Challenges of Technology and AI

While technology is a powerful ally, its implementation is not without challenges and risks that, if ignored, can lead to even bigger problems.

It is crucial to be aware of these limitations to avoid overdependence and use the tools strategically.

Screening Issues and Overconfidence

A major challenge is the reliability of detection.

Technology tools can generate false positives (flagging a customer as prone to conflict when they are not) or false negatives (failing to detect a problem when one exists).

It is important for professionals to understand the limitations of their technology and not blindly trust it, as human intuition and experience often detect nuances that an algorithm can miss.

Content relevance is another challenge, especially in self-service portals or knowledge bases.

If information is not constantly updated, customers may receive outdated solutions or incorrect, leading to a great deal of frustration.

Risks of Generative AI

Generative AI, such as ChatGPT and other large language models, presents its own challenges.

The first is data privacy.

By feeding an algorithm sensitive company or customer information, there is a risk that that data could be used to train a third-party vendor's AI, potentially compromising security.

Companies need to be cautious about the information they share with these tools.

Another risk is inconsistent tone and language.

An AI-generated response may sound "robotic" or out of place, especially in a conversation that requires a more personal or informal tone.

Finally, and critically, there is the issue of "hallucinations."

Generative AIs are probabilistic models, meaning they can sometimes generate false or incorrect information with great trust.

It is the practitioner's responsibility to verify each factual stateme