At Synovia Digital, we investigate emerging technologies to keep up with an industry that shifts fast and often unexpectedly. While the insights we share are grounded in 2025 data and the best analyses available, they’re not absolute predictions — Supply Chain, technologies and retail world changes quickly, and new breakthroughs can always alter the landscape.
Still, these trends point strongly toward where retailer–supplier collaboration is probably headed next.
In CPG, the relationship between retailers and suppliers has historically been productive — but fragmented. Each side holds different data, works with different systems, and runs different planning cycles. The result? Slow decisions, mismatched forecasts, and reactive firefighting that costs both sides margin and growth.
But in 2025, retailer–supplier collaboration is undergoing its biggest transformation yet — driven by AI-powered joint intelligence.
AI is finally enabling retailers and CPG companies to work as one integrated ecosystem, sharing real-time data and aligning decisions across demand, supply, shelf, and replenishment. And what emerges is powerful.
1. Shared Demand Twins: One Forecast, Not Two
One of the most significant breakthroughs is the idea of a shared demand twin — a live, AI-powered model jointly used by both the retailer and the supplier.
Instead of debating whose forecast is “right,” both parties operate on a single source of truth:
- POS and loyalty insights from retailers
- Manufacturing, supply, and promotion plans from the supplier
- External signals like weather, events, competition, and social data
A 2025 Bain & Company analysis shows that CPGs with tighter retailer integration outperform peers in promo ROI, forecast accuracy, and service-level stability — all areas where AI-powered shared twins excel.
Source: Bain, Consumer Products Report 2025: Reclaiming Relevance in the GenAI Era
Shared demand twins eliminate the weekly back-and-forth. Teams collaborate on the same predictive model, enabling faster alignment and stronger outcomes.
2. Automated Replenishment Agreements
AI is also transforming replenishment from a “push vs pull” negotiation into a highly coordinated, automated process.
Key capabilities include:
- Real-time case-level or SKU-level inventory monitoring
- Automatic reorder triggers aligned with both parties’ service KPIs
- AI optimizing order quantity based on current uplift, promo plans, and constraints
- Transparent risk scoring for suppliers during supply shortages
TELUS Agriculture’s 2025 insights highlight AI-driven replenishment as one of the biggest enablers of on-shelf availability improvements and reduced operational friction between trading partners.
Source: TELUS Agriculture & Consumer Goods, AI in Trade Promotion Management, 2025
By 2026, automated replenishment agreements will likely be the norm for high-velocity CPG categories — beverages, personal care, household essentials, and snacking.
3. Shelf-Availability Prediction: Fixing Problems Before They Happen
Out-of-stocks remain one of the biggest pain points between retailers and suppliers. They hit:
- service levels
- promo performance
- shopper loyalty
- and ultimately, revenue
AI brings a proactive approach.
With machine learning models using POS, foot traffic, weather, local events, and supply chain constraints, retailers and suppliers can predict shelf risks days before they occur.
A 2025 report from The Consumer Goods Forum emphasizes that cross-enterprise AI analytics will be the core differentiator in achieving real-time shelf availability.
Source: Consumer Goods Forum, Collaboration Becomes the New Currency in Trade Promotions, 2025
Knowing a shelf will go empty before it actually does? That’s a game changer.
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What This Means for 2026: The Rise of the Joint Planning Ecosystem
Based on 2025 data and adoption patterns, here’s what we’ll probably see in 2026:
AI-native joint business plans
Retailer and supplier teams collaborate on live forecast engines, not static documents.
Unified promotional planning models
Promotions will be co-designed with shared AI simulations, reducing overstock and stockouts.
Real-time orchestration between store, DC, and factory
AI agents route inventory, rebalance orders, and coordinate labour across the network.
“Availability guarantees” backed by AI
Retailers and CPGs agree on service levels that are monitored — and corrected — automatically.
Joint sustainability decision-making
Shared AI models optimise carbon-impact across transport, replenishment, and sourcing.
Retailer–Supplier Collaboration 2.0 is not a promise — it’s already happening.
AI is simply accelerating the shift into an always-on, deeply connected partnership model.
For decades, retailer–supplier collaboration has depended on static reports, manual alignment, and post-hoc negotiations.
AI changes that forever.
Supply chains, promotions, replenishment, and shelf availability can now operate in real time — as one ecosystem, not two companies.
Retailers get better availability, accuracy, and agility.
Suppliers get better forecasts, fewer disputes, and more efficient execution.
Shoppers get what they want, when they want it.
The era of AI-powered joint intelligence is here — and 2026 will likely be the year it becomes standard practice across leading CPG categories.