Have you encountered any challenges in terms of user understanding or acceptance of AI?

For sure. There are certain things AI does really well, and others that humans or traditional deterministic algorithms do better. That sounds obvious, but there's some nuance here that users often miss.

At Barracuda, we were the first major email security vendor to market with an AI based approach to stopping phishing and impersonation attacks. We invested a tremendous amount of time training the models to spot attacks that traditional solutions missed. We didn't train those models to catch run of the mill spam (the "easy" stuff) because there are mature solutions that catch those attacks, including others in our portfolio. What we didn't anticipate is that missing the "easy" stuff that we didn't train the models to detect undermined confidence in our ability to catch the stuff we were actually trying to detect. Users assumed that if we trained the models to catch one type of attack, it should automatically catch spam. What customers didn't appreciate is that AI doesn't work that way.

It just underscores the need to be vigilant and engage with customers as often as possible - their perception is reality and you'll need to adjust to it, not the other way around.

Yes, encountering challenges related to user understanding or acceptance of AI is quite common. Some of the challenges I've encountered include:

1. Lack of Trust

2. Misconceptions and Myths

3. Fear of Job Displacement

4. Bias and Fairness Concerns

5. Privacy and Data Security

6. Cultural and Ethical Considerations