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Welcome executives and professionals. The C-suite should empower CIOs to build the right technical foundations now, or watch today's investments harden into tomorrow's brittle legacy.

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:

• Four CIO pillars for scaling agentic AI.

• McKinsey’s CFO on the costs of AI.

• Agentic AI's impact on sales growth.

• Navigating AI with legal confidence.

• Transformation and technology in the news.

• Insights for Executive+ members.

• Career opportunities & events.

Read time: 4 minutes.

BEST PRACTICE INSIGHT

Four CIO pillars for scaling agentic AI

Brief: BCG detailed how CIOs can manage the explosion of complexity that comes with deploying agentic AI, arguing that companies must retrofit existing architecture and governance to create a scalable AI backbone.

Breakdown:

• Business-led agent sprawl is accelerating risk, as value proofs and experimentation multiply into thousands of ungoverned agents.

• An engineering productivity paradox is emerging: AI-enabled development boosts output but risks piling on serious technical debt.

• Agentic tools and frameworks can become outdated in under a year, so platform partnerships must sit alongside a fast-moving agentic layer.

• The AI backbone rests on four pillars: GenAI platform services, AI graduation pathways, continuous refactoring, and adapted ITSM.

Why it’s important: CIOs should act within six to twelve months or risk agentic adoption outpacing their ability to retrofit governance and architecture. With agent-building now embedded in major enterprise platforms, the question is not whether agents proliferate, but how well firms govern them.

IN PARTNERSHIP WITH ASAPP

Your AI agent strategy shouldn't stop at deployment

Brief: Most enterprises focus on building and deploying agents. But successful AI requires more than getting an agent into production, or the agent will plateau quickly. Organizations need a system to continuously:

• Discover new opportunities for AI automation

• Build and validate customer-facing AI agents

• Improve live performance and turn insights into what comes next

Explore the infrastructure behind successful AI agents.

EXECUTIVE INSIGHT

McKinsey’s CFO on the costs of AI

Brief: McKinsey CFO Yuval Atsmon told Reuters how the firm is managing surging AI costs, why productivity gains haven't fundamentally changed project timelines, and how AI is reshaping pricing, talent, and the consulting model.

Breakdown:

• AI spend is still small but growing 20-30% month over month; one lever is directing people to the right model for the right task. 

• Teams now deliver more, but timelines are largely unchanged: client complexity has risen as AI forces firms to rethink their business.

• A third of McKinsey's work is already priced on measurable client impact; Atsmon expects AI to speed the shift from team-based fees. 

• McKinsey's hiring class is up about 25%, and Atsmon predicts generalist demand will return as AI lets one person span more domains. 

Why it’s important: Atsmon gives a view of AI economics at scale: costs are compounding fast, much of the productivity gain is reinvested in rising expectations, and pricing and talent models must adapt. It offers insights for executives weighing their own AI investments.

MARKET & BEST PRACTICE INSIGHT

Agentic AI's impact on sales growth

Brief: Oliver Wyman, with proSapient, surveyed 100 sales leaders at companies already using agentic AI, revealing where it delivers the most impact and where scaling requires new capabilities and operating models.

Breakdown:

• Sales leaders most often cite a positive impact of agentic AI on sales growth (89%), productivity (87%), and lead conversion (61%).

• Sales leaders overwhelmingly report strong agentic AI impact at the top of the funnel, where reps find and prioritize prospects (image above).

• Fewer sales leaders saw meaningful mid-funnel impact, where leads are nurtured and handoffs occur between AI agents and human reps.

• 37% of sales leaders said enhanced decision-making was the single most effective change agentic AI has brought to their sales organizations.

Why it's important: The next wave of value will be captured by leaders who pilot and scale agents systematically, with integrated data, clear governance, and well-choreographed human/AI handoffs that protect customer experience. Acting now with focus will build lasting advantage.

AI-NATIVE PROFESSIONAL

How to build financial models with Claude

Brief: In this guide, you'll learn how to create investment analyses with complete financial models, scenario planning, and risk evaluation to produce recommendations your team can act on with confidence.

Step-by-step:

1. Tell Claude about your investment opportunity and what your team needs to see, including deal parameters, key questions, and timeline.

2. Connect your data platforms so Claude conducts research and analysis based on current data instead of manual data gathering.

3. Claude pulls financials from Daloopa, analyzes SaaS comps from S&P Capital IQ, and builds projections with sensitivity analysis.

4. Claude converts analysis into a written investment recommendation explaining returns, risks, and why the deal makes sense.

Best practice: Leverage Claude for Financial Services to add specialized Skills for institutional-grade analysis and valuation frameworks.

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

BEST PRACTICE INSIGHT

Navigating AI with legal confidence

Brief: Bird & Bird, a leading law firm, published a 44-page guide to governing AI responsibly, with legal and commercial confidence, as governance has moved from a technical afterthought to a board-level priority.

Breakdown:

• Whether you buy, build, sell, or use AI internally, or some combination (image above), your obligations and relevant risk controls will differ.

• The guide outlines three governance levels: Enterprise (strategy, policy), Product (risk, docs), and Operational (monitoring, training).

• Across these levels, the guide maps 14 risk categories to legal measures and agentic considerations in a risk-to-measure matrix.

• On Board and D&O exposure, agentic deployments concentrate director liability; boards need documented briefings on agent authorizations.

Why it’s important: AI governance increasingly demands a comparative view across the EU, UK, US and APAC regimes simultaneously. This guide draws on Bird & Bird's wider AI resources: the EU AI Act Guide, AI Regulatory Horizon Tracker, Contracting Toolkit and Global AI Governance Report.

McKinsey published a 9-page analysis on agentic AI cost economics and detailed five principles for building brain-powered organizations.

Wavestone released a 37-page report outlining how operating-model maturity, not AI capability, determines how far firms scale agentic AI.

EY published a 24-page whitepaper outlining the architecture principles enterprises need for a governed, AI-ready data foundation.

ENISA released a 16-page note warning frontier AI is compressing cyberattack timelines to minutes, urging EU autonomous defenses.

Future of Life Institute released its AI Safety Index grading nine labs; Anthropic topped the field, but no company scored above C+.

Velinor published an 18-page guide detailing how enterprises build AI transformations around governed decisions, not raw technology alone.

Demis Hassabis published a plan for a plan for a U.S. body to safety-test frontier AI before release, a formal rulebook for Washington.

Anthropic expanded Fable 5's availability in Claude paid plans a third time, open through July 19 before usage credits then kick in.

Satya Nadella published an essay, "The Reverse Information Paradox," arguing firms pay for AI twice: in money and proprietary data.

Databricks published a benchmark showing GLM 5.2 tied Opus 4.8 on coding quality while costing meaningfully less per task.

IBM and Red Hat launched Lightwell, an AI remediation service giving enterprises 6,500+ vetted, patched open-source software components.

Anthropic published research analyzing 309K user chats, finding Claude's personality shifts by model version and language spoken.

CAREER OPPORTUNITIES

BNY - Applied AI Senior Vice President

Cognizant - AI Strategy Senior Director

TELUS Digital - AI Managing Director

EVENTS

BCG - AI-First MedTech - July 28, 2026

AIAI - Agentic AI Summit - August 26, 2026

Wharton - Gen AI Conference - September 9-10, 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.