Why People Resist Embracing AI

Artificial intelligence has created a striking paradox. Consider that in a 2023 Gartner survey, 79% of corporate strategists said that the use of AI, automation, and analytics would be critical to their success over the next two years. But only 20% of them reported using AI in their daily activities.

AI’s success hinges not only on its capabilities, which are becoming more advanced every day, but on people’s willingness to harness them. And as the Gartner findings suggest, AI is not getting great traction with users.  Unfortunately, most people are pessimistic about how it will shape the future.  With such cynicism about AI, getting workers to willingly, eagerly, and thoroughly experiment with it is a daunting task.  The following five reasons behind such resistance.

1. People Believe AI Is Too Opaque.  The machine-learning algorithms underlying many AI tools are inscrutable “black boxes” to users. Their impenetrability frustrates people’s basic desire for knowledge and understanding, especially when their outcomes are uncertain or unexpected.  People tend to think that humans’ decision-making is less of a black box than algorithms’, but that belief is unfounded. Explanations of how AI tools work can increase their acceptance, but not all explanations are effective.  The style of explanations plays a crucial role too.  Essentially, the most convincing explanations are those that articulate the reasons behind the decision made as well as why alternatives were dismissed.  The complexity of an explanation relative to the task’s also matters.
2. People Believe AI Is Emotionless.  Though consumers tend to ascribe some human capabilities to AI tools, they don’t think that machines can experience emotions and therefore are skeptical that AI can accomplish subjective tasks that seem to require emotional capabilities.  Organizations can address this hurdle by framing tasks in objective terms—by focusing on their quantifiable and measurable aspects.
3. People Believe AI Is Too Inflexible.  People generally hold the view that mistakes help humans learn and grow, instead of interpreting errors as a sign of unchangeable defects. But they frequently think AI tools are rigid and not adept at adjusting and evolving—a belief that may stem from past experiences of machines as static devices that carry out limited functions.  Studies have indicated, however, that consumer use of AI output rises when people are told that AI has the capacity for adaptive learning.
4. People Believe AI Is Too Autonomous.  AI tools that can perform tasks without active human input often feel threatening to people. From early on in life humans strive to manage their surroundings to achieve their goals. So they’re naturally reluctant to adopt innovations that seem to reduce their control over a situation.  To increase utilization of AI systems, companies can restore consumers’ sense of agency by having people provide input to the systems (thereby creating what are known as “human-in-the-loop systems”).
5. People Would Rather Have Human Interaction.  Cultural context is most likely an important factor in anti-AI tendencies.

Rather than leaping straight into solution mode, tread carefully. Every AI system, use case, pilot, and full-scale deployment will encounter different barriers. It’s your job as a leader to recognize them and help your customers and employees overcome them.