The 2026 Supply Chain Resilience and AI Adoption Study reveals a widening performance gap between retailers with AI-ready, responsive supply chains and those relying on legacy planning cycles.
Incisiv, in partnership with the World Retail Congress and Anaplan, has released the 2026 Retail Resilience and AI Adoption Study, a global survey of 298 merchandise planning and supply chain executives across North America and EMEA.
The study finds that leading retailers average 71% full-price sell-through compared to 57% for the industry overall – a 14-point gap driven not by better products or more favourable markets, but by how quickly these organisations act on demand signals.
This study of 298 retail supply chain and merchandise planning executives across North America and EMEA reveals a persistent pattern: the industry has invested heavily in visibility, analytics and AI, yet the time between identifying a problem and acting on it has barely improved. Organisations know more than ever. They are not acting faster.
For every dollar of revenue, approximately 5 cents are lost or at risk because the organisation cannot respond fast enough.
The Latency Tax is not a market condition. It is an operating model choice. The 3-cent gap between Leaders and the industry is not a cost to manage. It is value waiting to be recovered.
“Our research shows that the organisations pulling ahead have restructured accountability and given systems the authority to act. The performance gap between them and the rest of the industry is now measurable in full-price revenue – and it is growing,” said Gaurav Pant, Chief Insights Officer, Incisiv.
Two-thirds of retailers estimate they lose 3% or more of annual sales because they cannot respond quickly enough to demand shifts, with a third putting that figure above 6%. For a billion-dollar retailer, that translates to more than US$60 million in annual losses. The study traces the source: 69% of organisations rebalance inventory monthly or less frequently, and 78% adjust upstream supply quarterly or slower – even when demand signals are available in real time.
“This research makes clear that the competitive divide in global retail is no longer about who has the best forecast. It is about who can turn insight into action fastest – and that requires a fundamentally different operating model,” said Ian McGarrigle, Chairman, World Retail Congress.
AI’s perceived value in retail planning is near-universal – more than 85% of executives rate it as critical across retail functions – but a 60-percentage-point gap exists between importance and actual deployment.
Only 31% have deployed AI in demand forecasting, and just 13% in exception management – where speed matters most.
The workforce dimension is equally stark. Executives expect more than half of all supply chain and merchandise planning roles to require fundamentally different skills by 2030, yet only 11% of teams have received any AI training to date. Organisations that fail to close this gap risk one of two outcomes: teams that distrust AI and override it, or teams that accept its outputs without the judgement to know when it is wrong.
The study segments respondents by operational maturity. Leaders – the top 10% – have taken a consistent sequence of steps that the broader industry has not.
- 90% refresh demand forecasts weekly or in real time, compared to two-thirds of the industry still on monthly or quarterly cycles.
- 24% have unified cross-functional incentives, five times the industry average.
- 76% operate at system-recommended or autonomous AI decision levels, with zero relying on fully manual processes.
“The retailers in this study who are winning have moved from just looking at data to acting on it. They are turning analytical noise into precise action by using AI-driven tools that bring purpose-built functionality and deep expertise into their core planning workflows. This connection between insight and execution is what enables them to make informed, confident decisions at the moment they matter, and it’s what truly separates the leaders from the rest,” said EJ Tavella, EVP, GM, Integrated Business Applications, Anaplan.
The path forward is clear from what Leaders have already done: compress planning cycles to match the pace of demand volatility; align incentives so that shared data leads to shared action; move AI from analytical overlay into the decision itself; and invest in workforce readiness before the transformation arrives, not after. The competitive divide in retail is no longer between organisations that have invested in AI and those that have not – it is between those that have turned that investment into faster, smarter decisions.
