A caveat before we dig into some top-level points from the webinar (which you can see in its entirety below): Hintze has already gone on record on AI’s current state. He’s pointed out that AI in the first quarter of the 21st century is the most primitive it will ever be. Hintze likens our current experience to someone logging on to AOL in 1990-something, unaware that we’ll all have broadband on mobile phones in a few short years.

Having said that, what AI has achieved to this point is revolutionary. Early adopters — especially when it comes to generative AI — have skewed younger, and with that, a lot of thorny issues have appeared (just ask any college prof who’s stumbled across an AI-generated student essay). On the upside, some of the early worries that surround the tech have begun to fade as older users start to understand how AI can assist — and not replace — them.

There are challenges, but they can be overcome.

Worries pop up around confidentiality, especially as AI develops LLMs (Large Language Models) that can carry on a conversation, not just respond with an action to a prompt. “We've seen customers wrestle with this in a variety of different ways, but some of those things include access to private and confidential data,” says Hintze. “How do you make sure that the info they’re providing to the tech remains private and confidential? How do you grant access to individual users, and how do they gain access to it in other places?”

There’s also the notion of “who gets what,” notes Hintze: “How can you also deliver a vertically focused application of AI to help someone do a specific job? There are different needs within a marketing department versus a tech support department versus an engineering department.”

Corrigan agrees: “Let's look at ‘a day in the life’ of the user and give the right tools to the people in the right places.” However, those tools can be complex, and she’s keenly aware of that. “To me right now, it's all about training and adoption,” she says. “It's all good if you enable people and give them the license, but if they don't know actually how to use it, it's useless. I had early access, but I'd say it took me at least six months to feel like using it properly was ingrained in my everyday tasks.

“It takes effort, and it takes that mindset that’s committed to growth — so it's a company culture change as well, in my opinion.”

It’s not as scary as some have made it out to be.

To really understand what Microsoft is trying to achieve, Corrigan adopts ways to ease people into using AI-driven tools. “We have newsletters every week that we post on LinkedIn — we try to break it down into bite-size pieces. A four-hour training is not something anybody enjoys, but if you follow me on LinkedIn, I’ll post something like, ‘Hey, do you want to learn how to create your own emoji? Cool, let's show you how to do that fun little thing.’” That’s how the company goes about creating AI evangelists.

Corrigan then gives an example of a radiologist who had to deliver a PowerPoint® presentation. The doctor had attended a conference, then used AI to translate a series of notes from the case studies she’d heard there and turn them into slides for her colleagues. As Kaye points out, that PPT would be useless without the doctor’s knowledge and skills as a presenter, so AI acted as a timesaving assistant in this instance.

Hintze agrees. “I think that as you embrace it and experiment with it, it actually removes a lot of the monkeys on your back about getting work done so you can get to the parts where you add real value and you're excited. There've been a number of times when I've used it to start the outline of a presentation. That first step is always such a drag for me, and I always put it off to the last minute. By using AI to build that outline, I moved right into that creative phase, and it made it a better product because it took that boring work off my plate so I could focus on the more important stuff.”