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Welcome executives and professionals. This edition comes from HumanX in San Francisco, convening enterprise AI executives, innovators, and decision-makers, with many members of The Boardroom.

Since the previous edition, we have reviewed hundreds of the latest insights in agentic and generative AI, spanning best practices, case studies, market dynamics, and innovations.

This briefing outlines what is driving material value — and why it’s important.

In today’s briefing:

• Live from HumanX, San Francisco.

• McKinsey’s AI transformation manifesto.

• AI engineering and product management.

• IBM’s agentic AI governance playbook.

• Transformation and technology in the news.

• Insights for Executive+ members.

• Career opportunities & events.

Read time: 4 minutes.

EXECUTIVE INSIGHT

Live from HumanX, San Francisco

Brief: Enterprise AI Executive joined HumanX in San Francisco, alongside 6,500 leaders, builders, and investors (60% C-level executives, VPs) driving enterprise AI transformation from inspiration to execution.

Breakdown:

• Al Gore, former VP of the United States, discussed sustainable AI, drawing parallels between AI and globalization’s reskilling challenges.

• Dr. Fei-Fei Li, pioneer of modern computer vision, explored the next leap: 3D generative worlds across gaming and social experiences.

• Mercedes CIO shared how a code refactoring project was shortened from 8 months to 8 days, and that 50% of the workforce uses AI.

• Speakers included Matt Garman (AWS CEO), Mike Krieger (Anthropic Labs Lead), Ali Ghodsi (Databricks CEO), Andrew Ng, and others

Why it’s important: HumanX connects AI decision-makers, fostering conversations and connections. It’s designed to help build relationships with C-level executives, VPs, and leaders shaping AI’s future. A powerful network for advancing AI strategies, partnerships, and industry transformation.

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BEST PRACTICE INSIGHT

McKinsey’s AI transformation manifesto

Brief: McKinsey published its AI transformation manifesto, outlining twelve themes that distinguish companies truly rewired for AI. These themes act as a checklist for change and guide organizations along the journey to value.

Breakdown:

• Leaders who rapidly absorb technologies like agentic AI have built the capabilities required to stay ahead and outperform peers.

• Will your transformation deliver game-changing value, or will wins be incremental, impacting your long-term success?

• McKinsey highlights studies of 20 leading companies, whose AI-driven transformations improved EBITDA by 20%.

• Other themes include (re)learning as if your business depends on it, ensuring AI deployments withstand scrutiny, and more.

Why it’s important: The companies that are truly innovating with AI are doing something very different from their peers: They are conceptualizing and developing AI capabilities that reshape their products, services, core business processes, and organizational systems to drive competitive advantage.

BEST PRACTICE INSIGHT & CASE STUDIES

AI engineering and product management

Brief: Deloitte explored the future of work and skills in engineering and product management, driven by two converging forces: the rise of agentic AI and the stabilization of hybrid work models.

Breakdown:

• AI is reshaping tech hiring, decoupling productivity from headcount and favoring specialized, senior talent over large teams.

• Software engineering is evolving into “SE 3.0,” where engineers shift from coders to orchestrators managing AI agents to build complex systems.

• Product managers are compressing the Product Development Life Cycle (PDLC), shifting from coordination to strategic acceleration (image above).

• Deloitte’s READY framework guides transformation, focusing on upskilling, AI-aligned leadership, Y-shaped HR, and more.

Why it’s important: AI is improving new product development times by 50% and accelerating software development tasks, with productivity gains of 30-40% in engineering teams. To realize this value, firms should rethink entire workflows, develop new skills, and adapt talent for human-agent collaboration.

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BEST PRACTICE INSIGHT

IBM’s agentic AI governance playbook

Brief: IBM shared insights on governing agentic AI at scale to unlock enterprise value. Without clearly defined purpose, boundaries, and success criteria, agents, regardless of capability, will deliver limited value.

Breakdown:

• The playbook covers the agentic opportunity-execution gap, why expanded AI governance is required, and where pilots fail.

• It highlights five fundamental choices that must be defined before agents take control, including who is accountable when an agent fails.

• IBM presents a framework for controlling agentic AI (image above), with example controls throughout the lifecycle.

• In planning, for instance, it’s key to define an agent’s purpose, scope, decision boundaries, and limits on access to APIs and systems.

Why it’s important: Autonomy requires an understanding of how to use it to create value. Not merely technical value and should thus be tied to defined output measures, incorporated into standard operating procedures and have supporting structures that maintain consistency and accountability.

WEF’s 13-page paper outlined four scenarios for physical autonomous systems by 2031, exploring their future impact on industries.

McKinsey explored AI’s revolution in software development, detailing best practices and how a factory of AI agents operates in the field.

Deloitte’s system dynamics model warned that cutting technical roles without matching data and AI investments could harm enterprise agility.

HfS released a 42-page assessment of agentic services, analyzing the why, what, how, and so what of service provider strategies.

KPMG’s 26-page Managed Services Outlook showed over 90% of executives see managed services as essential for delivering agentic AI solutions.

OpenAI’s 13-page policy document proposed ideas for navigating superintelligence, recommending 4-day work week pilots.

Anthropic introduced Project Glasswing, a cybersecurity coalition with major partners (e.g. AWS, Google), built around Claude Mythos Preview.

Meta plans to release initial AI models from Alexandr Wang’s Superintelligence team, with some open sourced while its largest models remain closed.

Anthropic blocked agent platforms like OpenClaw on Claude plans, shifting usage to paid add-ons or API access amid rising agent demand.

OpenAI, Google, and Anthropic are coordinating via the Frontier Model Forum to limit model distillation risks from Chinese AI competitors.

Microsoft’s Bing team open-sourced Harrier, a state-of-the-art embedding model supporting 100+ languages for search and AI agent grounding.

Z AI released GLM-5.1, an open-source coding model competing with frontier rivals, designed for extended autonomous sessions lasting up to eight hours.

CAREER OPPORTUNITIES

Deloitte - VP Sales Executive, Anthropic

JPMorgan - Executive Director, Agentic AI Strategy

Turing - Head of Applied AI Lab

EVENTS

IBM Think - May 4-7, 2026

C-Vision AI Executive Dinner - May 14, 2026

AI for Good - July 7-10, 2026

Reach enterprise AI decision-makers:

• 66% of readers are C-level executives or VP and Director-level leaders.

• 63.2% of the audience is based in the U.S., EU, UK, ANZ, and Singapore.

• Read by leaders at Microsoft, Deloitte, the Fortune 500, and more.

Guaranteed impression and custom sponsorship packages available, with post-send performance reporting.

Conceived as a practical communication for executives Lewis Walker has worked with, this briefing has become a trusted resource for thousands of senior decision-makers shaping the future of enterprise AI.

We welcome your feedback.