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:

• Lareina Yee - Director of Technology Research, McKinsey & Company

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AWS Principal Solutions Architect Wallace Printz explains how agents are reshaping SaaS business models, pricing strategies, and technical architectures.

Topics Include:

• Wallace Printz discusses agentic workloads transforming SaaS with largest AWS customers
• New interaction models include generative UI, voice agents, and proactive work
• Agents extending SaaS products to interact with external systems and businesses
• Virtual teammates enabling cross-department collaboration and upskilling non-expert users effectively
• Monetization strategies evolving as predictable costs become variable with agents
• Three patterns: dedicated agents, shared agents, and multi-tenant personalized agents
• Multi-tenant agents enable hyper-personalized experiences using individual tenant context enrichment
• Agent-centric business strategy requires real assessment beyond AI hype cycle
• Agent orchestration complexity grows with multiple specialized agents interacting together
• Tenant isolation requires JWT tokens and AWS Bedrock Agent Core identity
• Cost-per-tenant management needs LLM throttling, tiering, and unified control plane
• Multi-tenancy creates sticky personalized experiences; AWS white paper releasing soon

Participants:

• Wallace Printz - Principal Solution Architect, Amazon Web Services

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Industry leaders from Boomi, Demandbase and Smarsh share hard-won lessons on balancing AI creativity with guardrails, why data quality trumps frameworks, and deploying AI at scale.

Topics Include:

• Three industry leaders share experiences building AI solutions at Boomi, Demandbase, and Smarsh.
• Smarsh manages trillion communications for financial services, detecting bad actors across multiple channels.
• Boomi built agent studio, garden, and control tower while spawning 33,000 internal agents.
• Chris Timmerman used vibe coding to build embeddable Boomi in five months solo.
• Companies balance creativity with guardrails, starting with IT policies before unleashing innovation.
• Internal adoption driven by empowering teams to build their own solutions versus top-down.
• Demandbase saw 70% adoption within six months through grassroots approach and local champions.
• Measuring success proves challenging, comparable to tracking Excel usage rather than specific KPIs.
• Companies focus on outcomes like touch-free bug fixes and support metrics versus raw usage.
• Biggest lesson: Data quality and context determine success more than agentic frameworks.
• Need scaling framework from low-risk UX improvements to high-risk automation with appropriate guardrails.
• Industry created fatigue by overpromising; should have started smaller with realistic expectations.

Participants:

• Chris Timmerman – Vice President, Global Services Delivery, Boomi
• Harshal Dedhia – Vice President of AI, Demandbase
• Brandon Carl - Executive Vice President of AI and Product Strategy, Smarsh
• Allison Johnson - AMER Technology Partnerships Leader, Amazon Web Services

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