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In today's lineup: 

Robots

• Only 12% of companies are ready for AI

• Real ROI from Gen AI

• A leader's guide to RAG frameworks

People

• How John Ketchum became the most powerful man in the AI boom

Love

• The most important AI skill

• Transformative Reads: Turn the Ship Around! by L. David Marquet

Top Insights

• The skilled trades shortage is the real bottleneck for the AI boom.

• A new 25% tariff treats the AI supply chain as a national security risk.

• Interest rate hikes are cutting more jobs than automation is.

• The entire AI boom depends on one company's manufacturing forecast.

• Anthropic now warns its own product could trigger economic instability.

Only 12% of companies are ready for AI

A new Genpact report shows that only 12% of companies have the advanced capabilities to succeed with autonomous AI. This confirms a broader trend identified by analysts who see agentic AI transforming enterprise operations and leading the next wave of technological change. The research reveals a major gap between ambition and reality, as most organizations are stuck with messy data, rigid operating models, and no clear plan to move beyond simple automation.

How leaders can close the gap:

• Unify your data strategy to provide the clean information autonomous systems require.

• Stop plugging AI into broken workflows and instead redesign your core processes around its capabilities.

• Build cross-functional teams that can adapt as the technology and business needs change.

• Implement a governance framework that manages the risks and measures the ROI of each AI initiative.

Real ROI from Gen AI

How human-centric AI delivers business results

• Air India's virtual agent, built on Microsoft Azure, handles over 30,000 customer queries daily and automates 97% of sessions.

• CBRE's AI tool analyzes portfolio data to find underperforming assets, helping clients cut operational costs.

• Wayfair uses Google's Vertex AI to create "virtual photography," cutting the high cost of physical photoshoots for its online catalog.

Tool Spotlight

Your weekly briefing on tools that create competitive leverage

A leader's guide to RAG frameworks

LangChain

Best for: Developers who need a versatile framework for building a wide range of LLM applications. 

Choose if you:

• Need a modular, all-purpose toolkit for chaining components together.

• Are building complex applications that require custom agentic behaviors.

• Value a large, active community and extensive integration support.

LlamaIndex

Best for: Teams focused specifically on building powerful, data-centric RAG applications. 

Choose if you:

• Need to connect LLMs to your private or domain-specific data.

• Prioritize advanced indexing and retrieval strategies for complex data.

• Are building search, summarization, or question-answering applications.

3 other data frameworks to explore...

• Haystack: An open-source framework for building custom LLM applications with a strong focus on production-ready RAG.

• Meltano: An open-source platform for building and managing data pipelines, designed for data engineers who need control and visibility.

• Airbyte: A data integration platform for moving data between applications and databases, known for its large library of connectors.

Transformation Champion

How John Ketchum became the most powerful man in the AI boom

AI’s insatiable demand for electricity is the biggest bottleneck to its growth. John Ketchum, CEO of NextEra Energy, tackled this not as a utility provider, but as a "technology company that delivers electricity." Instead of just reacting to demand, he uses AI and a digital twin of the grid to show hyperscalers the ideal locations for their next data centers. As he explained in a recent McKinsey interview, this proactive approach transforms NextEra from a simple utility into an indispensable partner, actively building the infrastructure for the AI economy.

The most important AI skill

Most companies are hiring for "prompt engineers," but a study of 600+ users found the skill has almost no impact on performance.

The skill that actually matters is your team's ability to build a working relationship with the machine.

Three ways to build this skill:

• Clarify intent instead of just optimizing prompts. Your team needs to understand the AI’s reasoning to guide it t

  o the right outcome, especially when the first answer is wrong.

• Treat the AI like a new team member. Learn its strengths, test its weaknesses, and find its biases. The best users build a mental model of how their AI "thinks."

• Focus on relational intelligence. The work is a dialogue. Your team's ability to infer the AI's context and adapt is what produces better results.

Learn more in my article.

Transformative Reads

One book, handpicked from my conversations with friends, industry leaders, and tech innovators:

Turn the Ship Around! by L. David Marquet is a playbook for dismantling top-down leadership. On a nuclear submarine, Marquet pushed control to his crew, the people with the most direct information. The book’s core insight is that empowerment without competence creates chaos. It shows how to build a team's technical skill and organizational clarity until everyone is not just willing, but able, to take command.

Perfect for: Ops, Inno, and Tech leaders building high-performing, autonomous teams.

In Culture

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