En samling artiklar och inlägg om AI-strategi, styrning och CRM, ursprungligen publicerade på LinkedIn. Varje post länkar tillbaka till originalinlägget för att läsas i sin helhet.
LinkedIn Post
Why Understanding Token Consumption Is Critical for Business Success with AI
AI success isn't measured by token volume, but by the business value each token generates. The right model for the task, well-designed prompts, and prompt caching all compound into real cost and ROI advantages.
Your AI is only as intelligent as the data, processes and business knowledge it can access. Before investing further in models and agents, invest in data strategy — AI maturity follows data maturity.
Training a large model can use over a thousand megawatt-hours of electricity. A look at AI’s environmental costs, and how organizations can pursue AI progress responsibly.
AI in CRM: Navigating the Regulatory Landscape and Data Privacy Challenges
As CRM platforms embed AI across the customer lifecycle, the regulatory, ethical and privacy stakes rise fast. A practical look at the EU AI Act, US FTC guidance and India’s DPDP Act, and how CRM teams should respond.
How Does Prompt Engineering Help in CRM Processes?
A practical breakdown of where prompt engineering earns its keep inside CRM: customer service, personalization, lead qualification, analytics, training and marketing, each with a concrete example prompt.
LLM hallucinations can’t be eliminated — but they can be significantly reduced and managed. Enterprise RAG grounds AI responses in relevant, verified data through retrieval, citations and guardrails. Benchmarking for accuracy, citation quality and relevance is essential before production. Trusted AI comes from better retrieval, stronger grounding, continuous evaluation and monitoring.