EXPERTISE EXTRACTION is the pattern worth watching across AI product development right now. The most generic AI tools are converging rapidly on the same capabilities. The differentiator is not the model architecture, but the training input: specific, lived, domain-bound knowledge that no competitor can simply scrape or license. Three recent launches to make this concrete:
MAGGI, Nestlé's seasoning brand, built MAMI for Central and West African markets — an AI business advisor accessible by toll-free voice call on any basic mobile phone, requiring no internet connection or smartphone. Crucially, MAMI was not trained on generic business content. It was built on the expertise of experienced mammies: the women who run open-air ingredient markets across the region, and whose knowledge of pricing, stock control and cash flow has traditionally passed through informal mentorship. The tool launches first in Côte d'Ivoire. MAGGI has been investing in this trader ecosystem since 2016, when it developed a UNESCO literacy programme that has graduated more than 2,500 women. MAMI extends that investment into AI infrastructure, and the result is a tool that no rival brand could reproduce without the same on-the-ground relationships.
Meta took an analogous approach at platform scale. The Creator Assistant, launched in June 2026 and rolling out to Facebook creators in the US, Canada and India, moves past the standard metrics dashboard to explain why specific content performed — drawing on each creator's own audience and engagement data. The tool supports follow-up questions, suggests content directions based on trending audio, and sits inside the creator dashboard rather than as a separate product. Meta simultaneously expanded its AI-powered Reel translation to nine languages, including Arabic, Thai and Vietnamese, reaching over 500 million weekly viewers. The underlying asset is platform-specific performance data that external tools cannot replicate.
Realtor.com launched RealAssist AI in June 2026, built on Google's Gemini and connected to Multiple Listing Service data. The tool allows prospective US homebuyers to describe an ideal property in plain language, returns matched listings, and integrates full payment estimates — taxes, insurance, and HOA fees — alongside connections to real estate agents, all within a single conversational interface. The launch is deliberately positioned around transparency: the US housing market has seen a recent decline in consumer trust partly driven by misleading AI-generated listing photos, and Realtor.com is betting that financial completeness rebuilds confidence in a crowded field that includes Zillow and Redfin.
For brands and product teams, the signal is clear. The AI investment question worth asking is not about model selection, but about knowledge inventory: what proprietary expertise, practitioner wisdom or domain-specific data does your organisation hold that no one else can train on?