In a keynote address from re:Invent, McKinsey & Company's Lareina Yee shares fascinating data, trends and best practices on AI adoption, the future of skillsets, and leadership insights that are needed for AI transformation at scale.
Topics Include:
- Over 80% of companies have adopted AI in at least one business function currently.
- Despite heavy investment, 62% of companies remain in experimental or pilot phases with AI.
- Only 7% of organizations have achieved full-scale AI implementation, up from 2% earlier this year.
- Agentic AI has proliferated rapidly across functions from knowledge management to manufacturing in one year.
- Between 45% and 5% of companies have implemented AI agents across different business functions today.
- AI's productivity potential represents $4.4 trillion in economic value beyond just cost savings opportunities.
- Innovation ranks as the number one goal for AI investments, ahead of cost reduction priorities.
- Employee satisfaction, customer satisfaction, and competitive differentiation drive AI adoption alongside revenue growth and cost.
- High AI performers view implementation as total enterprise transformation, not just technology deployment projects.
- Leading companies spend 4.9 times more budget on AI investments compared to average performing organizations.
- Traditional software stacks evolved to SaaS, now transforming into AI-ready tech stacks within one generation.
- Job outlook remains mixed: 32% expect losses, 13% expect increases, 43% see no major change.
- Since 2023, significant skill shifts show increased demand for software development and business intelligence capabilities.
- AI fluency has increased seven times as the most sought-after skill across all job types.
- AI fluency means using AI in everyday work, not building models or creating large language models.
- Skills like driving records, coaching, customer service, and management remain harder to automate with current AI.
- Transactional, data-driven repetitive tasks like inventory management and invoicing face highest automation exposure currently.
- Historical technology revolutions like electricity created six to eight jobs for every one job displaced.
- New roles like prompt engineering emerge, requiring skills like effective questioning rather than technical coding.
Participants:
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