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Stickiness varies with different verticals. For example, government is a very sticky vertical. You're locked in contracts, and although there's always a way for the government to exit a contract, it's an extreme situation. In my 10 years of experience in government, I've never seen a vendor's contract ceased unless there's a party switch and a significant part of the government wants to reduce operations or headcount. Otherwise, government is sticky due to the nature of government and contracts. Enterprise Asset Management requires a lot of time, effort, and money to implement. Once you're rolling with them, exiting would cost even more money. It's a risk versus reward mindset we always discuss. In more transactional companies, like not-for-profits, where funds ebb and flow, they're not as sticky because of a transactional mindset. You keep them as long as you can.
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In summary, governments, at least legal defense governments, are not yet embracing AI as one might assume. They might have chatbots or copilots, but beyond that, I'm not aware of any government companies in my region with a policy embracing AI. Defense is similar, as it's an emerging technology, and these sectors typically have a lower risk appetite. They are cautious about adopting new technologies for existing customers. Startups are different, but we don't compete with them or have an interest in that. It's a bit complicated, I think.
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Absolutely, 100%. That was the reason I felt so nervous when I was a vertical manager. This is an emerging technology getting a lot of press, and there's a lot of misinformation out there about what AI can do for you and how mature it is. It's only when you start experimenting with it, working with it, and trying to implement it in business for proof of concept that you understand its capabilities. In government defense, where I often work, we focus on proof of concept. If we tick the boxes from what we agreed on, then we'll take the licensing. It was very difficult to ignore AI, but in those verticals, a more conservative mindset prevailed. As I mentioned, there was a risk-averse outlook, and people weren't ready to take that leap. Outside of basic AI introductions, like those built into Canva, which help you create images, or Copilot, which was essentially a glorified SharePoint indexation machine learning algorithm, there wasn't much interest. The risk versus reward wasn't appealing because they felt they already had mature products offering value. So, there was pushback on the value conversation.
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