Section
Strategy, costs and adoption.
4 stories
Plenty of companies pay for AI tools without knowing whether they pay off. Measuring return on AI is harder than counting licenses, but it is doable. This framework covers baselines, the costs people forget, the benefits worth tracking, a worked calculation and the mistakes that inflate results.
There is no single US law requiring businesses to label all AI use, but several federal and state rules do require disclosure in specific situations: bots that sell, AI voices on calls, fake reviews, political ads and more. Here is a practical map of when disclosure is required, and when it is simply wise.
Businesses adopting AI face a choice between off-the-shelf tools, AI features inside software they already use, custom apps built on model APIs, retrieval over their own documents, and fine-tuned or self-hosted models. This guide compares the options on cost, control, speed and risk.
AI chatbots can answer customer questions around the clock and cut wait times, or they can trap people in loops and invent policies. The difference is in the setup: what the bot is allowed to do, what it knows, when it hands off to a person and how you measure it. Here is a practical guide.
