In the race to adopt artificial intelligence, many organizations are starting in the wrong place. They begin by asking, “What can this technology do?” and then try to retrofit it into their business. But successful AI optimization doesn’t start with a tech demo—it starts with a deep understanding of people and process.
That’s because AI, no matter how powerful, can’t fix a process you don’t know is broken. And it certainly can’t replicate the invisible human effort that’s often propping up inefficient systems behind the scenes.
The Process You See vs. The Process That Works
In every organization, there are two versions of how work gets done: the formal process that’s documented (if at all), and the real process—which often survives because your people are quietly bridging the gaps.
It’s common for frontline staff to create workarounds, catch errors, and smooth over inefficiencies without fanfare. These human patches make the system appear functional. But when you introduce AI without understanding where those gaps exist, you risk automating dysfunction or removing the human “glue” that makes things work.
As technology thought leader Gene Kim puts it: “You can't improve what you can't see. And in many companies, processes have become so reliant on people heroics that leadership doesn’t realize what’s broken until it’s too late.”
People Are Your Innovation Engine
Beyond filling in gaps, your employees are often actively improving processes in small but meaningful ways. They adjust workflows to serve customers better, simplify steps to save time, or find smarter ways to use existing tools. These incremental innovations are often undocumented—but they’re real.
When AI optimization projects start with a tech-first mindset, they often miss these insights. A solution might be technically impressive, but if it doesn’t account for how people actually work, it can be clunky, resisted, or even counterproductive.
That’s why successful AI strategies begin by engaging staff: mapping current-state processes, surfacing informal adaptations, and understanding pain points from the ground up.
Grounding AI in Process First
At Aligned Outcomes, we’ve seen firsthand how AI projects succeed when they start with process clarity and people engagement. A process-first approach to transformation means:
· Identifying which processes are working well and which are being propped up by extra effort.
· Capturing both formal steps and informal fixes.
· Involving the people closest to the work in shaping the future state.
Only then should technology enter the picture—used strategically to solve the right problems, not just to showcase capability.
This principle is echoed by AI leaders like Fei-Fei Li, co-director of Stanford’s Human-Centered AI Institute, who emphasizes that “AI must augment human capability—not ignore or replace it.”
A Smarter Path Forward
AI has enormous potential to streamline work, reduce errors, and improve outcomes. But if you leap to implementation without understanding the human and process landscape, you risk automating the wrong things—or worse, losing what made your operations functional in the first place.
Start with your people. Understand your processes. Then bring in the AI. That’s how you ensure the technology truly works for you—and not the other way around.
References:
Kim, G. (2019). The Unicorn Project.
Li, F-F. (2022). Human-Centered AI. Stanford HAI.
Davenport, T. H., & Ronanki, R. (2018). Artificial Intelligence for the Real World. Harvard Business Review.