Beyond the ChatGPT hype
Every executive wants to use "AI" today, but few know how to turn the hype into tangible business results. Generative Artificial Intelligence can transform companies, but implementation requires strategy.
The first steps
1. Identify the real pain points Do not implement AI for its own sake. Look at your processes: where is the human bottleneck worst? Customer service? Report generation? Document triage?
2. Get your house in order (your data) AI works no miracles with bad data. The effectiveness of custom models or RAG (Retrieval-Augmented Generation) depends on the quality of your company's knowledge base. If your processes are disorganized, AI will simply automate the chaos.
High-ROI use cases
- Internal knowledge assistants: picture a chat where a new employee can ask about HR policies or product manuals and get precise answers, grounded in the company's internal PDFs.
- Tier 1 support triage: answering common customer emails, checking order status, and pre-classifying tickets before they reach a human.
- Code and query generation: accelerating technical teams by helping document legacy systems or generate complex SQL queries.
Security first
When adopting enterprise AI, prefer "Enterprise" versions (such as Azure OpenAI, AWS Bedrock, or Google Cloud AI) that guarantee your company's data will not be used to train public models. Privacy is fundamental.