What's the biggest misconception or myth about AI infrastructure that you'd like to debunk?

Many users equate AI solely with Generative AI, overlooking the broader scope of AI applications we've been working on, such as RPA. Education is key, and when we established our AI governance committee, we required members to undergo training to understand the risks and opportunities. We're partnering with Innovate US to provide free AI education tailored to local government needs. Our challenge is making this education mandatory, as it's a critical skill set for those involved with data. We're working with HR to incorporate AI understanding into performance reviews, emphasizing that while AI won't necessarily take jobs, those who understand it will have a competitive edge.

The misconceptions we've encountered include the belief that AI is cheap and quick to develop. As part of our digital transformation program, we've implemented digital training for all employees, including AI education. While this has helped dispel some myths, it's clear that AI development is neither fast nor inexpensive. Education is crucial to overcoming these misconceptions.

Many people, including those in executive leadership, don't fully grasp what AI is, its capabilities, or the importance of investing in it. This lack of understanding extends to cloud costs and the return on investment. While I can't pinpoint a specific myth, there's a significant knowledge gap that we're addressing internally. We're working on foundational education for everyone in the company, creating learning tracks to help employees understand AI and recognize opportunities for innovation.