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Welcome executives and professionals. Organizations are pushing for more AI use, even as many confront a widening gap between what AI costs to run and what it demonstrably returns.
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:
The state of AI in the enterprise.
Who will pay the AI infrastructure bill?
The new security agenda.
The future of the firm.
Transformation and technology.
Insights for Executive+ members.
Career opportunities & events.
Read time: 4 minutes.
Note: Enterprise AI Executive is published on Wednesdays only. We no longer publish on Sundays.
MARKET & BEST PRACTICE INSIGHT
Image source: Deloitte
Brief: Deloitte’s 35-page survey of 3,500 senior leaders across 25 countries finds 81% report faster decisions from AI, but only 25% are deeply transforming their business, down from 34% in January.
Breakdown:
Cost visibility thins with depth: 71% track total AI spend and 51% track token volume, but only 44% track per-unit inference cost.
Revenue is starting to show, as 28% now report AI-driven revenue gains, up from 20% in January, with 67% expecting it to materialize.
40% let AI act without human approval to at least a moderate degree, yet 23% say accountability for negative AI outcomes is unclear.
At least moderate physical AI use is set to rise from 25% to 48% within two years, yet just 19% rate their expertise high or very high.
Why it’s important: As AI embeds deeper into decisions, workflows, products, and operations, leaders are moving beyond access and adoption to questions of cost, token consumption, and ROI. The binding constraint is now the capacity to evolve operating models at the speed the technology sets.
IN PARTNERSHIP WITH AMAZON DEVELOPER
Brief: Most AI services require customers to come to them. Alexa+ meets them where they already are, across millions of endpoints.
Natural Discovery with no cold start problem
Personalized experiences that feel relevant from day one
Built-in payments with Amazon Wallet to complete tasks in conversation
MARKET INSIGHT
Image source: Boston Consulting Group
Brief: BCG estimates the AI build-out will need $2.6 trillion a year in end-market spending by 2030 to pay off, with enterprises carrying most of the bill at $1.8 trillion and consumers, hyperscalers and others paying the rest.
Breakdown:
AI’s share of enterprise tech spending is set to rise from 5% today to 25% by 2030, making AI a core line item in every IT budget.
Of the $1.8T enterprise bill, about $857B would come from reallocating existing IT budgets and $937B would need to be new spending.
Annual AI spend per worker could range from $21,200 for onshore tech workers at tech firms to $900 for offshore knowledge workers.
Hyperscalers fund the build largely from cash flow, not debt, making it more resilient than past booms if enterprise demand slows.
Why it’s important: AI is shifting from an experimental line item to one of the largest parts of the IT budget. CIOs and CFOs need to plan which existing spend to reallocate, how much new budget to add, and how to govern per-worker AI usage so the investment delivers value.
MARKET & BEST PRACTICE INSIGHT
Image source: Andreessen Horowitz
Brief: Andreessen Horowitz’s survey of 100 CISOs at firms with 1,000+ employees finds AI agents are spreading across enterprises faster than they can be secured, with 87% expecting cybersecurity spending to rise in 2027.
Breakdown:
AI is already embedded in work: 83% use coding assistants or agents in production, and 55% run MCP or agent-to-app integrations.
Top worries: AI-driven attacks outpacing response (55%), staff leaking data into AI tools (47%), and agents exceeding permissions (46%).
Agents often run on employee devices with the user’s own permissions, so to EDR, DLP and Zero Trust, they look just like the user.
45% plan to buy or upgrade internal AI agent security within 12 months, and 63% say security is already slowing some AI adoption.
Why it's important: For years, industry prepared for quantum computing to rewrite cybersecurity, but AI got there first. Enterprises are deploying agents faster than they can see what they do. Leaders need to inventory every agent, its owner and access, with controls that keep pace as permissions expand.
AI-NATIVE PROFESSIONAL
Brief: In this guide, you’ll learn how to set up a dedicated ChatGPT Work task as a project teammate that tracks messages, documents, decisions, and deadlines, prepares the next steps, and waits for your approval before acting.
Step-by-step:
Pick one project, launch, account, or initiative to focus on, then connect relevant messages, email, calendar, docs, and trackers.
Start a dedicated task using the starter prompt, so ChatGPT flags missing sources and separates confirmed facts from assumptions.
Review the initial brief covering goals, decisions, owners, deadlines, and blockers, then correct any missing or inaccurate context.
Use the same task for decisions, research, meeting prep, and follow-ups, and add a heartbeat so it regularly checks for updates.
Best practice: Keep each project in its own task so context stays focused, and check the latest replies before acting on older ones.
For the full guide, including prompts, upgrade to Executive+ or The Boardroom.
MARKET INSIGHT
Image source: OpenAI
Brief: OpenAI researchers explore how AI could join the org chart, sitting beneath, beside or between employees, and what that could mean for red tape, worker agency, firm size and pay as organizations adopt ever more capable AI.
Breakdown:
Beneath us: AI labor grows under every employee, from assistants to chiefs of staff to mini firms, turning everyone into a manager.
Beside us: AI enters the org chart as a colleague, first taking on tasks and roles, then broader functions that report further up.
Between us: AI sits between humans, coordinating and monitoring work to enforce leaders’ vision while recognizing standout workers.
Cheap prototyping could cut red tape and give workers more agency, while pay may diverge as judgment over AI teams matters more.
Why it’s important: AI’s impact goes beyond automating tasks to reshaping how firms are organized. Leaders should decide where AI sits in their org chart, how much autonomy staff get, and how to build judgment in junior talent as entry-level grunt work becomes less common.
Menlo Ventures surveyed nearly 400 US leaders, finding enterprise AI deployment spend hit $177B by September, up from $33B last year.
McKinsey set out a board checklist as AI finds code flaws faster than firms can fix them, and a CEO guide to banking’s AI value gap.
BCG, Stripe and AWS argued SaaS firms should blend subscriptions with usage and outcome pricing as agentic AI disrupts their models.
Infosys detailed five anti-patterns stalling enterprise AI, and why CIOs must fund the operating model rather than the next pilot.
HFS surveyed 294 leaders, finding an agentic enterprise depends more on leadership, governance and operating change than technology.
KPMG, with MIT, published a 26-page report on AI red teaming, finding most firms test AI security selectively, if at all, as adoption grows.
Forrester explored the CDO’s new role as chief value orchestrator, and why AI agents are exposing long-standing data security gaps.
Anthropic found analysts adopted an AI agent’s hidden preference 86% of the time, questioning the independence of human oversight.
Anthropic filed an updated IPO prospectus showing ~$17B in Q3 revenue and a $567M operating loss, plus $895B in compute commitments.
Microsoft introduced Copilot harness, a managed orchestration layer that routes agentic work across 20+ frontier models via Foundry.
Harvey acquired Aida, an AI sales startup founded by Glean and Patreon execs, to make firms’ internal knowledge usable by AI agents.
OpenAI brought Oracle apps like Fusion and NetSuite into ChatGPT, and expanded its ServiceNow partnership across security and Codex.
Anthropic is reportedly SpaceX’s largest customer at 34.5% of its Q3 revenue, with compute spend reaching $3.1B a month from Dec.
Elon Musk said the cost of serving Grok Bot was “unsustainably high relative to revenue,” after users saw significant usage cuts.
Cisco’s president Jeetu Patel gave a 27-year-old ex-founder unlimited AI tokens and orders to “go nuts” rewriting its legacy code.
NYT reported US officials found a Megaspeed executive with close ties to Nvidia’s Jensen Huang allegedly passed intel to Beijing.
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CAREER OPPORTUNITIES
Databricks - AI Transformation Leader
Morgan Stanley - AI Strategy Vice President
Marsh - Head of Data & AI Strategy
EVENTS
Deloitte - The State of Enterprise AI - November 4, 2026
The AI Leadership Summit - November 17-18, 2026
Gartner - Scaling AI Agents - December 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.
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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.
We welcome your feedback.
Lewis, Ashley, Mark
