3 Ways AI Can Free Organizations from Legacy Workflows

2026-05-07 · Source: Feeds - HBR.org · Field: Business & Management — Corporate Strategy & Leadership, Operations & Process Management, Marketing, Branding & Advertising · Depth: Fundamental Awareness, medium

Summary

Organizations often struggle with outdated workflows, metrics, and assumptions, which hinder competitiveness more than a lack of new capabilities. This phenomenon, termed "organizational forgetting," is frequently overlooked despite the increasing influence of AI. The article, published on May 7, 2026, by Graham Kenny and Ganna Pogrebna, outlines three key organizational constraints stemming from a reluctance to abandon the past. It demonstrates how AI can objectively identify and address these issues, providing examples such as a U.K. retail chain overhauling obsolete performance metrics, a U.S. software company purging contradictory brand messaging, and a global financial services firm debunking customer myths through behavioral evidence. AI's ability to process vast datasets and present objective findings helps overcome emotional and political resistance to change.

Key takeaway

For product managers overseeing strategic initiatives, recognizing that legacy workflows and assumptions can silently erode competitiveness is crucial. You should consider deploying AI-powered analytics to objectively identify outdated metrics, inconsistent brand messaging, or false customer beliefs. This data-backed approach can provide irrefutable evidence for change, reducing internal friction and enabling your team to prioritize truly impactful product and strategy adjustments.

Key insights

AI provides objective, data-backed evidence to overcome organizational resistance to change and shed legacy practices.

Principles

• Outdated practices hinder competitiveness.
• Organizational forgetting is crucial for renewal.
• Objectivity reduces resistance to change.

Method

AI platforms (e.g., Snowflake Cortex Agents, Microsoft Fabric, GPT-4, IBM Watson Analytics) analyze internal documentation and live data streams to detect contradictions, obsolete terminology, and test embedded assumptions against real-world behavior.

In practice

• Use AI to identify irrelevant KPIs.
• Deploy AI for strategic language audits.
• Test customer myths with behavioral data.

Topics

• Organizational Forgetting
• Legacy Workflow Transformation
• Performance Metrics Optimization
• Brand Messaging Strategy
• Customer Behavior Analytics

Best for: Product Manager, Executive, Director of AI/ML, VP of Engineering/Data

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Editorial summary, takeaway, and curation by AIssential. Original article published by Feeds - HBR.org.