To make their AI models truly effective, Personio enriched them with specific, internal go-to-market knowledge. They uploaded ICP definitions, pitch decks, and onboarding processes. This proprietary context, layered on top of customer data, is critical for training LLMs to be relevant for a specific business.
A custom AI tool offers more value than a generic one like ChatGPT because it can be trained on a brand's unique, paywalled intellectual property. This creates a curated experience that aligns perfectly with your teachings and provides answers that cannot be found for free on the web, solidifying your expertise.
The key for enterprises isn't integrating general AI like ChatGPT but creating "proprietary intelligence." This involves fine-tuning smaller, custom models on their unique internal data and workflows, creating a competitive moat that off-the-shelf solutions cannot replicate.
A key competitive advantage for AI companies lies in capturing proprietary outcomes data by owning a customer's end-to-end workflow. This data, such as which legal cases are won or lost, is not publicly available. It creates a powerful feedback loop where the AI gets smarter at predicting valuable outcomes, a moat that general models cannot replicate.
Since LLMs are commodities, sustainable competitive advantage in AI comes from leveraging proprietary data and unique business processes that competitors cannot replicate. Companies must focus on building AI that understands their specific "secret sauce."
Instead of guessing at marketing copy, build an AI model of your ideal customer. By feeding it internal data like call transcripts and external data like forum posts, this "digital twin" can review and rewrite your marketing materials using the customer's exact language.
By creating a private GPT and uploading all relevant business information, you can build an AI consultant that understands your specific context. This helps clarify priorities, vet new strategies, and maintain focus.
If a company and its competitor both ask a generic LLM for strategy, they'll get the same answer, erasing any edge. The only way to generate unique, defensible strategies is by building evolving models trained on a company's own private data.
Consistently feed your AI tool information about your company, products, and sales approach. Over time, it will learn this context and automatically tailor its sales prep output, connecting a prospect's likely problems directly to your specific solutions without needing to be reprompted each time.
The ultimate value of AI will be its ability to act as a long-term corporate memory. By feeding it historical data—ICPs, past experiments, key decisions, and customer feedback—companies can create a queryable "brain" that dramatically accelerates onboarding and institutional knowledge transfer.
For superior AI-generated content, create a persistent knowledge base for the model using features like Claude's "Projects." Uploading actual sales call transcripts and customer interviews trains the AI on your specific customer's voice and pain points, resulting in more authentic and targeted marketing copy.