Channels

Segment Analysis

Software held 72.18% of the generative AI in retail demand forecasting and merchandising market size in 2025. Demand planning engines, merchandise planning suites, and retail-focused GenAI applications make up the core of this software spending, including tools used for forecast narratives and planning simulations. SAP, Blue Yonder, and Oracle have established positions through planning platforms already used by enterprise retailers across finance, supply chain, and merchandising functions. RELEX, SymphonyAI, and o9 offer retail-focused applications that can shorten the time needed to introduce specialized planning capabilities and connect them with existing retail processes. The software segment benefits when retailers seek a shared foundation for forecasting, replenishment, assortment, promotional decisions, and regular review of operating results.

Services are projected to expand at a 29.28% CAGR from 2026 to 2031. Retailers use services for enterprise resource planning integration, data preparation, model tuning, change management, and the mapping of local retail processes into new planning workflows. These engagements can help create retailer-specific data assets and planning rules that remain valuable after deployment rather than treating implementation as a one-time technical project. The generative AI in retail demand forecasting and merchandising market is therefore separating into customized enterprise programs and simpler subscription tools for smaller retailers. Vendors need different delivery models because each group has different data resources, budgets, internal technical capacity, and appetite for extended implementation support.

Cloud deployment held 76.94% of revenue in 2025. Cloud platforms offer flexible computing capacity for retailers that manage many locations, large stock-keeping unit portfolios, and fluctuating workloads across planning cycles. Microsoft Azure, AWS, and Google Cloud have added AI capabilities to retail cloud services, increasing the number of ways that retailers can build or obtain forecasting support. AWS reported in 2025 that 80% of surveyed retailers planned to increase funding for AI and generative AI. The generative AI in retail demand forecasting and merchandising market uses cloud delivery to make forecasting, scenario work, and data services easier to scale across stores, channels, and teams.

Hybrid deployment is projected to expand at a 29.83% CAGR from 2026 to 2031. This approach lets retailers use cloud resources for training and simulations while retaining selected workloads in their own environment, closer to operational systems. It is relevant for grocers, pharmacies, and specialty retailers that handle sensitive customer or pricing information across multiple business units. Hybrid models can also support latency-sensitive processes that require real-time decisions, with local processing and uninterrupted access to essential retail data. The generative AI in retail demand forecasting and merchandising market is likely to retain hybrid demand where data residency and governance requirements shape technology selection.

Complete Report Scope:

• By Component
  • Software
  • Services
• By Deployment Mode
  • Cloud
  • On-Premise
  • Hybrid
• By GenAI Capability
  • Conversational AI and Natural-Language Interfaces
  • Insight and Recommendation Generation
  • Scenario Generation and Simulation
  • Synthetic Data Generation
  • Other GenAI Capabilities
• By Application
  • Demand Forecasting
  • Assortment Planning
  • Merchandise Planning
  • Inventory Optimization
  • Visual Merchandising
  • Other Applications
• By End User
  • Grocery and Hypermarkets
  • Specialty Retail
  • Fashion and Apparel
  • Consumer Electronics
  • Home and Furniture
  • Online Retailers
  • Other End Users
• By Enterprise Size
  • Large Enterprises
  • Small and Medium Enterprises
• By Geography
  • North America
    • United States
    • Canada
    • Mexico
  • South America
    • Brazil
    • Argentina
    • Rest of South America
  • Europe
    • Germany
    • United Kingdom
    • France
    • Italy
    • Spain
    • Russia
    • Rest of Europe
  • Asia-Pacific
    • China
    • Japan
    • India
    • South Korea
    • Australia
    • Rest of Asia-Pacific
  • Middle East
    • Saudi Arabia
    • United Arab Emirates
    • Turkey
    • Rest of Middle East
  • Africa
    • South Africa
    • Egypt
    • Rest of Africa

Geography Analysis

North America held 39.48% of the generative AI in retail demand forecasting and merchandising market size in 2025. The region combines high enterprise technology budgets with established cloud services and specialist planning vendors. The United States serves as a major deployment center for retail AI tools from Microsoft, AWS, Blue Yonder, SymphonyAI, and o9. Microsoft introduced retail agent templates, catalog enrichment tools, Copilot Checkout, and brand agents at NRF 2026. Canada and Mexico are also relevant adoption areas, particularly where cross-border commerce requires coordinated inventory positioning.

Asia-Pacific is projected to expand at a 30.73% CAGR through 2031. China’s large e-commerce operators are developing proprietary planning infrastructure for extensive product portfolios. Japan’s retail sector is applying AI to address labor constraints and improve the use of purchase data. Toshiba developed a sales forecast AI using smart receipt purchase data and consumer cluster segmentation in 2026. India’s organized grocery and fashion retail sectors are adopting cloud-based forecasting tools, while South Korea’s digital commerce ecosystem supports rapid use of assortment and pricing applications.

Europe is a significant but compliance-shaped part of the generative AI in retail demand forecasting and merchandising market. Germany, the United Kingdom, and France are leading adopters because they combine large retail groups with mature digital operations. The European Union’s AI Act adds disclosure and governance requirements for relevant consumer-facing uses, which can create procurement caution but also raise demand for auditable systems. South America has demand for managed cloud replenishment tools as online retail grows and supply chains remain complex. Saudi Arabia and the United Arab Emirates are benefiting from technology investment plans, while South Africa and Egypt represent early-stage opportunities as retail networks formalize.

List of Companies Covered in this Report:

• Microsoft Corporation
• Google LLC
• Amazon Web Services, Inc.
• International Business Machines Corporation
• SAP SE
• Oracle Corporation
• Kinaxis Inc.
• NVIDIA Corporation
• Blue Yonder Group, Inc.
• RELEX Solutions Oy
• SymphonyAI, Inc.
• o9 Solutions, Inc.
• SAS Institute Inc.
• C3.ai, Inc.
• First Insight, Inc.
• Impact Analytics, Inc.
• ToolsGroup S.r.l.
• Anaplan, Inc.
• Infor Inc.

Additional Benefits:

• The market estimate (ME) sheet in Excel format
• 3 months of analyst support