How to Drive Business Growth During the Evolution of AI-Powered Demand Forecasting
Build a best-of-breed AI foundation to stay ahead of demand and the competition.
From product planning to final markdowns, demand forecasting is at the heart of delivering high-margin growth. Even the smallest brands and retailers must sense how much inventory is needed each day to maximize sell-through while minimizing discounts.
Now layer in the complexities of a global business with hundreds or thousands of SKUs and forecast becomes even more daunting. Outdated demand forecasting methods built on historical data and instinct—crumble under today’s pace of change. Retailers and brands simply cannot afford to just guess what consumers want.
As Rupal Deshmukh, Partner in the Strategic Operations practice at Kearney, explained in an interview with Retail TouchPoints:
Demand is typically the most important piece of input that goes into the operations of a company. Poor demand forecast accuracy equals cash out the door.”1
That’s why this eBook dives deeper into:
- The evolution of traditional demand forecasting roles.
- The impact of AI on demand forecasting.
- How AI demand forecasting connects the retail lifecycle.
1 Adam Blair, “AI in Action: How Retailers are Transforming Demand Forecasting with New Tech,” Retail TouchPoints, March 17, 2025.
Table of contents
Introduction
AI shifts demand forecasting roles
Business benefits of AI-powered demand forecasting
How AI demand forecasting connects the retail lifecycle
About Centric Software
Introduction
From product planning to final markdowns, demand forecasting is at the heart of delivering high-margin growth. Even the smallest companies must sense how much inventory is needed each day to maximize sell-through while minimizing discounts.
Now layer in the complexity of a global business with hundreds—or thousands—of SKUs, and the forecasting challenge becomes even more daunting. Traditional methods built on historical data and instinct simply can’t keep up. Retailers and brands can no longer afford to guess what consumers want.
As Rupal Deshmukh, Partner in the Strategic Operations practice at Kearney, explained in an interview with Retail TouchPoints:
“Demand is typically the most important piece of input that goes into the operations of a company. Poor demand forecast accuracy equals cash out the door.”1
Consumer behavior has also shifted dramatically. Shoppers no longer rely solely on physical stores to discover and buy products. Today, discovery happens through clicks, scrolls and social feeds—shifting demand signals to digital.
This is where the opportunity lies: businesses that embrace AI forecasting will thrive. Those that don’t will fall behind.
Retailers often over-index on internal POS data while missing external demand signals:
“They often have a lot of POS data, but they don’t use [the data that] product companies have or even what consumers have. They don’t listen to consumers or market signals; we find over and over again that they don’t do this right. Companies that are doing well have a true pulse on market signals, for example what consumers are seeing on social media, as well as weather trends and the impact of geopolitical events.”1
Enter AI-powered forecasting: “AI allows you to evaluate unstructured data in a much more structured way.”1
But before unlocking these capabilities, it’s important to understand how AI is reshaping the roles and responsibilities around demand forecasting—and how that shift is powering a new era of productivity.
1 Adam Blair, “AI in Action: How Retailers are Transforming Demand Forecasting with New Tech,” Retail TouchPoints, March 17, 2025.

AI shifts demand forecasting roles
With AI-driven demand forecasting, retailers can anticipate what will sell, which size or color will trend and which messaging will resonate—before consumers act.
As a result, forecasting is no longer siloed or reactive. Teams across planning, merchandising, allocation and pricing are moving toward faster, more data-driven decision making. Here’s how traditional roles are evolving:
The merchandise planner/financial planner has evolved from a spreadsheet-heavy number cruncher to a strategic decision maker. AI frees this role to focus on high-value planning and cross-functional alignment.
The buyer/merchant/assortment planner has evolved from intuition-led buying to data-validated assortment curation. AI strengthens creative decisions with predictive confidence.
The allocator/inventory manager/replenishment planner evolved from reactive firefighting to a proactive inventory controller. AI empowers smarter decisions across the supply chain network.
The sales representative/wholesale manager (brand side) has evolved from a reactive seller to a proactive partner. AI helps sales teams provide value-added insight to retail partners and improve seasonal performance.
The pricing/lifecycle management team has evolved from static pricing operators to lifecycle strategists. AI enables more responsive, profit-protecting price management across the season.
This is just a snapshot of the shifting roles as outlined in more detail in the eBook titled, “From Reactive to Predictive: The AI-Driven Demand Forecasting Evolution,” however, retailers “need to build on the pockets of goodness that AI is creating,“ where using external market signals to augment forecast accuracy has led to improvements by as much as 10 to 20 percentage points.1
But the business benefits don’t stop there.
Business benefits of AI-powered demand forecasting
AI-powered forecasting empowers retailers to predict demand with speed, precision and confidence. By accurately forecasting at the SKU level and modeling dynamic scenarios, teams can minimize inventory risk, reduce markdowns and improve responsiveness across the entire product lifecycle.
One such company leading this shift is Trespass, one of the UK’s most successful outdoor clothing brands, retailing a wide range of products from specialist performance clothing to outdoor sports equipment, selling internationally and exporting to over 60 countries.
“Like many others in our industry, we arrived at a point where the manual execution of daily activities was reaching a critical threshold. Our merchandise teams needed system support to free up time and be able to operate and strategize more efficiently,” explains Afzal Khushi, Director at Trespass.
Trespass chose Centric Planning™ for AI-driven planning, merchandise and allocation to drive more profitable assortments. With advanced analytics and solutions embedded with AI, Trespass expects to reduce reporting time by up to 20% and drive better inventory allocation in 300+ stores.
“Mondays were usually spent updating reporting in spreadsheets, so we expect to gain back one day a week, enabling our merchandisers to drill down deeper into decision making. Instead of setting up these massive spreadsheets, it will all be there in one inclusive system, making range planning faster and freeing up time in-season,” adds Kean Martin, Senior Merchandiser at Trespass.
“Everyone’s excited about being able to work faster and more efficiently. Centric Planning will really speed things up and it will make us, in the long run, more accurate and more profitable as well,” concludes Martin.
“By forecasting replenishment using AI-assisted suggestions, we expect to reduce markdowns and increase store sales by filtering each SKU into the right location.” — Kean Martin, Senior Merchandiser at Trespass
AI-powered demand forecasting benefits snapshot
- Improve forecast accuracy in data-sparse categories.
- Reduce overproduction and minimize unsold inventory.
- Align assortment, pricing and supply strategies with financial goals.
- Enhance agility with dynamic scenario planning.
- Enable data-driven investment and sales growth decisions.
How AI demand forecasting connects the retail lifecycle
AI demand forecasting doesn’t just improve accuracy—it connects the entire retail planning lifecycle. With scenario planning, granular forecasts and real-time demand signals, AI helps teams align decisions from initial buy to final markdown.
Here’s how it supports each phase:
Pre-season (Merchandise Financial Planning, Assortment Planning, Buy Planning)
Key Roles:
Merchandise Planner/Financial Planner
Buyer/Merchant/Assortment Planner
Key activities:
Set financial and category sales targets.
Forecast future demand by style, color and size.
Build assortments across channels, regions and clusters.
Allocate initial buy quantities to meet sales and margin goals.
How AI demand forecasting supports:
Predicts demand for new styles using visual/attribute similarity.
Simulates multiple scenarios for investment planning.
Aligns assortment mix with consumer demand and financial KPIs.
Enables targeted assortment planning by channel and consumer segment.
In-season (Allocation, Replenishment, Inventory Optimization)
Primary roles involved:
Allocator/Inventory Manager/Replenishment Planner
Merchandise Planner
Sales Representative/Wholesale Manager
Key activities:
Distribute inventory to stores/channels.
Monitor sales and adjust stock flows.
Manage transfers, reorders and inventory shifts.
Anticipate sell through and demand surges.
How AI demand forecasting supports:
Refines forecasts in real time with actual sales data.
Identifies where stock is needed to avoid missed sales.
Guides replenishment and transfer decisions at the SKU-store level.
Improves visibility into wholesale demand and booking trends.
End-of-season/lifecycle management (Markdown Optimization, Price Management, Inventory Liquidation)
Primary roles involved:
Pricing/Lifecycle Management team
Allocator/Inventory Manager
Merchandise Planner
Key activities:
Set markdown strategies to maximize full-price sell through.
Adjust pricing to clear remaining inventory.
Evaluate sell through by size, color, store and product group.
Learn from outcomes to inform next season's planning.
How AI demand forecasting supports:
Optimizes markdown timing and depth based on real-time demand.
Simulates pricing impacts on margin and inventory.
Improves liquidation decisions while protecting profitability.
Feeds performance insights into pre-season planning cycles.
How AI demand forecasting connects the retail lifecycle
AI-powered demand forecasting isn’t just about improving accuracy—it’s about enabling smarter, faster decisions at every stage of the product lifecycle.
Retailers that integrate AI into their forecasting processes are better equipped to align teams, respond to real-time demand shifts, and drive profitable growth.
Centric Planning delivers the intelligence and flexibility modern businesses need to stay ahead of change—turning data into action and forecasts into results.
See how Centric Planning can support your planning transformation.
About Centric Software
Centric Software® (centricsoftware.com)
From its headquarters in Silicon Valley, Centric Software provides an innovative and AI-enabled product concept-to-commercialization platform for retailers, brands and manufacturers of all sizes. As experts in fashion, luxury, footwear, outdoor, home, food & beverage, cosmetics & personal care as well as multi-category retail, Centric Software delivers best-of-breed solutions to plan, design, develop, source, comply, buy, make, price, allocate, sell and replenish products.
- Centric PLM™, the leading PLM solution for fashion, outdoor, footwear and private label, optimizes product execution from ideation to development, sourcing and manufacture, realizing up to 50% improvement in productivity and a 60% decrease in time to market.
- Centric Planning™ is an innovative, cloud-native, AI solution delivering end-to-end planning capabilities to maximize retail and wholesale business performance, including SKU optimization, resulting in an up to 110% increase in margins.
- Centric Pricing & Inventory™ leverages AI to drive margins and boost revenues by up to 18% via price and inventory optimization from pre-season to in-season to season completion.
- Centric Market Intelligence™ is an AI-driven platform delivering insights into consumer trends, competitor offers and pricing to boost competitivity and get closer to the consumer, with an up to 12% increase in average initial price point.
- Centric Visual Boards™ pivot actionable data in a visual-first orientation to ensure robust, consumer-right assortments and product offers, dramatically decreasing assortment development cycle time.
- Centric PXM™, AI-powered product experience management (PXM) encompasses PIM, DAM, content syndication and digital shelf analytics (DSA) to optimize the product commercialization lifecycle resulting in a transformed brand experience. Increase sales channels, boost sell through and drive margins.
Centric Software’s market-driven solutions have the highest user adoption rate, customer satisfaction rate and fastest time to value in the industry. Centric Software has received multiple industry awards and recognition, appearing regularly in world-leading analyst reports and research.
Centric Software is a subsidiary of Dassault Systèmes (Euronext Paris: #13065, DSY.PA), the world leader in 3D design software, 3D digital mock-up and PLM solutions.
Centric Software is a registered trademark of Centric Software, Inc. in the US and other countries. Centric PLM, Centric Planning, Centric Pricing & Inventory, Centric Market Intelligence, Centric Visual Boards and Centric PXM are trademarks of Centric Software, Inc. All third-party trademarks are trademarks of their respective owners.
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