3.1 Canals vs. Railroads: Why Agentic AI Fails When Viewed as Faster RPA
Blog ID: 3.1 Canals V's Railroads
Author: James Hewitt
Date: 15-Jan-26
Audience: CHRO, Head of Talent Acquisition, TA Operations & Strategy

Image 2: Map of Edo era canal network in Tokyo, Japan c1850.
We have arrived at
Chapter 3: Transformation. We have our
Players, our
Playbook, and our
Infrastructure. But before we deploy the most advanced
Player—the
Agentic AI—we must perform a critical mental upgrade.
The greatest risk to your Ecosystem investment isn't the technology failing; it’s you applying the wrong mental model to the technology’s success.
As Sangeet Paul Choudary writes, in the 19th century, canals were the height of efficiency. When railroads emerged, leaders saw them as "faster canals"—a better way to execute the same job. They failed to see that railroads demanded a new mindset:
system design and coordination. To run trains, the industry had to invent standardised time zones, collapsing vast distances and creating new national markets.
The problem with Agentic AI in 2026 is the same: experts trained in Robotic Process Automation (RPA) are treating this systemic technology as "faster RPA". They see a better way to automate a task (Canal Logic) when the true value lies in reinventing the entire workflow around coordination and governance (Railroad Logic).
The market data proves this failure. While
87% of companies have adopted AI for simple tasks (Canal Logic), only
11% are doing deep, strategic integration. This gap is why satisfaction with AI tools is low—leaders are digging canals in an age that demands railroads.

This "Canal Logic" fails in two ways:
- It Automates Workflows Instead of Eliminating Them. RPA taught us to automate steps. Agentic AI makes the entire linear sequence obsolete. A "Canal" approach automates sending a resume to an HM. A "Railroad" approach uses an Agentic AI to score the candidate against the Kickoff Meeting (Blog 2.1) criteria and schedule them directly for an interview, eliminating the review workflow entirely.
- It Focuses on Execution at the Cost of Governance.
The value of
Agentic AI is not how fast it executes a task, but how well it coordinates with the
Playbook. Your
Kickoff Meeting is the "standardised time zone". Your human
Player's role in
Data Competency (Blog 2.5) is the
Governance that makes the whole system safe and effective.
The
Railroad Mindset means you must now deploy your
Infrastructure as a coordinated system.
The first step is to fuel it. In
Blog 3.2, we detail how to deploy
Agentic AI to
Activate Your 1st Party (Proprietary) Data.











