Welcome to Part 4 of our series: Getting Ready for AI.
In our previous posts, we established why store data must shift from static artifacts to dynamic assets, and why your people must be prepared before you touch new technology.
Today, we are tackling the operational engine that connects them: your process.
When retail leaders decide to bring AI into store planning, real estate, or store operations, their first instinct is to try and replicate existing workflows.
The problem? Process documentation of those workflows is often a fairytale.
The Myth of the Theoretical Process
In the real world, human workflows evolve constantly. Frontline teams invent ad-hoc fixes, shortcut bad handoffs, and build manual workarounds just to keep store refreshes and rollouts moving.
As tech veteran Jeremy Culshaw noted during our discussion:
“When you start to uncover and dig up those procedures, guidance, tasks, and activities, you realize they’ve changed so much from the original process that you really have no idea. It looks like a totally different organization.”
Uncovering your “actual as-is” workflow is no longer optional. Hoarding manual workarounds doesn’t build a protective moat around anyone’s job—it simply creates operational drag.
When frontline teams participate in mapping real-world workflows, process discovery becomes your single best tool for building employee buy-in. They aren’t marking themselves for replacement; they are actively co-designing how humans will work alongside AI.
The Firsthand Lesson: What Our Internal AI Test Taught Us
We recently experienced this lesson firsthand at DedON.
We were testing an AI tool to run a legacy human workflow, and we were over 80% of the way through the build.
Then, we paused.
We realized we were working extraordinarily hard just to explain our human process to the machine.
Here is the major red flag: If you have to do mental gymnastics to explain a workflow to an AI model, the problem isn’t the technology—it’s your process.
Manual human workflows rely on unwritten rules, intuitive leaps, and informal conversations to patch over friction. Instead of forcing a bloated process into production, we paused the AI build, went back to the drawing board, and simplified the core human workflow first.
The Architecture: Straight Execution vs. Human Gates
AI does not work like a human, and it shouldn’t be forced to.
To take full advantage of AI, tasks moving from Point A to Point B must be simplified, repeatable, explainable, and driven by crystal-clear decision criteria. This is where the massive time savings live.
- Autonomous Execution: AI should run predictable, day-to-day execution autonomously between defined boundaries.
- Human Decision Gates: Humans step in at critical gates—not to perform manual labor, but to evaluate complex exceptions and make strategic decisions where straight logic isn’t enough.
The 30-Year Shift: AI Amplifies Your History at 100x Speed
We are at a historic turning point, much like the massive migration from paper records to desktop computers.
Over the last 30 years, our economy and the software industry poured enormous resources into one primary task: documenting and encoding processes into software. Software, at its core, is simply documented ways of working.
AI amplifies that entire history. AI essentially allows your process to move at 100x speed.
If you automate a bloated or broken process, you don’t get efficiency. You just get automated chaos.
That is why understanding and simplifying your process today is mandatory. AI can assist you in interviewing teams and analyzing existing documentation, but you cannot skip the foundational step of gaining a crystal-clear understanding of how your organization actually works today.
Taking the time to streamline your core workflows isn’t a delay—it is the non-negotiable step that protects your team and allows AI to help you evolve.
What legacy workflow in your organization needs to be simplified before AI touches it?
The above blog post was taken from a conversation between Stephen Hart (DedON Founder & CEO) Jeremy Culshaw – SignaNorth
j.j.culshaw@signanorth.com
SignaNorth helps mid-market companies turn AI investment into real, measurable business value by starting with people and process, not technology. Their view is simple: AI transformation touches every function in a business but lives in none of them, which is exactly why so many pilots stall. SignaNorth steps in as the one accountable partner who carries a company from strategy through delivery to outcomes a board can see in the numbers, then hands over the playbook because their engagements end when your company can stand on its own. Founded by Jeremy Culshaw, who brings more than two decades of enterprise information management and transformation experience across life sciences, healthcare, and other services, SignaNorth is prepared to discuss what it really takes to get your organization AI-ready.