What tests does a company need to conduct before launching AI?

Before launching an AI system, a company must conduct a series of crucial tests to ensure it functions correctly, safely, and ethically. These tests validate performance, reliability, and adherence to intended purpose prior to deployment.

Essential testing includes functional testing to verify core capabilities against specifications, performance testing under load for scalability and responsiveness, and rigorous security testing to identify vulnerabilities protecting data and models. Fairness and bias testing is critical to uncover and mitigate discriminatory outcomes across user groups. Robust data integrity and quality checks must also be performed, alongside usability testing to assess real-world user interaction.

The sequence typically starts with unit and integration testing, progresses to comprehensive system and non-functional testing (performance, security), and concludes with user acceptance testing. Implementing this structured testing regimen minimizes deployment risks, safeguards against ethical pitfalls and regulatory non-compliance, builds user trust, and ultimately enhances the AI's business value by ensuring reliable and responsible operation.