One of the questions we get asked often is, “Is our organization ready for AI?”
It’s a reasonable question. There’s no shortage of information about what AI can do, and the technology is evolving so quickly that it’s difficult to know where to begin. You may already have employees experimenting with ChatGPT or other AI tools, while others aren’t using them at all. So how do you figure out where to start?
At HIA, we offer AI Readiness Assessments that help organizations answer that question in detail. But there are a few things you can do yourself before engaging a consulting firm, and they’re probably simpler than you think.
Start with the work, not the technology
One of the biggest barriers to successful AI adoption that we see is organizations struggling to identify what they actually want AI to do. Go beyond saying, “We need to start using AI” and figure out exactly what you want it to help with.
AI is capable of doing an enormous number of things, probably far more than most people realize. But that doesn’t mean it belongs everywhere. And introducing it into a process that doesn’t need improving isn’t going to accomplish much, other than giving everyone another tool to learn.
Instead, start by looking at the work your team is already doing. What takes longer than it should? What causes frustration? Where are people spending hours on tasks that seem like they should be easier? What important work isn’t getting done because nobody has enough time? Those are the places I’d start looking.
Once people see AI helping them solve problems they already have, something interesting happens. They start recognizing other opportunities on their own. They begin thinking about their work differently, and AI becomes something they know how to use rather than something leadership keeps encouraging them to try. That’s where meaningful adoption begins.
So, what kinds of work should you look for?
I’d start by looking for two characteristics.
1. Work that follows a reasonably repeatable process.
I’m not necessarily talking about software workflows or traditional automation. I’m talking about the messy, everyday work that happens in most organizations. Things like developing proposals, preparing social media content, responding to purchase order requests, creating monthly client summaries, or pulling together reports for leadership.
These activities aren’t always identical, but they usually follow a recognizable sequence. Someone gathers information, organizes it, develops something, reviews it, makes changes, and eventually produces a finished result.
AI can be very helpful with different parts of that work. It might help gather and organize information, develop a first draft, identify missing details, or evaluate something before it goes to a client.
And don’t overlook work that requires judgment. For example, preparing a recommendation for leadership may not be repetitive in the traditional sense, but AI can help evaluate alternatives, challenge assumptions, and identify considerations that might otherwise be missed.
2. Work that your organization understands well enough to explain.
This one is particularly important, and it’s something organizations sometimes overlook. How well do you actually understand the process you’re trying to improve? Can you explain what needs to happen, in what order, who is responsible, what information is needed, and what a successful result should look like?
You don’t necessarily need a beautiful process map or a 40-page procedure manual. But someone should be able to walk through the work and explain how it’s supposed to happen.
For example, if you’re developing proposals, where does the source information come from? Who determines the strategy? What has to be reviewed? Who approves the final product? And what separates a strong proposal from a mediocre one?
Those details matter because AI needs direction. It needs to understand what you’re trying to accomplish and what standards you expect it to meet. AI can do some remarkable things, but figuring out how your business SHOULD operate isn’t something I’d recommend delegating to it.
If your existing process is confusing, inconsistent, or poorly understood, adding AI may simply help you produce confusion at a much higher speed. Which, presumably, isn’t your objective.
Start small. Seriously.
Once you begin looking at your organization’s work this way, you’ll probably come up with quite a few opportunities. And that’s where I’d encourage a little restraint. Don’t create a list of 20 AI projects and attempt to tackle them all at once. Start with three to five.
Then look at which ones are taking your team the most time, which are relatively easy to understand, and which involve the fewest systems or complicated integrations. I’d also consider how easily someone can review the results and whether there are any meaningful risks associated with getting something wrong.
For your first projects, you want something valuable enough to make a difference but manageable enough that your team can learn without turning the whole thing into a six-month technology initiative. And remember, the first project doesn’t have to be particularly sophisticated. If AI can help your team cut several hours out of preparing a monthly report while maintaining or improving its quality, that’s a worthwhile result.
More importantly, your team will begin understanding how AI fits into the work they already know. That experience will help them recognize other opportunities, ask better questions, and become more comfortable using AI in ways that are genuinely useful.
What happens next?
If you can identify three to five opportunities like these, you’re in a much better position to have a productive conversation about bringing AI into your organization. You don’t need to have all the answers, and you certainly don’t need to know which AI tools or platforms will be involved. That’s part of what a good advisor can help you determine.
At Hybrid Intelligence Advisors, we begin by understanding how your organization works, what you’re trying to accomplish, and where the greatest opportunities exist. From there, we can help determine whether AI makes sense, what it might take to implement, and which opportunities are actually worth pursuing.
You can learn more about our AI Readiness Assessment on our website. And in the meantime, I’d encourage you to ask your team one simple question: “What’s something we do regularly that takes far more time or effort than it should?” You may be surprised by the answers. And you may find that you’re much closer to being ready for AI than you thought.