Managers play critical role in a company's AI transformation - and they know it

· Source: News and Advice on the World's Latest Innovations | ZDNET · Field: Business & Management — Corporate Strategy & Leadership, Operations & Process Management, Human Resources & Workforce Development · Depth: Fundamental Awareness, short

Summary

A Salesforce survey of over 500 middle managers reveals their critical role and optimism in company AI transformations. Two-thirds of managers are optimistic about AI's future, with 77% already saving over three hours weekly using AI tools. This transformation is primarily relational, requiring a "seven Rs" framework: process redesign, employee re-skilling, talent redeployment, organizational restructuring, stakeholder value reclamation, AI-centric metric recalibration, and leadership re-mandate. Managers are crucial for reducing AI skepticism, especially among US desk workers, and 78% feel personally committed to their teams' successful AI adoption. Despite 51% feeling anxious about AI's pace, only 32% work for companies formally tracking AI adoption. Managers prioritize hands-on AI training (37%), clear organizational AI strategy (35%), and better IT support (34%) to lead successful AI integration.

Key takeaway

For Directors of AI/ML or VPs of Engineering aiming for successful AI integration, recognize that your middle managers are the linchpin. You should prioritize investing in hands-on AI training and developing a clear organizational AI strategy to empower them. This will directly address manager anxieties and skepticism, ensuring broader team adoption and tangible benefits, rather than just focusing on technology deployment. Your support for managers is critical for navigating the relational aspects of AI transformation.

Key insights

Middle managers are pivotal for successful AI transformation, driving adoption and addressing skepticism through relational change.

Principles

Method

Achieving agentic business transformation involves "seven Rs": redesign processes, re-skill employees, redeploy talent, restructure organizations, reclaim stakeholder value, recalibrate AI metrics, and re-mandate leadership.

In practice

Topics

Best for: CTO, Executive, Director of AI/ML, VP of Engineering/Data, Consultant

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Editorial summary, takeaway, and curation by AIssential. Original article published by News and Advice on the World's Latest Innovations | ZDNET.