Industry Stats: Forecasting, Supply Chain & AI Benchmarks
A continuously refreshed snapshot of the numbers that matter to demand planners, supply chain leaders, CPG operators, manufacturers, and small business owners. Every figure is sourced from a verified primary publication, no blogs, no aggregators.
Quick answer: the state of forecasting & AI in 2026
- Forecast accuracy: Median MAPE is ~25% in food & beverages and ~50% in durable consumer products. Best-in-class operators hit ~20%.
- AI in supply chain: Gartner projects 70% of large organizations will adopt AI-based forecasting by 2030.
- Stockouts: Cost global retailers approximately $1 trillion annually (IHL Group / Retail Dive).
- Manufacturing: Federal Reserve capacity utilization sits at 75.8%, 2.4 pts below long-run average. ISM PMI was 47.9 in December 2025 (contraction).
- Enterprise AI: 88% of organizations now use AI in at least one function; 71% use generative AI. But 80%+ report no measurable EBIT impact yet (McKinsey).
- Small business AI: 76% of SMBs use AI; only 14% have it fully integrated into core operations (Goldman Sachs).
Supply Chain & Demand Planning
Benchmarks for forecast accuracy, AI adoption in planning, and where best-in-class operators sit today.
70%
of large organizations will adopt AI-based supply chain forecasting by 2030.
Source: Gartner press release, Sept 2025
~25%
median forecast error rate in food & beverages; upper quartile achieves ~20%.
Source: Gartner, How to Set Meaningful Forecast Accuracy Targets
~50%
benchmark forecast error rate in durable consumer products, a structural accuracy gap.
Demand Forecast Error %
remains the single most-tracked supply chain KPI according to ISM’s monthly metric series.
Source: Institute for Supply Management
Retail & CPG
Stockouts, on-shelf availability, and inventory pressure — the dollars left on the floor when planning misses.
~$1T
global retailer revenue lost annually to persistent stockouts.
Source: Retail Dive · IHL Group study
Top 3
retailer challenges in 2025: stockouts, stricter return policies, and inflation-driven cost volatility.
Source: National Retail Federation, 2025
Omnichannel
inventory now spans in-store, click-and-collect, and third-party (Instacart, DoorDash, Uber) fulfillment, making availability harder to track.
Real-time
shelf visibility via computer vision is now the dominant CPG investment area for reducing OOS in 2025–26.
Manufacturing
Real signals from ISM and the Federal Reserve on capacity, demand momentum, and the path into the back half of 2026.
82.4%
of normal capacity utilized by manufacturers (ISM Fall 2025 survey), up 3.2 pts from May 2025.
75.8%
Federal Reserve manufacturing capacity utilization, 2.4 pts below the long-run (1972–2025) average.
Source: Federal Reserve G.17 release
47.9
ISM Manufacturing PMI for December 2025, the lowest of the year, signaling contraction heading into 2026.
H2 2026
is when supply executives expect manufacturing growth to accelerate. H1 outlook is cautious-optimistic.
Enterprise AI & Analytics Adoption
How fast organizations are deploying AI and the gap between deployment and measurable EBIT impact.
88%
of organizations now use AI in at least one business function, up 10 pts year over year.
Source: McKinsey, State of AI 2025
71%
regularly use generative AI in at least one function, up from 65% in early 2024.
Source: McKinsey State of AI 2025
80%+
of organizations report no tangible enterprise-level EBIT impact from gen AI yet. Workflow redesign is the differentiator.
23%
of organizations are already scaling agentic AI systems; another 39% are experimenting.
AI for Small Business
Small firms are closing the AI gap fast but core operations integration is still where most upside sits.
76%
of small businesses now report actively using AI in their operations.
93%
of small businesses using AI say it has had a positive impact on their business.
14%
are fully integrating AI into core operations, leaving large headroom for productivity gains.
67%
of small business owners expect AI to increase their revenue going forward.
Act on these benchmarks. Geneva Forecast API.
These stats describe the gap. Geneva Forecast closes it. One API call returns a production-grade forecast across 45+ algorithms with automatic model selection per SKU — the same engine RoadMap has used with Fortune 500 customers since 1988, now exposed for your team, your Python notebooks, or your AI agents.
pip install, paste API key, call geneva.forecast().Frequently asked questions
What percentage of large organizations will use AI-based supply chain forecasting by 2030?
According to a September 2025 Gartner press release, 70% of large organizations will adopt AI-based supply chain forecasting to predict future demand by 2030.
What is a typical forecast error rate in consumer goods?
Gartner benchmarks show median forecast error of around 25% in food and beverages (upper-quartile performers reach ~20%), while durable consumer products see error rates closer to 50%.
How much do stockouts cost retailers globally?
Persistent stockouts cost global retailers approximately $1 trillion in lost revenue annually, according to an IHL Group study reported by Retail Dive.
What is current U.S. manufacturing capacity utilization?
The Federal Reserve G.17 release reports manufacturing capacity utilization at 75.8%, which is 2.4 percentage points below the long-run 1972–2025 average. ISM’s Fall 2025 survey shows manufacturers operating at 82.4% of normal capacity.
What share of organizations now use AI?
McKinsey’s State of AI 2025 found that 88% of organizations now use AI in at least one business function, up 10 points year over year. 71% regularly use generative AI in at least one function.
What percentage of small businesses use AI?
Goldman Sachs 10,000 Small Businesses Voices (2026) found 76% of small businesses now use AI in their operations, with 93% reporting positive business impact. However, only 14% are fully integrating AI into core operations.
How can I act on these benchmarks?
RoadMap Technologies builds production-grade forecasting infrastructure. The Geneva Forecast API exposes 45+ algorithms behind a single call, automatically selecting the best model per SKU and serving forecasts to dashboards, Python, or LLM agents via MCP. Operators replacing legacy stacks with Geneva typically cut MAPE 15-25% within a quarter.
How often are these statistics updated?
RoadMap Technologies re-verifies every statistic on this page weekly against its primary source. When the source publishes new data, the figure changes on this page within seven days. Stats that cannot be re-verified against an official source are removed.
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