How are you managing the cultural adjustments needed to prepare your IT department for the integration and oversight of AI?

We are currently working on a change management program which involves an external consultant to guide our company, both IT and business, in this transformation path. We selected 35 "early adopters" from different areas, including IT, to be our copilots and we intend to spread the knowledge and awareness about AI all around the firm. In parallel, I am organizing some special training sessions on security and infrastructure issues only for IT department staff. These sessions will cover topics such as data governance, privacy, ethics, cloud computing, and AI monitoring.

I think many IT organisations are prepared and/or more than capable here... the bigger challenge based on my customer and industry engagements is preparing the business functions

One thing is for sure AI is a great help and time saver for day-to-day tasks but AI can also hallucinate at times and data can not yet be trusted without expert SME review. Accountability and responsibility remain with humans to vet the truth and ensure that sensitive data is protected and used for the benefit of all. Culture should remain one of accountability and responsibility for all data integration and decision outcomes.

I view it as any other new "disruptive" technology that is out there.  There are a lot of buzzwords floating around and it seems everyone wants to tack AI to anything that is helpful, even if it really isn't AI....  The catch for me/us is that it is coming fast and furious across so many platforms.  So, in our case, we took a step back to incorporate an AI policy so we define when and how we can use, for anything new we have a security review and we've defined what can and can't go into some of the AI platforms (proprietary info, etc.).  I've also been in front of it with our organization only so people "slow down" before jumping in.  I'm not against using it, but don't want a side-effect that someone hadn't considered.

We have a number of different things we are doing to try to get ahead and keep ahead of this.  We are approaching it more as an "enterprise digital readiness" initiative.  So the scope is broader than AI, but I feel all could apply to a more AI focused approach.  We have an enterprise-wide communication plan that is fairly generic, but is focused on educating staff on certain terminology, examples, etc. just to keep the conversation top of mind for them.  We will highlight AI models, patient engagement initiatives, etc. with examples that are more relatable to them.  We also have quarterly executive business relationship meetings where we take a topic like AI, Advanced Analytics, Bots, etc. and dive a little deeper, trying to tie more to business value than the technology.  In our Annual Meeting, we held break-out sessions to discuss emerging tech and digital solutions where are had AI specific material to hand out.  For our tech teams, we have obviously gone a couple of levels deeper.  We have had our data scientists hold Q&A sessions, present examples in meetings, etc. intentionally getting the proactive dialogue going...rather than waiting for people to ask questions.  Lastly, we started two different "all tech team" recurring monthly sessions focused on learning and socializing new tech, including AI.  We have one session where its a specific tech topic that someone does a quick intro presentation on and then opens for Q&A.  The second session is what we call "reverse rounding."  Being in healthcare, this is a common concept.  We bring in a front-line user from one of the operational areas and they explain to our whole tech team what a day-in-the-life looks like for them in their role.  This has gotten our team much more in-tune with end users and has increased empathy and meaning in their work.  What we've recently added to that is some prep with that presenter to call out more specifically where the technology our team supports intersects with their job.  We specifically highlight areas where there is new tech, AI, automation, advanced medical tech, etc. so the broader team can see the impact.  Hope this helps.