Chapter 2
Human Patterns Behind Process Bottlenecks
Shows why automating a visible bottleneck can preserve the human pattern that produced it.
AI and organizational behavior concept
How Can Organizations Avoid Automating Existing Dysfunction?
Direct answer
Organizations avoid automating dysfunction by investigating the real behavior surrounding a process before scaling it. They compare documentation with communication, exceptions, delays, and workarounds; ask why those adaptations exist; and resolve unclear ownership or trust first. Otherwise, AI can make a flawed operating pattern faster, wider, and harder to see.
In the book
Where this concept is developed
This page offers a concise orientation. An Inbox Between Us develops the idea in greater depth through the following parts of the book, where it is connected to the wider argument about AI, organizational behavior, and modern work.
Chapter 7
The Real Cost of Chaos
Traces what fragmented work, delayed decisions, and chronic ambiguity cost before any attempt is made to scale them.
Chapter 9
AI Failure Isn’t About AI
Explains how AI initiatives inherit misunderstood processes, behaviors, and readiness problems long before deployment.
Automation preserves assumptions
Every automated workflow contains assumptions about what information is sufficient, who can decide, and which variation matters. If those assumptions reflect an imagined process, the implementation may remove the very adaptations employees use to keep outcomes safe.
Speed can then amplify rework, conflict, and risk. The organization experiences more output without greater clarity.
Slow down at the discovery point
Slowing down does not mean resisting AI. It means spending enough time to discover the system being changed. Leaders should identify recurring exceptions, ask the people closest to them what purpose they serve, and decide which behavior should be preserved, redesigned, or stopped.
The fastest implementation is not the one that launches first. It is the one that avoids rebuilding the same problem at machine speed.
A new solution can become another workaround
Tim’s episode makes the dysfunction risk concrete. People already have ways of getting work done, even when those ways never appear officially. If leaders ignore that reality, an AI project may not displace the workaround. It may join the workaround and make the process more layered than before.
Industrializing dysfunction can therefore look surprisingly ordinary: a new AI tool, the old spreadsheet, the same side conversation, and a team still doing invisible coordination to make the documented process work.
Dysfunction scales through culture
Build a Vibrant Culture makes the warning cultural: AI will not automatically save the day for an unhealthy organization. Because AI industrializes human behavior, it can also industrialize the dysfunction already present in team dynamics, communication habits, and unclear accountability.
The answer is not to abandon AI. It is to return to discovery, understand the organization as it behaves, and involve the people who understand culture before automating across unresolved patterns.
Use AI to discover where AI is unnecessary
ProductCamp Conversations offers a second protection against industrializing dysfunction: use AI to figure out how not to use AI. A model can help expose the ambiguous part of a problem, but the repeatable parts may be better served by explicit rules, conventional software, or a clarified human decision.
This is not an anti-AI position. It keeps probabilistic technology focused on the uncertainty it is suited to handle while making stable steps cheaper, more predictable, and easier for a team to maintain.
Operational example
A company automates contract routing based on the official approval chain. It later discovers employees had been performing informal risk checks before routing. The automation did not remove the risk; it removed the behavior that was containing it.
Further conversations and perspectives
These appearances extend the book’s argument through questions, examples, and perspectives raised in conversation.
ProductCamp Conversations →
Dave observes that AI can paper over and exacerbate messy processes; David answers with a product test—use AI to discover where AI is unnecessary and reserve it for genuine ambiguity.
The Expert Authority Coach Podcast
David states the mechanism directly: AI industrializes human behavior, so introducing it into a dysfunctional organization industrializes the dysfunction already present.
Future Factory
The phrase industrializing dysfunction captures the risk of scaling behavior before understanding it.
People Business
The interview emphasizes discovery before redesigning work around AI.
Tim Stating the Obvious →
The episode warns that AI can become another layer in the workaround when organizations skip discovery of actual work.
Build a Vibrant Culture
The conversation warns that AI will industrialize dysfunction when organizations skip self-awareness and ignore the human behaviors behind culture.
Finding Freedom
The episode warns that without self-discovery, AI may accelerate work that was never fully understood.
Follow The Brand by Grant McGaugh →
David describes AI as a way to industrialize human behavior. Without organizational self-awareness, the technology can scale the same fear, overload, inconsistent communication, and informal workarounds already shaping the business.
On Brand with Nick Westergaard →
The episode warns that AI industrializes human behavior; pushing adoption before understanding organizational behavior can industrialize dysfunction instead.
Questions this concept helps answer
- What does industrializing dysfunction mean?
- How can AI make a broken process worse?
- Which employees should participate in workflow discovery?
- When should an organization slow an AI implementation?
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