Lexia Consulting
AI Readiness & Activation Programmes
Translate AI Ambition into Practical Advantage Across Your Operations
Most organisations have enthusiasm for AI but lack a realistic picture of where it creates value in their specific context. We help leadership teams cut through the noise — mapping your operations, identifying the right opportunities, and committing to pilots that actually move.
Why this matters now
AI ambition is common, AI traction is rare.
We see the same three patterns across FMCG, retail and B2B organisations — regardless of size or sector.
Early in the AI journey
The digital foundation is still taking shape — making it hard to know where AI fits and where to start.
Enthusiasm without direction
Some treat AI as a better search engine; others expect it to solve everything. There is appetite — but no shared, realistic picture of what AI can do today.
Bottom-up alone won't scale
Whoever builds a tool becomes its permanent support desk. Without leadership backing and governance, citizen-developer momentum stalls and tools get abandoned.
How we work
A structured three-stage engagement
We prepare thoroughly, run an intensive on-site workshop, then stay engaged until pilots are moving — the same team throughout, so nothing is lost in handovers.
Typically 1–2 weeks
Prepare
We map your value chain, route to market and systems footprint. We research 10–15 industry case studies and build working demonstrations tailored to your business and processes.
Typically 2–3 days on-site
Workshop
Three days with your leadership team — from AI fundamentals to hands-on agents, to a prioritised use-case portfolio with named owners and 1–2 committed pilots ready to move.
Typically 1–2 weeks
Embed
Structured follow-up sessions with use-case owners — unblocking, refining direction, and ensuring the workshop's decisions actually go somewhere beyond the room.
Our methodology
We map your business before we touch AI
In the preparation weeks we look at how people, processes, systems and data interact across your value chain. The handoffs between them are where AI and automation create the most value.
What we look for: where work hands off between functions, where data is re-typed between systems, and where knowledge sits in someone's head rather than in a process — that is where AI and automation create the most value.
Process handoffs
Where work moves between teams or functions — often manually, with data re-keyed and context lost at every step.
Knowledge in heads
Expertise that lives with individuals rather than in documented processes — a business fragility and an AI opportunity.
Repetitive tasks
High-volume, rules-based work that consumes time but adds no analytical value — the clearest candidates for automation.
What you get
Tangible artefacts and lasting capability
Documents you can act on immediately — and decisions your team owns long after we leave.
Deliverables
5–15 use cases scored on impact and feasibility, with rationale for what is in and what is cut.
One page per committed pilot: objective, named owner, named sponsor and clear first steps.
Phases, key milestones and dependencies for the prioritised pilots.
Decision rights, security principles and all templates and canvases to reuse internally.
Outcomes
Leadership aligned on what AI can and cannot do today — in your specific business context.
Clear agreement on where AI should — and should not — play across your value chain.
1–2 pilots greenlit, each owned in-house with a sponsor and clear next steps already agreed.
Agreement on who steers AI decisions and governance after we leave the room.
AI in practice
What leading organisations have already shipped
We bring 10–15 industry case studies into every engagement. Here are five examples across animal nutrition, FMCG and retail.
Cargill
Animal Nutrition & AgricultureWhat they did: Deployed AI across the full value chain — Agriness monitors 3.5 million sows across 30+ countries; CattleView tracks 350,000+ cattle via drone; Broiler View weighs up to 12,000 birds per camera. Generative AI ("Ask Emma") accelerates customer co-creation across product and nutrition teams. Winner of the 2026 BIG AI Excellence Award.
The industry reference point for turning farm data into actionable nutrition and logistics intelligence at scale.
dsm-firmenich
Animal Nutrition & HealthWhat they did: Built on IBM's Environmental Intelligence Suite to pull hourly weather data from 61,000 points worldwide and forecast mycotoxin risk in corn and wheat field-by-field — up to 8 months before harvest. Grounded in the World Mycotoxin Survey, running annually since 2004, covering 43,000+ samples across 80+ countries.
Proof that domain expertise combined with publicly available data becomes a differentiated, sellable advisory service.
Unilever
FMCGWhat they did: Deployed 100,000 AI-enabled freezer cabinets across 60 countries to provide real-time stock insights and drive retailer reorders. AI analysis of weather data sharpens production forecasts — improving accuracy by 10% in Sweden and saving up to 10% of high-value ingredients such as vanilla and cocoa. Named a Gartner Supply Chain Master six consecutive years.
AI-enabled field assets turning point-of-sale and environmental data into end-to-end supply chain intelligence.
Heineken
FMCG / BeveragesWhat they did: AIDDA (AI Data-Driven Advisor) provides sales representatives with real-time, data-driven recommendations at the point of customer contact — scaled to 8 markets with 490,000 engagements per day and a measurable 5% sales uplift in Mexico. Blue Yonder AI handles demand planning by integrating weather, events, promotions and social signals.
AI turning field sales activity into consistent, measurable commercial advantage across multiple markets simultaneously.
Walmart
RetailWhat they did: Transitioned from isolated AI models to a unified ecosystem of purpose-built agents — Sparky for customer shopping assistance, an Associate agent for store operations and HR, and Wally (merchant assistant) for buying and range decisions. AI-monitored HVAC and equipment via digital twins reduced emergency maintenance costs by 30%.
The clearest example of agentic AI moving from pilot to enterprise-wide deployment across customer, associate and merchant workflows.
Ready to move from AI curiosity to committed execution?
Let's start with a conversation about your business — no obligation, no boilerplate.
Get in touch