Four years Arinti – Four lessons from four years of AI projects
March 1st, 2021An AI project always comes with a learning curve. Here are the four most important lessons we've learned to turn AI projects into successes.
Be open to change — and communicate transparently
Implementing AI always comes with change management. Transparency should be the top priority: explain what AI does, how it operates, how it's trained, and where it gets its information. At Unilever, we implemented AI using 10 years of data. Project lead Robin made it his duty to spread AI awareness within the company.
Account for hidden costs
In 99% of AI projects, you'll pile on extra costs — mostly the time different internal stakeholders invest. IT provides system access, domain experts explain the business, ambassadors defend the project internally, and employees learn to work with AI. Time is your most precious resource.
Empower everyone — inside and outside
AI empowerment needs to be nurtured bottom-up. Get IT involved from the start — they hold the key to important data. Don't forget external stakeholders either. For Socialistische Mutualiteiten's chatbot for pregnant women, we organised workshops with moms-to-be to get their input.
Define your goals before you start
No goal = no viable AI project. Without an identified goal, projects rarely go into production. Partena Professional came to us with a clear goal: saving time and automating expert HR services. Less than three months after PoC, chatbot Louise became an essential tool for 900 payroll consultants.
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