Edition in partnership with

Welcome executives and professionals. Agentic AI partnerships face complex challenges, including governance and liability, that can strain relationships between companies with different worldviews and decision-making speeds.

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:

• How executives fix failing partnerships.

• The growing AI operations challenge.

• How enterprises put AI to work.

• The path to agentic transformation.

• Transformation and technology in the news.

• Insights for Executive+ members.

• Career opportunities & events.

Read time: 4 minutes.

BEST PRACTICE INSIGHT & CASE STUDIES

How executives fix failing partnerships

Brief: BCG examined how agentic AI raises the stakes for tech-industry partnerships, even as success rates remain poor. To improve the odds, leaders should match the partnership to the right archetype and avoid six key pitfalls.

Breakdown:

• As agentic AI reshapes sectors, enterprises increasingly depend on tech partnerships, yet nine in ten have previously failed to achieve their goals.

• Despite that failure rate, the logic for tech-industry partnerships is sound: they solve a number of fundamental strategic problems (image above).

• Match the partnership archetype to strategic intent: AI transformist, tech co-creator, venture launcher, or cross-border integrator.

• Common pitfalls include misaligned incentives, unclear data and IP ownership, and decision-speed mismatches. Each has a fix.

Why it’s important: Daunting as the pitfalls are, enterprises are right to seek partnerships that bring leading-edge technology, particularly agentic AI, into their sector. Choosing the right archetype and avoiding the six pitfalls cuts risk and accelerates learning.

IN PARTNERSHIP WITH TELEPORT

From zero trust to agent trust

Brief: AI agents operating at scale have characteristics that have no equivalency in purely human or software environments. Zero trust, as currently conceived, is insufficient to contain them. Teleport's new white paper explores what must change to preserve trust as agents enter your infrastructure.

The Teleport advantage:

• Least-privileged access enforced per request for every AI identity

• Short-lived certificates that eliminate static credentials and secrets

• Full identity attribution for every AI action across your infrastructure

• Audit-ready visibility into human and machine access alike

Trust doesn't scale by default. Read the new white paper.

BEST PRACTICE INSIGHT

The growing AI operations challenge

Brief: McKinsey explored the AI operations challenge and what it takes to keep production AI delivering value after launch, along with Live AI Operations (LiveOps), the offering it designed to address that challenge.

Breakdown:

• In agentic systems, the blast radius expands because the system acts autonomously. Many common failure modes rarely surface in testing.

• LiveOps, from QuantumBlack, AI by McKinsey, is an end-to-end AI operations capability across Build and Launch → Operate → Maintain.

• It turns one-time AI deployment into a dependable, long-term service, with a clear set of practices so AI continues to deliver value in production.

• McKinsey breaks down four critical elements: evaluations; architecture, scalability, and tooling; observability; and model changes and reliability.

Why it’s important: AI projects succeed only if they keep working after deployment. Value can erode after launch, and the trust users place in it. Teams can quickly find themselves consumed by reactive fixes: outages, degraded outputs, stakeholder disappointment, and falling adoption.

MARKET & BEST PRACTICE INSIGHT

How enterprises put AI to work

Brief: OpenAI published its latest edition of Enterprise Signals, drawing on enterprise usage data. It shows a widening frontier gap between leading (top 10%) and typical firms (middle 10%), and a shift to AI execution.

Breakdown:

• As of June, Agentic (Codex) generated 64% of combined Agentic (Codex) and ChatGPT output tokens among enterprise customers (image above).

• Frontier firms, the top 10% by AI usage, generate 8.3x the output tokens per active user of typical firms, up from 2.6x in January.

• Each week, 21% of active users at frontier firms use Plugins, versus 9% at typical firms, highlighting room for deeper adoption.

• Since February, weekly Codex users grew 108x in legal, 41x in sales and recruiting, and 26x in marketing, versus 5x in engineering.

Why it's important: Enterprise AI is entering a new phase: more work is delegated to agents, and the firms furthest along are pulling away. They use the same models as peers; what differs is how they deploy them, giving agents complex work well beyond software development.

AI-NATIVE PROFESSIONAL

How to create presentations with ChatGPT Work

Brief: In this guide, you'll learn how to create or revise a PowerPoint or Google Slides presentation with ChatGPT, working from your own source material, an existing reference deck, or a reusable template you can apply to future decks.

Step-by-step:

1. Start with materials you have: notes, a memo, research, or an existing deck. Tell ChatGPT who it's for and what should stay unchanged.

2. In the ChatGPT desktop app, use @Presentations to build a deck from source material. Inside an open file, use the PowerPoint add-in.

3. ChatGPT drafts a short slide plan, builds the presentation, and checks the rendered slides, preserving approved figures and your branding.

4. Use follow-up prompts to match a reference, adapt the story, bring in new information, or save a format you expect to use again.

Best practice: Template Creator saves a personal template backed by the original presentation, so you can reuse the same format in future tasks.

For the full guide, including prompts, upgrade to Executive+ or The Boardroom.

MARKET INSIGHT & CASE STUDIES

The path to agentic transformation

Brief: Deloitte surveyed 501 US-based senior managers through C-suite leaders across five industries between April and June 2026, all at least piloting agentic AI. Findings were augmented by 20 executive and AI leader interviews.

Breakdown:

• 42% of leaders say their organizations have tested or deployed AI agents; only 15% have scaled, orchestrated multi-agent adoption.

• 72% say they lack unified, accessible data; 70% don’t feel they can trust and govern agents; and 67% say integration is too costly and complex.

• Across seven organizational readiness areas, 52% say they are prepared or highly prepared on vision and strategy (image above).

• 43% of leaders expect AI agents to bring significant job disruption within 18 months; over two to three years, that rises to 72%.

Why it’s important: Without decisive action, gains may stall and returns disappoint. Near-term efforts may yield localized, quick-win ROI. But realizing agentic AI's potential means treating it not as a layer atop existing processes, but as enterprise-wide transformation.

Kearney detailed how focusing on the five highest-intensity enterprise AI cost pools can recover 20 to 40% of run-rate spend in 12-18 months.

BCG published a guide to how an Enterprise AI Control Plane helps CIOs govern AI agents, and detailed AI in banking risk reviews.

McKinsey outlined four actions leaders can take to build trust through transparency, clarity, and sustained investment in employees.

KPMG outlined six steps to embed AI security into enterprise operations, from initial discovery through to continuous validation.

MIT, with Google Cloud, published a 19-page report surveying 300 data and tech executives on how legacy systems limit AI agent effectiveness.

Anthropic published research on multiagent AI systems, from measuring coordination to conformity and incompatible goals.

OpenAI previewed Ultrafast, a Cerebras-powered API tier that speeds up its GPT-5.6 Sol model by up to 14x, hitting 750 tokens/sec.

SpaceXAI launched Grok 4.6, a new top model rivalling frontier options like Fable 5 and GPT-5.6 Sol while charging 60% less to run.

Google released Gemini Flash 3.7, with strong upgrades to coding, knowledge work, and intelligence at a price undercutting Sonnet 5.

Databricks closed a $5B round at a $190B valuation, and crossed a $7B revenue run-rate after growing more than 80% year over year.

Google announced that its Gemini app has officially hit 1B users, making it the fastest-growing product in the company's history.

OpenAI hired Wiz President and COO Dali Rajic as its revenue chief, replacing former Slack CEO Denise Dresser after under a year.

CAREER OPPORTUNITIES

OpenAI - Partner Director, McKinsey Alliance

Cognizant - Senior Partner Consulting, AI

Samsung - AI Strategy Leader

EVENTS

WRITER - The Agentic Enterprise - August 25 2026

HCLTech - Contact Centre AI Transformation - September 03, 2026

MIT - Leading in an AI World - October 05, 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.