Few technologies have reached so many products so quickly. In a matter of months, almost every company has asked itself how to use artificial intelligence. Far fewer have asked what for.
Our answer is simple: AI adds value when it solves a real problem for the people who use the product. If its only job is to let you say the product has AI, it adds nothing.
Where it tends to help
- Search and discovery: understanding what someone means, not just what they type.
- Summarising and explaining: turning documents, bills or complex data into something clear.
- Personalisation: adapting content and recommendations to each context.
- Automating the repetitive: sorting, tagging and drafting so the team can decide.
Where to tread carefully
In decisions that affect people's lives, such as credit, health or employment, AI should help people decide, not decide on its own. And whenever it answers a user, it has to be clear what it knows, what it doesn't, and how to reach a human.
Designing for trust
A good AI experience explains what it's doing, lets you correct it and doesn't hide its mistakes. Transparency isn't a legal add-on. It's what makes people come back.
The question isn't what AI can do. It's what it should do for your users.
We always start with a small use case that's measurable and clearly valuable. If it works, it grows. If it doesn't, you learn fast and at little cost. That's how artificial intelligence goes from promise to result.