BlogsAI Strategy Is Shifting—And It Starts with the Paper on Your Desk
AI Strategy Is Shifting—And It Starts with the Paper on Your Desk
Focus on improving legacy processes before adopting new AI tools to maximize ROI. Map workflows, identify inefficiencies, and automate to unlock the true potential of AI for operational efficiency.
AI Strategy Is Shifting—And It Starts with the Paper on Your Desk
What Leaders Need to Know Before They Chase the Next Big Tool
Every day I speak with business leaders who are wrestling with the same thing:
How should our strategy evolve as AI becomes more accessible, more hyped, and more complex?
And while some organizations are deploying copilots, testing agents, or exploring next-gen LLMs, many are missing what I believe is the most important—and most overlooked—starting point.
It’s not the model. It’s the process.
Start With the Process—Not the Platform
Before you chase the next AI tool, I always ask this question:
“If your goal is to move faster, why are you investing in more technology before addressing the inefficiencies already baked into your legacy processes?”
That may sound obvious—but here’s the truth:
The fastest path to AI ROI is often hiding in the process you’ve ignored for a decade.
Take a single piece of paper that moves through your organization.
It could be:
An accounts payable form
A purchase order
A sales order
An inventory reconciliation
A compliance report
Now ask:
How many systems does it touch?
How many people are involved?
Where does it stall?
What do you assume works that actually doesn’t?
Where are the handoffs unclear or inconsistent?
This is process intelligence.
And while it might sound complex, it’s remarkably simple.
Map it once—and you’re 80% of the way to automating it.
Process Intelligence: The Real Low-Hanging Fruit
I’m seeing leaders overcomplicate AI when the real unlock is much more basic:
Map your manual workflows.
Identify redundant handoffs.
Spot the gaps where data disappears.
Uncover the steps no one owns.
Surface the exceptions that eat your time.
Once you lay this out, you now have the foundation to apply:
Robotic Process Automation (RPA)
Robotic Process Automation (RPA)
Document Intelligence
Workflow Orchestration
And eventually—AI agents that work alongside your team
You don’t have to start with a transformer model.
You can start with a PDF.
What the Most Effective Leaders Are Doing Now
The organizations making real progress aren’t chasing the headline.
They’re asking:
What process is costing us the most time, friction, or delay?
Can we measure how long it takes and where it breaks?
What would change if it ran autonomously?
And what decisions could we make if the data behind it was surfaced in real-time?
Once they answer that, AI isn’t hypothetical anymore.
It’s operational.
The Opportunity Ahead: From Workflow to Intelligence
Once your process is clean—digitized, automated, and connected—you unlock the real power of AI:
On-demand intelligence.
You can now deploy an AI agent that:
Monitors the process
Flags exceptions in real-time
Summarizes what’s happening
Recommends what to do next
Connects the dots across silos
That’s not the future.
That’s what’s possible now—if you do the foundational work first.
You Don’t Need a 3-Year AI Roadmap. You Need a 3-Day Process Map.
Before you invest in another platform, ask yourself:
What’s the slowest, most manual, most painful process in your business?
Fix that.
Automate it.
Then amplify it with intelligence.
AI doesn’t transform organizations that don’t understand their own workflows.
But for the ones who do—it accelerates everything.
Leadership is crucial for effectively utilizing AI tools like Microsoft Copilot; organizations should focus on execution, speed, and clarity rather than just strategy. Identify time losses and integrate AI into broken processes to enhance productivity and value creation.
Switching to JSON prompting enhances clarity, structure, and control in AI interactions, reducing ambiguity and improving output consistency, making it ideal for scalable workflows and team integrations.
Generative AI is rapidly being adopted in organizations, necessitating a clear Acceptable Use Policy that defines user roles, authorized tools, data input restrictions, output review processes, and monitoring strategies to mitigate risks while fostering responsible innovation. Regular training and feedback loops are essential for embedding governance into workflows.
Get Weekly Tech Plays Straight to Your Inbox
Actionable insights, productivity hacks, leadership strategies, and technology trends—curated for visionary leaders ready to level up.