Welcome executives and professionals. Google Cloud CEO Thomas Kurian briefed Enterprise AI Executive ahead of Next ’26 in Las Vegas, expected to draw 35,000 attendees.

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:

• Google Cloud CEO keynote preview.

• Google CEO on being “customer zero”.

• OpenAI’s AI jobs transition framework.

• The convergence of blockchain and AI.

• Transformation and technology in the news.

• Insights for Executive+ members.

• Career opportunities & events.

Read time: 4 minutes.

NEXT ‘26

Google Cloud CEO keynote preview

Brief: Agentic enterprise transformation is underway, and Google Cloud’s unified AI stack enables it. Here’s a preview we received of what Google Cloud CEO Thomas Kurian plans to announce in today’s 9 a.m. PST Next ’26 keynote.

Breakdown:

• Google is introducing Gemini Enterprise Agent Platform, a secure full-stack connective tissue to build, scale, govern and optimize agents.

• Google is unveiling new agentic security offerings, combining Google Threat Intelligence and Security Operations with Wiz’s platform.

• The new eighth-generation TPU 8t is built for training, scaling to 9,600 chips and 2 petabytes, 3x the processing power of Ironwood.

• TPU 8i, optimized for inference, connects 1,152 TPUs in a single pod, reducing latency to run millions of agents cost-effectively.

Why it’s important: Since last year’s Cloud Next, the pace of change has accelerated as enterprises accelerate agentic transformation. Google’s first-party models now process 16 billion+ tokens per minute through customer APIs, up from 10 billion last quarter.

NEXT ‘26

Google CEO on being “customer zero”

Brief: Google Cloud held an event last night to unveil the eighth-generation TPUs. The launch reinforced Google’s “customer zero” model, a theme Google CEO Sundar Pichai is expected to highlight today online.

Breakdown:

• Google always wants to imagine, test, build and scale its best products internally before bringing them to enterprise customers.

• AI now helps Google create 75% of new internal code, up from 50% last fall, with engineers reviewing and approving output.

• Google’s Security Operations Center agents now automatically triage tens of thousands of threat reports each month.

• Google’s marketing teams used its AI models to rapidly generate creative asset variations, driving a 20% increase in conversions.

Why it’s important: Operating as customer zero gives Google a live environment to test products at scale before customers deploy them. That can improve reliability, and create stronger proof points for enterprises. Beyond TPUs, Google’s Bigtable database service is another example.

MARKET INSIGHT

OpenAI’s AI jobs transition framework

Brief: OpenAI introduced its AI Jobs Transition Framework, combining technical exposure, human necessity and demand elasticity, then validating results with ChatGPT usage data across 900+ occupations covering 153.7 million U.S. jobs.

Breakdown:

• High automation risk: 18% of roles face higher short-term automation risk, especially routine clerical work such as data entry keyers.

• Less immediate change: 46% of jobs are less likely to see near-term disruption, mainly now hands-on roles such as janitors.

• Growth with AI: 12% of jobs could expand because of AI, as lower effective cost may increase utilization, including software developers.

• Reorganization: 24% of jobs may see declining employment as task composition shifts, though remaining positions will still need workers.

Why it’s important: Most analysis of AI’s impact on the labor market begins with the same question: what jobs are most exposed to AI? Exposure helps us understand where AI has technical capability. It cannot, on its own, tell us which jobs are most likely to be automated, redesigned, or expanded.

BEST PRACTICE INSIGHT & CASE STUDIES

The convergence of blockchain and AI

Brief: Hedera published a 32-page report explaining how the convergence of AI and distributed ledger technology is built on three core principles and is already being applied to strengthen trust across enterprise environments.

Breakdown:

• Autonomous AI agents require infrastructure no single party controls. Contracts, payments and decisions create risks on centralized databases.

• AI regulation requires transparency immutable ledgers can provide. The EU AI Act mandates audit trails that centralized systems struggle with.

• Economic scalability requires micropayment rails, as AI agents will make thousands of daily transactions beyond traditional capabilities.

• The report includes case studies with Hedera, NVIDIA and Accenture delivering verifiable compute capacity and AI governance infrastructure.

Why it’s important: The AI industry is reaching an inflection point as systems evolve from reactive assistants into autonomous agents. By 2033, the global AI market is projected to reach $4.8 trillion. Billions of agents will require trustless coordination, verifiable execution and economic agency.

Bain detailed how the Claude Mythos cybersecurity wake-up call reflects a business risk of the highest order, not a technology problem to be delegated.

BCG outlined four visions for 2050, including AI abundance, based on analysis of 100 megatrends and historical data.

Deloitte’s TMT Predictions 2026 include gen AI inside existing search engines overtaking standalone gen AI, and exponential AI agent orchestration value.

AWS explored AI-driven business process re-engineering, asking why firms stopped asking “What’s the problem?” and how to redesign work.

MIT outlined how to build an effective AI strategy and why responsible AI must address workforce impact.

Delphi Group argued in a 45-page paper that the agentic age’s core disruption is not autonomy, but leadership itself.

Adobe introduced CX Enterprise, an agentic platform helping businesses coordinate marketing, content and customer engagement through AI agents.

Anthropic launched Claude Design, turning prompts, screenshots and codebases into prototypes and marketing assets using Opus 4.7.

OpenAI rolled out Chronicle, a Codex preview feature that runs background agents capturing screens to build persistent memories.

Google co-founder Sergey Brin is rallying DeepMind to out-code Anthropic with Gemini via a "strike team" focused on self-improving AI.

Moonshot AI open-sourced K2.6, an agentic coding model nearing top models like GPT-5.4, Opus 4.6, and Gemini 3.1 Pro at lower cost.

Nous Research launched Tool Gateway, a subscription service powering Hermes Agent without requiring multiple APIs amid surging usage.

CAREER OPPORTUNITIES

Cognizant - Head of AI Sales

Estée Lauder - AI Executive Director

Zoom - AI Transformation Lead

EVENTS

Deloitte Global AI Fest - May 2026

Google Agentic Exec Roundtable - May 5, 2026

The AI Summit - June 10-11, 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.

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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.

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