For the last few years, the business world has been asking a simple question:
"Should we be using AI?"
Today, that question feels largely settled. AI is no longer a futuristic concept. It's integrated into our daily lives, embedded within business applications, and rapidly becoming a standard part of how work gets done.
The challenge facing organizations today is no longer whether they should adopt AI. The challenge is figuring out how to use it strategically.
Many organizations are still approaching AI from an adoption mindset:
While these are reasonable questions, they often skip an important step - they start with the technology. A strategic approach starts somewhere else. It begins by understanding the business problem that needs to be solved.
I've observed a familiar pattern as organizations begin exploring how to incorporate AI. They decide they need AI because competitors are using it, employees are asking about it, or industry headlines create a sense of urgency.
The result is often:
"Let's find somewhere to use AI."
This may sound logical, but it will create challenges. When organizations start with the tool, they often discover that their biggest barriers aren't technological at all - they're operational. Problems often faced are:
AI doesn't fix the problem - it exposes it
One of the biggest misconceptions surrounding AI is that it can do anything to include compensate for process inefficiencies. In reality, AI often magnifies them. Imagine a workflow that already contains unnecessary steps, duplicative steps, communication gaps, or unclear roles and responsibilities.
Adding AI may make individual tasks faster, but it doesn't eliminate the underlying inefficiency. In fact, it may accelerate a flawed process.
A phrase I've come back to repeatedly is:
A bad process with AI is still a bad process. It just happens faster.
Technology has taught us this lesson for decades - AI simply making it more visible.
Organizations that rush to implement AI without understanding how work actually flows through their business often find themselves disappointed with the results, not because the technology failed; instead, because the process was never optimized in the first place.
Before implementing AI, organizations should have a clear understanding of how work gets done today.
That means asking those tough questions that should always be asked:
These questions aren't new. Business leaders have been asking them for decades. What is new is the opportunity AI creates once those answers become clear. When you understand your processes, identifying AI opportunities becomes significantly easier. Instead of forcing AI into the business, you can strategically place it where it creates measurable impact.
The companies generating meaningful value from AI aren't necessarily adopting the most tools.They're identifying specific business challenges and determining whether AI can help address them.
Their approach often looks like this:
Simple doesn't mean easy.
But it is effective. Rather than chasing every new AI platform, these organizations focus on solving business problems. That's where the real value is created.
As leaders, I believe we need to move the conversation beyond adoption. The question is no longer: "Should we use AI?"
The more important questions are:
Those are the strategic questions we should be asking. And ultimately, strategy - not technology - is what drives results.
AI has quickly become probably the most powerful tool available to the every day people, companies and organizations to date, but tools alone don't create transformation - understanding your business does.
Those that gain the most value from AI won't be the ones that adopt it first; instead, it will be the ones that understand their processes well enough to know exactly where AI belongs.
The next phase of AI won't be defined by adoption.
It will be defined by strategy.