Your AI Strategy Needs a Reality Check
AI is in your inbox, your social feeds, your software, and it’s probably already worked its way into your personal day-to-day. There’s a growing pressure to adopt it quickly, to experiment, to stay ahead. No one wants to be the last to figure it out.
But what if the bigger risk is moving too fast without a plan?
At our latest Intersessions, B2B tech strategist Chris Theisen offered a different perspective: before you double down on AI, your strategy might need a little sobering up.
AI Isn’t Magic
There’s a tendency to talk about AI like it’s a shortcut to better work. Something that can instantly generate content and solve your long-standing business challenges with the push of a button.
A more accurate way to think about AI is as a highly capable assistant. As Chris put it during the session, “the best way to describe it is really that it’s like your highest paid intern.” It can move quickly and produce a lot, but only when it’s given the right direction. Without that, it will produce an output, but not necessarily the kind you want.
That distinction is important. While the tools feel powerful, they’re not inherently strategic. They rely on you to provide the context and guardrails.
The Foundation
One of the most important ideas from the session was around AI amplifying your problems.
If your data is disorganized, your processes are unclear, or your goals are undefined, adding AI into the mix won’t clean things up. It will just help you move faster in the wrong direction.
For many businesses, this is where things start to break down. It’s easy to get excited about new tools, to test what’s possible, to try and automate pieces of the workflow. But without a strong foundation underneath, those efforts rarely lead to meaningful results.
The businesses seeing real value from AI have taken the time to organize their systems, define their workflows, and understand what they’re trying to achieve.
We’ve Been Here Before
Early social media followed a similar pattern. Businesses rushed to create accounts, post regularly, and “be active” because the platforms were new and accessible. But many did so without a clear strategy to sustain the effort.
The result was a lot of time spent with very little return. AI is following a similar trajectory. The barrier to entry is low, the possibilities feel endless, and the messaging around it often makes it sound easier than it is. Like social media, the real value comes from how intentionally it’s used.
Another challenge right now is the sheer volume of tools entering the market.
It seems like every platform has added “AI” to its feature list, and every new product promises to transform the way you work. Not all of these tools are as advanced, or as necessary, as they claim to be.
In many cases, companies are layering AI into existing systems or repackaging other technologies under a new label. That doesn’t make them inherently bad, but it does make it more important to evaluate them carefully.
Start With What You’re Trying to Solve
Before bringing AI into your workflow, it helps to take a step back and define your starting point.
What are you trying to improve?
For some teams, the opportunity lies in augmentation and using AI to support the work already being done. This might look like speeding up research, generating first drafts, or helping teams get past the blank page more quickly.
For others, it may be about automation by identifying repetitive, time-consuming tasks that could be handled more efficiently with the right systems in place.
Both approaches have value, but they require different levels of readiness. And for most organizations, starting with augmentation tends to be the more practical and effective path.
In the session, Chris pointed to a common imbalance: companies are investing heavily in tools, but not enough in their people or their processes. He instead emphasized a 90/10 shift towardpeople and processes first, with technology layered in later. So before adding anything new to your tech stack, start by looking inward.
Document your processes. What does a typical task look like from start to finish? Where are the slow points? Where do things get repeated or handed off? Where does information get lost or duplicated?
From there, patterns start to emerge. And once you understand those patterns, it becomes much easier to identify where AI can add value for your team.
It’s not the flashiest starting point. It doesn’t come with a demo or a free trial. But it’s the work that makes everything else more effective.
And if you’re looking for a simple way to begin, it can be as straightforward as this:
Write down one recurring task you do each week
Break it into steps
Identify what feels manual, repetitive, or time-consuming
Then explore where AI could assist
The Bottom Line
AI is going to continue shaping how we work. That much is certain.
But the businesses that benefit most won’t be the ones chasing every new tool or trend. They’ll be the ones that take the time to build a strong foundation, define clear goals, and use AI as a way to enhance, not replace, the work they’re already doing well.
Or, as Chris Theisen put it during the session:
“It’s not magic. It takes discipline.”
ICYMI: If you'd like to dive deeper into the discussion, we recorded the session for you to watch back.