Recently, I stumbled across a blog that said AI without context is just expensive guesswork. Obviously, that resonated with me — it’s what we’ve been writing about in The Productivity Manifesto — so I read it.
It came from CCNY Inc., a nonprofit based in New York City that supports health and human service agencies with data, analytics, and quality improvement. In their post, they shared the story of an organization that invested millions in AI without seeing any ROI.
After a nine-month study, they arrived at the same conclusion we’ve been championing for years: AI is only as good as your understanding of your business. Without that context — without clarity on your way of working — how could AI possibly deliver meaningful results?
Obviously, most organizations don’t have millions to waste. The good news? If you have Microsoft 365, you already have the technology. What’s missing isn’t the tool — it’s the context. It’s your business context, your documented way of working, that makes AI valuable.
The Illusion of AI Magic
Everywhere you turn, someone is promising that AI will transform your business. Just plug it in, and productivity will skyrocket. The reality is far less glamorous. AI doesn’t come with built-in knowledge of how your organization operates.
Leaders are being told that AI will fix staffing shortages, streamline documentation, and ease compliance burdens. In care settings especially, the pitch is enticing — AI that predicts needs, reduces paperwork, and helps teams do more with less. But if the underlying processes aren’t clear, AI just adds more noise to an already overwhelmed system.
Building the Context AI Needs
If AI is going to work for your organization, it needs more than data — it needs context. That context comes from how your business actually works day to day. Before you dive into AI, there are a few steps every organization should take:
Step 1 – Document Your Core Processes
Don’t let “tribal knowledge” be the only way people know how to work. Write down your most important processes — whether it’s onboarding, scheduling, daily documentation of services, or regulatory reporting — and make them accessible to everyone. This creates a shared understanding and ensures consistency.
Step 2 – Align Your Digital Workspace to Them
AI doesn’t operate on paper files or unspoken knowledge — AI needs digital context. That means moving your people out of inboxes, away from scattered documents, and into shared spaces built to support the way they actually work.
Start by designing a digital workspace that reflects your core processes. For many organizations, Microsoft Teams is a natural choice. Create teams and channels that mirror the stages and steps of a process, using the same language your employees already use. This makes adoption easier because you’re not asking them to learn a new tool, you’re giving them a familiar process in a better environment.
Step 3 – Get Actual Intelligence Before You Go Artificial
As people work inside this digital workspace, you want two important things to happen. First, you start collecting structured data that AI can eventually learn from. Second, you get feedback from employees about how processes actually work in practice, which gives you the insight needed to optimize and prepare for automation and AI.
The key is to be intentional about this feedback loop. Set aside time each week for your teams to discuss issues, surface what’s working and what’s not, and agree on next steps. A simple meeting rhythm, like the L10 format used in EOS, ensures these conversations happen consistently. Real intelligence comes from people who understand the work — and capturing that intelligence is what gives AI the context it needs to truly add value.
Step 4 – Apply Technology Where It Helps the Most
As your people grow into their improved digital workspace and become more comfortable sharing their feedback — which always happens once they feel heard — you’ll have both the data points and the real-world insights to guide your next moves.
That combination shows you what’s working, what isn’t, and where to invest your limited resources of time and money. The goal isn’t to chase every new tool, but to apply technology where it truly helps your most valuable resource: your people.
From Guesswork to Guidance
AI is not the destination — it’s a multiplier. But without context, it multiplies confusion and cost. The organizations that thrive will be the ones who take the time to build clarity first, then let AI accelerate what’s already working.
So before you spend another dollar on the latest AI add-on, ask yourself: have we built the context that AI needs to succeed? If the answer is no, that’s where the real work — and the real opportunity — begins.
