Transform Your AI Strategy: Centering Customers for Success

Artificial intelligence is often seen as a technological race, focusing on building the most powerful models and algorithms. However, for AI to truly transform industries, it must prioritize people over data. Here’s how to ensure your AI products are genuinely useful to users.

3 Ways to Make AI Work for Customers

1. Target your actual users and find out what they want.
2. Cultivate trust through transparency.
3. Make sure it augments human users.

Building AI for Real Users, Not Hypotheticals

One major pitfall for AI developers is assuming they know their users’ needs without engaging them. Instead, we integrated ourselves into our target audience. User-centric AI development goes beyond surveys; it requires continuous iteration based on real-world interactions. For example, our campus ambassador program allows direct feedback from students, helping us refine our AI solutions.

When students expressed the need for assistance with literature reviews, we developed Scholar Mode, sourcing information from over 200 million academic journals. Similarly, we created Essay Mode to help with reference-backed essay writing after users highlighted this challenge.

Growing Transparency and Trust in AI

Users crave transparency in AI tools, not just accuracy. They want to understand the reasoning behind search results. This means proactively showing users how our AI operates, explaining why certain articles rank higher. Building trust in AI involves clarifying the origin of results and the methodology behind recommendations.

AI Is an Assistant, Not a Replacement

AI should empower users, serving as an extension of human expertise, rather than replacing it. This principle applies across various sectors, including education, customer service, and healthcare. Successful AI programs enhance human judgment instead of attempting to override it.

AI development should be an ongoing dialogue with users to adapt as their needs evolve. The future of AI isn't about the technology itself, but how effectively it serves people. To make AI truly beneficial, we need to prioritize listening to users.