P&G wants to build AI content production capability into the marketing function — not outsource it to the agency roster. Marc Pritchard has been public about the goal: significant reduction in content production costs without quality compromise. The brief is how to get there in a way that works across 65+ brands and 10 categories.
91% Match P&G · Prior engagement · Relationship activeP&G's Chief Brand Officer has been the most articulate voice in FMCG on AI in marketing. The public position is clear: AI should reduce production costs while maintaining creative quality. What's less clear — from the outside — is whether that ambition is being executed as a marketing function capability or as a series of agency experiments.
The difference matters. Agency experiments produce case studies. Marketing function capability produces a new operating model. That's what this brief is actually asking for.
we worked on P&G brands before. we know the standard.A pipeline where one brief produces four brand-matched, deployed outputs in under 90 seconds. The Mastercard output looks nothing like the Granola output. Brand governance is built into the generation, not applied after. Directly relevant to P&G's multi-brand challenge.
55 editorial feeds, automated daily content pipeline, consistent brand voice across all outputs. AI content at scale with a single enforced editorial standard. Demonstrates the governance model P&G needs applied to a real content operation.
Full multi-format GTM packs for two challenger brands entering new markets. Four output types per brand (strategy deck, press narrative, agency brief, competitive map) — brand voice consistent across all four despite different formats.
Map the current content production workflow for three P&G brands: one global premium brand (Gillette), one mass-market brand (Ariel), one digital-first brand (Olay). For each: brief-to-asset time, cost per execution, number of human touchpoints, current AI tool usage (sanctioned or not). Identify the 2–3 production stages where AI has the highest impact without brand risk.
Redesign the production workflow for all three pilot brands. Build the AI governance layer: what the brand director approves, what the AI produces without approval, what requires human review. Run live campaigns through the redesigned workflow. Measure: time, cost, quality (brand director assessment). Target: 40% production time reduction with zero quality-flagged outputs.
Build the P&G AI Content Production Framework. Toolkit, governance model, quality bar, training programme — designed to work across all 65+ brands with brand-specific configuration. Rollout to 8 additional brands. Year-two recommendation based on 12 months of pilot evidence.
P&G client history. 15+ years brand strategy and AI product development. Built AI systems where brand governance is a design constraint, not a retrofit. Former R/GA (handled global brand accounts), MediaMonks (content production at scale), Poke, Dare, AnalogFolk. Now building AI-native products including The System — which does for business development what P&G needs done for brand content.
Career: MediaMonks ($3.2M Web3 revenue) → Contagious → Burst (founder) → R/GA, Poke, Dare, AnalogFolk. Clients: Nike, Adidas, Google, Meta, Gucci, BMW, P&G, EA, Netflix, Sony, TikTok, McLaren, Unilever. BIMA 100 Tech Pioneer. Published author (BCS, 2024).
For an 18-month engagement at this scope, we'd bring in a production design partner and a P&G brand specialist from our network. Strategy, AI system design, and brand governance framework stay with us.
Give us one active P&G content brief — your choice of brand. We'll produce the outputs twice: once through the current agency workflow (timed and costed), once through an AI-assisted workflow with our governance checkpoints in place. You compare the outputs. If you can't tell which is which on quality — and the AI version is 60% faster — we've made the case. One week. One brief. No commitment.