Edition sponsored by

Welcome executives and professionals. Throughout history, significant technological advancements have driven major innovations. The AI era offers the opportunity to create the next generation of trillion-dollar companies.

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.

Note: Previously published as Generative AI Enterprise, this briefing is now titled Enterprise AI Executive.

In today’s briefing:

• The next trillion-dollar opportunity.

• Rethinking software pricing for agentic AI.

• Responsible AI insights from 1,500 executives.

• The rise of generative engineering.

• Transformation and technology in the news.

• Career opportunities & events.

Read time: 4 minutes.

OPPORTUNITY INSIGHT

The next trillion-dollar opportunity

Brief: Sequoia examined eight historical retail technology shifts, from mass production and cash registers to mobile apps, and projects a future Amazon-scale opportunity in AI worth over $2T. Here are five ways it could manifest.

Breakdown:

• AI addresses complex customer questions, guiding consultative purchases when buyers know their problem but not the product.

• Purchases completed directly within AI chat interfaces (e.g. ChatGPT, Gemini, Perplexity) through connected MCP servers.

• Future “Amazons” proactively ship items a customer may want, charging only if the customer chooses to keep them.

• Autonomous vehicles operating as mobile storefronts, roaming constantly to provide a continuous flow of available products.

• Computer vision and AI predict shopping needs, plan recipes from pantry footage, and automatically order missing ingredients.

Why it’s important: Retail, a $7T market in the U.S. alone, transforms with each major tech leap. AI offers a chance to reinvent the industry. History hints at how AI-native companies might reshape retail, but it’s up to today’s innovators to make these experiences a reality.

PRESENTED BY STACKAI

Explore 15+ real-world AI agent use cases

Brief: Discover how AI agents are enabling finance teams to reduce manual tasks, accelerate decision-making, and scale operations across banking, insurance, and investment management.

• Build secure AI agents on StackAI to automate workflows with ease.

• Launch AI agents with enterprise-grade governance, integrations, and secure deployment options.

• Protect sensitive data at scale with built-in SSO, access controls, and domain restrictions.

Download the free guide now.

BEST PRACTICE INSIGHT

Rethinking software pricing for agentic AI

Brief: BCG explores pricing strategy shifts over the past decade from perpetual licenses to subscriptions and toward consumption models, with AI agents driving even closer links between price and value delivered.

Breakdown:

• The shift from seat-based to agent/outcome-based models is expected to continue, though incumbents transitioning face revenue risk.

• Hybrid pricing will emerge, combining subscriptions with agentic models to balance vendor revenue stability and customer predictability.

• Agent-based pricing will rise as developers increasingly build multiple, task-specific subagents, agents replace human labor, and volume grows.

• Outcome-based pricing will expand among managed-service vendors, tying charges to completed jobs as customers seek clear value measures.

• Vendors will combine models, most often agent/outcome-based, to monetize both agent capabilities and the value of work delivered.

Why it’s important: Enterprises should assess whether their AI solutions deliver unique value that justify standalone packaging. Transition to outcome-oriented pricing models, while managing revenue volatility risks. Invest in usage forecasting, and customer success programs for sustainable adoption.

MARKET INSIGHT

Responsible AI insights from 1,500 executives

Brief: Infosys surveyed 1,500 executives across North America and other Western countries, revealing in a 34-page report the scale of AI risks and gaps in enterprise capabilities to safely deploy AI.

Breakdown:

• Nearly all executives (95%) report at least one AI incident, including inaccurate predictions, with 39% rated severe/extremely severe.

• Most incidents (77%) cause direct financial loss, yet executives find reputational damage as a greater threat to business success.

• RAI practices are viewed as drivers of growth, and most executives welcome new AI regulations to provide clarity, confidence, and trust.

• RAI spending makes up 25% of AI budgets, yet financial losses from AI incidents are just 8%, indicating a high-risk premium.

• As agentic AI adoption grows, 86% of enterprises anticipate higher risks, but only 2% are RAI leaders across governance and risk mitigation.

Why it’s important: As agentic AI systems operate with increasing autonomy, embedded RAI safeguards are business-critical. Rather than bolt-on, RAI should be integral, with dedicated resources supporting use case identification and ensuring governance, trust, and risk mitigation across the enterprise.

BEST PRACTICE INSIGHT

The rise of generative engineering

Brief: BCG X, BCG’s technology arm, examined how many organizations are redefining how software is built, who builds it, how fast it can be delivered, and introduced five levels of generative engineering.

Breakdown:

• Forward-leaning firms are already embracing this shift. At Google and Microsoft, about 30% of all new code is now AI-generated.

• Engineering isn’t ending but evolving: less manual, more strategic. Experienced developers remain critical for secure, production applications.

• Developers can ship more features, faster. Some teams report 20x, 50x, even 100x increases in feature output versus manual coding.

• The spectrum of AI coding autonomy ranges from those who reject AI assistance to the full agentic "Vibe Coder" model (see image above).

• Enterprises/developers should advance to remain competitive. Banks may begin at L1–L2, while YC startups may start at L3–L4.

Why it’s important: AI coding tools won’t deliver massive productivity gains overnight, and not all tools fit every tech stack. Success comes from thoughtful adoption, clear guardrails, fostering behavioral change, and evolving development processes to fully leverage AI capabilities.

KPMG explored how Shadow AI, unsanctioned tool use without the explicit approval or oversight, is outpacing enterprise controls.

OpenAI showed how Basis’ AI agents, built with o3, o3-Pro, GPT-4.1, and GPT-5, cut accounting workloads 30% and expand advisory capacity.

Alvarez & Marsal shared 23-page report on “strategic patience”: late movers can beat early adopters by learning from missteps and entering as AI matures.

McKinsey outlined five steps for change management in the gen AI era and how agentic AI is poised to disrupt retail and SME banking.

PwC urged boards to match AI’s velocity, and how AI agents make IT a strategic driver for faster delivery, smarter decisions, and broader impact.

AWS published 79-pages on operationalizing agentic AI, and how it's building automated responsible AI reasoning checks with PwC.

EY published a 32-page report on the IT services shift: decoupling scale from headcount, hybrid human+AI pods, and skill-first career development.

Deloitte shared a 28-slide report gen AI adoption in retail and consumer products sectors, and how banks can further automation with agentic AI.

OpenAI CEO Altman announced changes to ChatGPT after GPT-5 backlash, restoring 4o, expanding rate limits, and adding model choice controls.

Google announced several new Gemini features, including temporary chats and user preference learning, and released Gemma 3 270M.

Anthropic introduced new memory capabilities for Claude’s Max, Team, and Enterprise tiers, and offered US federal government access for $1.

The U.S. government is reportedly placing tracking devices in Nvidia and AMD AI chip shipments, and is set to take a 15% cut of chip sales to China.

DeepSeek’s highly anticipated R2 model is reportedly facing delays due to training issues on Huawei’s Ascend chips, despite rumors of an August launch.

Mistral unveiled Medium 3.1, an upgraded model that shows improvements in overall performance and creative writing.

Cohere raised $500M at a $6.8B valuation and appointed Meta’s Joelle Pineau, VP of AI Research, as its new Chief AI Officer.

xAI is suing Apple, alleging App Store bias toward OpenAI’s products and suppression of rivals like Grok. Sam Altman accused X of similar practices.

CAREER OPPORTUNITIES

J.P. Morgan - AI Executive Director

Michael Baker International - AI Vice President

EPAM Systems - AI Delivery Director

EVENTS

Anthropic - Deploying Multi-Agents - August 27, 2025

Everest Group - Agentic AI in HR - September 9, 2025

Gartner - AI Cost, Risk & Value - September 16, 2025

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

If your AI product or service adds value to this audience, contact us for information on a limited number of sponsorship opportunities.

We also welcome feedback as we continue to refine the briefing.