What Fragmentation Costs You

The number that isn't on your dashboard

You can name your AI adoption rate. You can name your license count. You can list every pilot running across the org right now. But if someone asked what it costs you that all of those people and tools are pulling from different, disconnected sources of information, you couldn't give them a number.

That's not because AI isn't working. Individually, it clearly is — people are faster. The problem is that it's working in fifty separate places, and none of it adds up to anything the company can point to.

We built a calculator to put a number on it. Type in a few facts about your org, and it shows you what fragmentation is costing you today, and what that's worth to bring your AI workflows into a single surface.

• Identify the true cost of fragmentation off of one workflow
• Get a real number that helps your finance team understand the ROI of a single source of truth
• Put a true number on what a single source of record saves your company

Here’s how to use our calculator and where the costs come from

Retrieval: The cost you already know about

Everyone knows people lose time hunting for the current, correct version of something — which spreadsheet is the real one, where is the agent’s work from one week ago, which draft is live? Here you’ll quantify how much time is lost looking for the source of truth.

A 2022 Forrester study commissioned by Airtable found that people spend 30% of their week, roughly 12 hours, looking for information. Our calculator defaults to 5. Start there and adjust the number up if your own experience says otherwise.

Reconciliation: The cost of finding it twice

Retrieval is the cost of finding information. Reconciliation is the cost of finding it twice and getting two different answers.

You know the scene: the CRM says one number, the finance sheet says another, and three people spend part of a meeting deciding which one is real. It happens often enough that in a 2026 Wakefield Research survey of 1,000 senior technology leaders, commissioned by Teradata, 42% named data scattered across systems that can't be connected as one of their biggest barriers.

Searching and settling disagreements between systems feel like the same problem. They aren't. One is the cost of looking. The other is the cost of not trusting what you found. Estimate how many hours each person in your organization roughly spend on reconciliation.

Re-briefing: The cost of gathering the same inputs repeatedly

Re-briefing is explaining to an AI tool — again — what your pipeline stages mean. Re-pasting the same three documents into a new chat because the last one doesn't remember. Asking a teammate “what did the agent assume when it made this?” and nobody knows.

Here's what makes it different from the other three costs: it grows as you adopt more AI. More tools and more sessions means more re-explaining, not less. That's why buying more AI licenses hasn't felt like getting proportionally more leverage — some of the gain gets spent right back on re-explaining, every single week. And no dashboard tracks it, because nobody has ever had a category for it.

In the 2026 Wakefield Research survey of 1,000 senior technology leaders, commissioned by Teradata, 77% said 20% or less of their company's information is described well enough for AI tools to use reliably. Most AI workflows die when the session closes — and every time one does, someone has to start over. Estimate how many hours each person in your organization spend rebuilding the memory and inputs for quality AI outputs.

Rework: The cost of building on a wrong number

This is the hours spent finding and fixing work that was built on an outdated or incorrect number — not the cost of the bad decision that got made in the meantime, just the cleanup. Pricing the fallout of a bad decision is guesswork, so we leave it out.

Almost nobody measures this today, which is exactly the argument for writing it down. Even a rough count beats the current count, which is zero. And the underlying problem is well documented: in the same 2026 Wakefield Research survey commissioned by Teradata, 51% of technology leaders cited the accuracy and reliability of AI outputs as a significant barrier to rolling AI out further. Instead of hours, quantify this in number of incidents per month per person on the team.

The discount: Why we cut our own number

Getting hours back is not the same as getting money back. If someone gets four hours back on a Tuesday, the company doesn't automatically get four hours of extra output — some of it becomes a longer lunch, some becomes work that didn't need doing anyway.

So the calculator only claims 40% of recovered time turns into real value. Set that number with your own finance partner, and set it lower than feels good. Cutting your own number before finance does is what makes the rest of the math hold up in the room.

What to run on the calculator

Pick one workflow you own and count the systems it touches. Then follow one real instance of it end to end with a stopwatch, tagging each delay as retrieval, reconciliation, re-briefing, or rework.

That gives you a bottom-up number for one workflow, built from your own data. A bottom-up number you built yourself beats any top-down estimate when you have to defend it in a room.

Where Airtable fits

The four costs above are all symptoms of one condition: people and AI tools working from different copies of the truth. That's the condition a shared system is built to end — everyone and everything reading and writing the same live data, so retrieval, reconciliation, and re-briefing stop being three separate jobs and start being one solved problem when you’re using Airtable as your system of record.

Download the calculator and see your number