If someone asked you where artificial intelligence could create the greatest value in your organization, how would you answer?
Many leaders immediately begin thinking about software.
They start researching AI platforms, comparing vendors, or asking colleagues what tools they recommend.
While those conversations are understandable, they often happen too soon.
The first question isn't:
“What AI should we buy?”
The first question is:
“What problem are we trying to solve?”
Organizations rarely struggle because they lack technology.
They struggle because work becomes more complicated over time.
Processes evolve. Responsibilities shift. New systems are added while old systems remain. Employees create workarounds to keep things moving.
Information ends up stored in spreadsheets, emails, filing cabinets, whiteboards, notebooks, and software systems that don't communicate with one another.
Eventually, people become so accustomed to these challenges that they stop seeing them as problems.
They become “the way we've always done it.”
The Discover stage is about seeing your organization with fresh eyes.
It is an opportunity to slow down, observe, ask questions, and better understand how work actually gets done.
Look for Frustration Before You Look for AI
One of the easiest ways to identify opportunities is to pay attention to frustration.
Where do employees become discouraged?
Where do customers experience delays?
Where do managers spend time answering the same questions?
Where do projects consistently fall behind schedule?
Where do mistakes occur repeatedly?
Frustration often points directly toward opportunities for improvement.
Sometimes the problem is a broken process.
Sometimes it's poor communication.
Sometimes it's missing information.
Sometimes AI can help.
Sometimes it can't.
The important thing is to understand the problem before searching for a solution.
Organizations that begin with technology often end up trying to force AI into situations where it provides little value.
Organizations that begin with the problem usually discover that the right solution becomes much clearer.
Spend Time Where the Work Happens
One of the most valuable things leaders can do during the Discover stage is simply observe.
Spend time on the manufacturing floor.
Sit beside the customer service representative.
Watch someone prepare a quote.
Observe how new employees are onboarded.
Follow an order from beginning to end.
Walk through the purchasing process.
Listen more than you talk.
Many organizational challenges never appear on reports or dashboards.
They become visible only when you watch people work.
Employees often develop creative ways to overcome inefficient systems.
While those workarounds help keep operations moving, they also hide opportunities for improvement.
When leaders spend time understanding daily work, they begin seeing patterns they hadn't noticed before.
Ask Better Questions
The quality of your AI journey will depend on the quality of the questions you ask.
Instead of asking:
“Where can we use AI?”
Ask:
What consumes the most time each week?
Which tasks do employees dislike because they're repetitive?
Where do errors occur most often?
Which reports take too long to prepare?
What decisions are delayed because information isn't readily available?
Which customers or clients experience unnecessary delays?
What knowledge exists only inside one person's head?
What keeps managers awake at night?
These questions focus attention where it belongs, on improving the organization.
AI becomes part of the solution only after the challenge is clearly understood.
Listen to the People Doing the Work
One of the biggest mistakes organizations make is assuming leadership already knows where improvement is needed.
Leadership understands strategy.
Employees understand reality.
The people closest to the work often recognize inefficiencies long before anyone else.
They know which forms are completed multiple times.
They know which reports are never used.
They know where communication breaks down.
They know which systems are difficult to navigate.
They know which tasks could be completed in minutes if unnecessary steps were eliminated.
Inviting employees into the discovery process does more than generate better ideas.
It builds ownership.
When employees help identify opportunities, they are far more likely to support the changes that follow.
Successful AI adoption is never something done to employees.
It is something built with them.
Document Before You Improve
Organizations are often eager to fix problems immediately.
Resist that temptation.
Before redesigning a workflow or introducing AI, document how the current process actually works.
Map the steps.
Identify who is involved.
Note where information is entered.
Record where delays occur.
Highlight duplicate work.
Capture where decisions are made.
This exercise often reveals opportunities that have nothing to do with AI.
In many cases, simplifying a workflow creates immediate value before any new technology is introduced.
When AI eventually becomes part of the process, it is supporting a workflow that has already been thoughtfully designed.
It is not supporting one that is cluttered with unnecessary complexity.
Discovery Is an Investment, Not a Delay
Some leaders worry that spending time discovering problems slows progress.
The opposite is true.
Discovery prevents organizations from investing time and money solving the wrong problems.
A few weeks spent understanding workflows can save months of frustration during implementation.
More importantly, it helps ensure that AI is introduced where it can create measurable value instead of becoming another technology initiative searching for a purpose.
The organizations that achieve the greatest success with AI don't begin by chasing technology.
They begin by understanding themselves.
That understanding becomes the foundation for every decision that follows.
Moving to the Next Stage
Once you've identified your organization's challenges, documented key workflows, and gained a clearer understanding of where opportunities exist, you're ready for the next step.
Now it's time to determine whether your organization is prepared to act on those opportunities.
In the next chapter, we'll explore Stage Two: Assess, where you'll learn how to evaluate your organization's readiness across leadership, culture, data, governance, workflows, and measurement.
Before launching any AI initiative, it's important to understand not only what you want to improve, but whether your organization has the foundation needed to improve it successfully.