Ways to Build Trust in AI Workflows
While the adoption of artificial intelligence in business processes creates trust issues, usage without human supervision can lead to financial losses.
The use of artificial intelligence in organizational workflows brings efficiency and reliability concerns, while a lack of human oversight can lead to financial damage, as seen in the Air Canada case. Five practical steps stand out for building trust in AI processes.
Explaining AI Integration
The biggest mistake organizations frequently make is blindly accepting artificial intelligence solutions without understanding them or rejecting them entirely. This situation leads to a decrease in trust in the processes.
Maintaining Audit Trails
Project teams and developers can maintain a robust audit trail to make it easier to explain business processes and artificial intelligence interventions. These records should be visible to employees across all relevant departments.
AI Literacy
Most teams using artificial intelligence assistants keep documentation and automate repetitive tasks; however, the level of literacy regarding how machine learning and natural language processing work is quite low.
Involving Diversity
Artificial intelligence works best when there is diversity in the business process. Diversity in the workflow refers to teams with different expertise and knowledge bases benefiting from AI integration.
Human Intervention
Humans must always be a part of the artificial intelligence loop. Human oversight is essential not just to click accept or run buttons, but to monitor every step of the AI in the workflow.