Welcome, executives and professionals.

We identify and breakdown the top 1% of Generative AI for enterprises.

This week:

• Sequoia: AI apps beating corporate IT "pretty doable".

• MIT's real-world GenAI case studies & insights for enterprises.

• McKinsey transforms its document classification with GenAI.

• Accelerate builds with new prompt engineering repository.

• Fast Fives: Transformation and technology in the news this week.

• Career opportunities & events.

Read time: 4 minutes.

MARKET INSIGHT

Sequoia: AI apps beating corporate IT "pretty doable"

Brief: Sequoia, the prominent Silicon Valley venture capital firm, discusses in its article Generative AI’s Act o1 how startups beating corporate IT and global systems integrators by focusing on GenAI at the application layer is "pretty doable".

Breakdown:

• Competition in the foundational layer (infrastructure and models) is stabilizing, led by Microsoft/OpenAI, AWS/Anthropic, Meta, and Google/DeepMind, due to high capital requirements.

• GenAI is evolving from "thinking fast" (pre-trained responses) to "thinking slow" (reasoning at inference), unlocking the potential for disruptive "killer apps" in consumer and enterprise markets.

• The cloud transition brought software-as-a-service. The AI transition is about building applications that automate and amplify knowledge work, 'service-as-software', a much larger market worth trillions.

• However, transforming generative AI capabilities into reliable end-to-end enterprise applications still requires significant expertise and engineering effort.

• Established enterprises must adapt or risk being outpaced by new businesses that master the intricacies of knowledge work and manage to reach customers.

• Similar to the emergence of 20 $1 billion+ companies in cloud and mobile applications, Sequoia expects a comparable opportunity with AI.

Why it’s important: There is vast potential for enterprise disruption and reinvention. Innovation at the application layer will play a key role in defining the next generation of industry leaders. The choice is clear: disrupt or be disrupted.

BEST PRACTICE INSIGHT & CASE STUDIES

MIT's real-world GenAI case studies & insights for enterprises

Brief: MIT’s new special report Leading With AI explores how enterprises are leveraging GenAI, featuring various insights and real-world case studies from eight companies. Each case includes a graphic detailing approaches and value delivered.

Breakdown:

• The report highlights Pfizer speeding up knowledge transfer, Comcast improving customer call responses, and Takeda accelerating drug trial designs.

• It also features Dicks Sporting Goods creating personalized email campaigns faster, along with four other case studies.

• Scaling AI or GenAI is a top priority for 82% of C-suite leaders, while 80% of chief data officers believe GenAI will transform their business. AI has been shown to improve worker performance by up to 40% when used for appropriate tasks.

• There is no single route to large-scale AI deployment. Leaders should focus on solving critical business problems with AI, ensuring their data is AI-ready, and addressing AI maturity levels and skills gaps among employees.

• To reskill employees, companies like Johnson & Johnson follow a three-step approach: develop a skills taxonomy, gather evidence of current skills, and assess employees to identify training needs.

Why it’s important: MIT’s report provides leaders with actionable insights and detailed real-world case studies to help integrate GenAI effectively, enhance workforce performance and drive innovation across industries.

CASE STUDY

McKinsey transforms its document classification with GenAI

Brief: McKinsey traditionally relied on manual processes to curate and tag documents in its internal knowledge repository, achieving ~50% accuracy. A new generative AI tool now labels 26,000 documents annually, improving accuracy and efficiency.

Breakdown:

• McKinsey’s manual tagging system took 20 seconds per document with ~50% accuracy.

• The GenAI tool uses zero-shot classification with GPT, reducing classification time to 3.6 seconds per document and improving accuracy to 79.8%.

• The new system saves up to 676 hours of manual work per analyst each year.

• Annually, 26,000 documents are automatically labeled, which will enhance metadata for 140,000 weekly user queries in its colleague GenAI chatbot, Lilli.

• The solution improves the search algorithm’s performance by improving search relevance and reducing errors.

Why it’s important: Automating document classification enhances efficiency and accuracy while improving McKinsey's knowledge management and responsiveness to client needs.

ACCELERATOR

Accelerate builds with new prompt engineering repository

Brief: A new repository of prompt engineering tutorials and implementations offers one of the most extensive collections available today, featuring step-by-step tutorials and practical prompt implementations utilizing Python code, LangChain, and OpenAI models.

Breakdown:

• The repository includes 22 tutorials covering fundamental concepts, core techniques (e.g. chain of thought), optimization, refinement, and advanced applications (e.g. ethical considerations, prompt security).

• Implementations leverage Python code, the LangChain framework, and OpenAI models.

• This repository builds on linked repositories for RAG techniques (now 31 implementations), recently summarized, and GenAI Agents (now 17 implementations), recently summarized.

• Users can clone these repositories, navigate to techniques of interest, and follow detailed implementation guides in each technique’s notebook.

Why it’s important: Leveraging this comprehensive repository enables teams to quickly adopt and refine prompt engineering techniques, accelerating the development of generative AI applications in enterprises.

Transformation

In the news this week:

1. Deloitte reveals new survey: nearly 50% of boards don’t yet have AI on the agenda, and just 2% have high expertise. The report highlights steps to strengthen strategy, governance, and AI literacy for improved oversight.

2. Amazon scaled Rufus, a generative AI-powered shopping assistant, using 80,000 AWS chips for Prime Day, supporting customer decisions by gathering insights from Amazon and across the web. The case study summarises the solution, including optimization and scaling.

3. Air Street Capital released its State of AI 2024 report, highlighting OpenAI’s leadership in reasoning, minimal impact of US sanctions on Chinese labs, and rising AI enterprise revenues.

4. World Economic Forum published a white paper on AI governance, advocating for a 360° approach to policy and regulation, addressing current gaps introduced by GenAI, sharing cross-sector knowledge, and cultivating global cooperation.

5. Infosys hosted Stanford’s Prof. Mykel Kochenderfer, who shared insights on generative AI’s potential in helping to design aircraft, improving material composition, and advancing autonomous flight systems.

Technology

In the news this week:

1. OpenAI reportedly seeks independence from Microsoft for compute power. It also introduced a new benchmark to evaluate AI agents' performance on real-world machine learning engineering tasks.

2. Anthropic launched the Message Batches API, allowing developers to submit up to 10,000 queries for async processing in under 24 hours at a 50% discount compared to standard API calls.

3. Writer, an AI enterprise startup, launched Palmyra X 004, an LLM that sets a new benchmark for action capabilities and function calling tasks in enterprise AI, outperforming leading models.

4. AMD launched its new lineup of AI-focused processors at the Advancing AI 2024 event, aiming to compete with Nvidia and Intel in the data center and AI chip market.

5. Sierra, led by OpenAI Chairman Bret Taylor, is reportedly set to raise hundreds of millions in funding at a valuation of over $4B for its conversational enterprise AI agents.

Career opportunities

• Nvidia - Director of Product Management – Enterprise Gen AI Software

• JPMorgan - Generative AI - Vice President

• AWS - Principal Specialist SA, Generative AI and ML

Events

• GENAI SUMMIT Silicon Valley 2024 - November 1 - 3, 2024

• Generative AI in Operations Webinar (1 hour) - October 17, 2024

• Private Equity and Generative AI - AI Leaders from Bain & Company, Apax Partners, and Anthropic (1 hour) - October 23, 2024

Whenever you’re ready, here’s how we can help you:

1. Get 12 proven Generative AI case studies from industry leading enterprises for free. In-depth analysis and tangible value delivered.

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All the best for the week ahead,

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