AI Can't Survive Your C-Suite’s Magic Thinking

2021-11-04 · Source: High ROI AI · Field: Business & Management — Corporate Strategy & Leadership, Operations & Process Management, Project & Product Management · Depth: Intermediate, medium

Summary

The article argues that corporate culture, particularly "magic thinking" and business-driven data practices, is the primary cause of the 95% failure rate in AI initiatives. It claims that CEOs have failed engineering organizations by demanding conformity over true strategic innovation and by prioritizing business-driven data that skews findings to support pre-made decisions. This has created a "defect" in corporate structures, where technology is used to reflect broken processes rather than fix them. The author suggests that a recent "event" (likely the widespread AI adoption and subsequent failures) is forcing C-suite leaders to choose evidence over comfort, necessitating a dramatic transformation of enterprise and a shift towards outcomes-based approaches, rather than blaming engineers or reverting to old habits.

Key takeaway

For CEOs and C-suite leaders grappling with AI strategy, recognize that 95% of AI failures stem from entrenched corporate "magic thinking" and business-driven data, not technical issues. You must choose evidence over comfort, embracing uncomfortable enterprise transformations. Prioritize outcomes-based approaches and empower engineering leaders to integrate technology into the business, rather than forcing engineers to conform. Your ability to act decisively now will determine success over the next 18 months.

Key insights

Corporate "magic thinking" and business-driven data practices, not technical issues, cause 95% of AI initiative failures.

Principles

• Corporate culture often prioritizes conformity over engineering innovation.
• Business-driven data poisons the well for AI and ML success.
• AI amplifies existing broken processes and poor decisions.

In practice

• Integrate structural causal models for reality alignment.
• Prioritize data-driven insights over business-driven data.
• Embrace "the event" to drive uncomfortable but necessary change.

Topics

• AI Strategy
• Corporate Culture
• Data Governance
• Engineering Leadership
• Digital Transformation
• Business Outcomes

Best for: Executive, Director of AI/ML, Consultant

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Editorial summary, takeaway, and curation by AIssential. Original article published by High ROI AI.