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How to build an AI workforce strategy using data | Perspectives from Davos | Deloitte Insights
Summary
A significant gap exists between the demand for AI skills and the actual implementation of workforce strategies. While 75% of companies seek AI talent, only 30% have a defined AI workforce strategy. This discrepancy highlights a critical challenge for organizations aiming to integrate AI effectively.
Employee engagement remains low, with only 21% of employees feeling engaged in their roles. This lack of engagement, coupled with the high demand for AI skills, indicates a misalignment between workforce capabilities and organizational goals.
Data plays a crucial role in understanding workforce dynamics and informing strategies. Utilizing workforce data and sentiment analysis can reveal engagement and trust gaps, which are essential for developing effective AI workforce strategies.
Organizations must evaluate the implications of AI on every job and role to establish a baseline understanding of required skills. A taxonomy of competencies can help in breaking down roles and understanding the economic impact of AI.
Perspectives
short
Proponents of AI Workforce Strategy
- Highlight the critical need for data to inform workforce strategy
- Emphasize the high demand for AI skills across industries
- Argue that understanding workforce dynamics is essential for effective AI integration
- Point out the low employee engagement as a challenge for organizations
- Propose using a taxonomy of competencies to assess job roles impacted by AI
Skeptics of Current AI Workforce Strategies
- Question the accuracy of the claim that 30% of companies have a genuine AI workforce strategy
- Critique the potential self-reporting biases in workforce strategy assessments
- Challenge the effectiveness of current strategies in addressing workforce needs
Neutral / Shared
- Mention the importance of sentiment analysis in understanding employee trust
- Discuss the implications of AI on job roles and required skills
Metrics
demand
75%
percentage of companies demanding AI talent
High demand indicates a critical need for AI skills in the workforce.
75% of companies are demanding AI talent in some way, shape or form.
strategy
30%
percentage of companies with a stated AI workforce strategy
This low percentage suggests a lack of preparedness to meet AI demands.
30% actually have a stated AI workforce strategy.
engagement
21%
percentage of employees engaged in their work
Low engagement may hinder the effective implementation of AI strategies.
21% of employees are actually engaged in what they're doing.
Key entities
Timeline highlights
00:00–05:00
A significant gap exists between the demand for AI skills, with 75% of companies seeking such talent, and the actual implementation of workforce strategies, as only 30% have a stated AI workforce strategy. Employee engagement is low at 21%, indicating a misalignment between workforce capabilities and organizational goals.
- 75% of companies are demanding AI skills, yet only 30% have a stated AI workforce strategy, which may be an inflated figure. This discrepancy raises questions about the effectiveness of current workforce strategies in meeting the demand for AI talent. The low engagement rate of 21% among employees further complicates the situation, indicating potential gaps in workforce alignment with organizational goals
- The use of data is emphasized as critical for understanding workforce dynamics and informing strategy. There is an interesting challenge posed by the high demand for AI skills, which may not be matched by employee engagement or trust in employer relationships. The reliance on sentiment analysis from sources like Gallup highlights the need for organizations to address these trust factors to improve workforce engagement
- The speaker speculates on the implications of AI for every job and role, suggesting that a baseline understanding of skills is necessary for effective workforce planning. With a taxonomy of 14 competencies, organizations may be able to better assess the economic impact of AI on roles. However, uncertainties remain about the specific actions that should be taken based on this analysis