AI for FMCG that ships. FMCG AI consulting and development — demand forecasting, inventory optimisation, trade-promotion analytics, supply-chain visibility, and BI automation. Production AI in 3-8 weeks, grounded in real demand-forecasting and FMCG data case studies. See the latest AI in FMCG statistics.
Last updated August 2026 · Our latest FMCG demand-forecasting model holds 88% accuracy in production on unified ERP, MES and SCM data.
Four specialist areas where AI in the FMCG industry pays back fastest — targeting the most expensive problems in consumer-goods data and operations.
Lift-and-shift plus modernise — migrate your on-premises SQL infrastructure to Azure with zero data loss and minimal downtime.
Replace legacy SSRS with modern Power BI paginated and interactive reports — with automated distribution and executive dashboards.
ML-powered demand intelligence that accounts for seasonality, promotions, and external signals to reduce stockouts and overstock.
Automate complex commission calculations, tax compliance, and merchant reconciliation — with full audit trails.
A leading FMCG enterprise migrated from on-premises SQL Server to Azure — fully modernised in 20 weeks with zero data loss. Separately, our ML demand-forecasting engine reached 88% accuracy for a manufacturer on unified ERP/MES/SCM data.
Read the FMCG migration case study · Read the demand-forecasting case study
Azure-first with the modern data stack for FMCG scale.
Concrete problems AI solves across the FMCG sector — not whitepapers.
On-prem SQL Server to Azure cloud with all stored procedures, jobs, and linked servers migrated intact
1,000+ SSRS reports converted to Power BI with automated delivery and role-based access control
ML-driven forecasting models integrated with ERP/WMS for live inventory optimisation
Commission engines, tax compliance modules, and reconciliation workflows replacing manual Excel processes
200+ stored procedures, 1,000+ reports — we have done it at scale and delivered on time.
Parallel validation, phased cutover, and rollback plans ensure business continuity throughout.
Commission and compliance reporting built to pass finance audit — not just look good in a demo.
Data engineering, ML, BI, and automation — one team, one engagement, no coordination overhead.
AI in FMCG is the use of machine learning and data engineering to run fast-moving consumer goods operations more accurately and efficiently — demand forecasting, inventory optimisation, trade-promotion and pricing analytics, supply-chain visibility, and the automation of reporting and finance workflows. In practice, artificial intelligence in FMCG turns the huge volumes of sales, ERP, and market data that consumer-goods companies already generate into decisions they can act on daily.
The highest-value applications of AI in FMCG are demand forecasting (accounting for seasonality, promotions and external signals), inventory and safety-stock optimisation, trade-promotion and price-pack analytics, supply-chain and route-to-market visibility, and the automation of BI reporting, commission and tax-compliance workflows. We prioritise the use case with the clearest return first, then expand.
Across the FMCG industry and sector, AI is used to cut forecast error and stockouts, free planners from manual Excel work, unify data scattered across ERP/MES/SCM systems, and give leadership real-time visibility. For a manufacturer we built an ML demand-forecasting engine that reached 88% prediction accuracy on unified SAP ERP, Siemens MES and Oracle SCM data — the same class of system we build for FMCG companies.
Yes. FMCG AI consulting is a core practice: senior AI/ML and data engineers scope the highest-value use case, then build and deploy it in production — typically in 3-8 weeks, not quarters. We work in weekly sprints with working software at each step, and we can deploy in your cloud, private cloud or on-premises.
For a leading FMCG enterprise we migrated 200+ stored procedures and 1,000+ reports to Microsoft Azure in 20 weeks with zero data loss, cutting infrastructure cost by 40%. For a manufacturer, our demand-forecasting engine reached 88% accuracy and enabled proactive inventory management. See our FMCG migration and manufacturing demand-forecasting case studies for the full detail.
We run a full compatibility analysis first, migrate in phased batches with parallel validation, and convert legacy SSRS reports to Power BI with row-level security via Azure AD — validating output against the source before cutover. Our 98%+ migration success rate reflects this rigorous, business-continuity-first process.
The use of AI in FMCG comes down to three jobs: predict demand more accurately, hold less stock without running out, and take manual work out of planning, reporting and finance. On top of those sit trade-promotion and pricing analytics and supply-chain visibility. We start with the one job that pays back fastest on your data, ship it in production, then add the next.
The fastest-payback AI use cases in FMCG are demand forecasting and inventory optimisation — they cut stockouts and free working capital quickly. Automating BI reporting and finance workflows (commissions, tax compliance) is close behind because it removes recurring manual effort. Trade-promotion and price-pack analytics take a little longer but compound over time. For the numbers behind adoption and ROI, see our AI in FMCG statistics.
Tell us your migration or analytics challenge. We'll scope a plan in 48 hours.
Schedule a Discovery CallBook a call for a scope and a fixed estimate, or get the report first. Either way you talk to a senior engineer, not a salesperson.
A 30-minute call with a senior engineer. You leave with a scope, a timeline and a fixed estimate — usually back to you within 48 hours.
Book a call — get a scope + estimateGive us a work email and we'll send the State of AI in FMCG 2026 report and a free project scope + estimate. No spam, one follow-up.