How do you expect AI to impact traditional IT roles such as sys admins or network engineers?

We've been cautious with AI, particularly in the healthcare sector. The changes I foresee are more anticipated than currently observed. Many on my team are looking to adapt their skill sets in anticipation of changes. For instance, we're going to need people who can fine-tune language models and look at compliance roles in IT. We're also going to need AI product managers. One of the earliest places we're seeing AI emerge is in predictive modeling and analytics. We're not at a point yet where we're replacing humans with AI. Instead, we're adjusting human skills to leverage AI capabilities. The changes we're seeing are more in the skill sets rather than replacing people.

We're also taking a cautious approach. We're looking at tweaking human skills to leverage AI. As a mid-size manufacturer, it's not prudent for us to develop our own models. We're focusing on how to use what's available safely and how to train our staff. I see an impact on the security side and data loss prevention. I see opportunities in data wrangling and being able to use AI appropriately to get the results we're looking for.

I'm working with my team to foster a culture of curiosity around AI. I envision a future where AI becomes part of your skill set, automating repetitive tasks and providing predictive maintenance of platforms. I'm trying to inspire my team to understand how AI can be incorporated into everything they do. This is particularly important when you consider generative AI and how it's starting to incorporate into workflows. Our goal in a healthcare environment is to provide real-time insights for better patient care. This means AI is coming into the clinical applications and my clinical applications team needs to understand and be able to work with AI.

I'm all in on generative AI and the future of AI, but I question whether AI needs to be baked into everything we do. I think it's causing us delay or keeping us grounded. I'm not sure that needs to be our end state. I'm trying to distill AI into bite-size pieces for quick time to value and momentum.

Organizational responsibilities are changing. AI technologies are normally for very targeted areas. We need to manage how technology is used and understand what's happening under the covers when it comes to data. AI is going to be like electricity at some point - it's there or it's not, but it's how we're interacting with it.