Your AI strategy isn't a technology problem. It never was. A thread for CEOs and executives who need to hear this 👇 🧵

For NeeDOH lovers and gifts Great gal to follow and shop from on WhatNot whatnot.com/s/qeA1BJVp

Vast majority of organizations are so far behind…so true

Most CEOs are underestimating what AI can already do for them. Not writing emails. Not summarizing documents. This past weekend, I: → Rebuilt and relaunched my website → Built an AI Chief of Staff that preps my meetings, puts the key numbers in front of me with my morning coffee, and challenges my decisions before I make them A few years ago, the first meant an agency and a few weeks. The second meant another person on the team. Now you can go from "I wonder if we could do this?" to "It's working." in a weekend. The real opportunity isn't doing today's work faster. It's gaining capabilities you didn't have last week. And once you've built something yourself, your AI conversations with your team change. They stop being vague. They get specific. So skip the massive transformation plan. Build something useful. Solve one real problem. Then ask your leadership team: Not "How can we use AI?" But "What can we do now that we couldn't do before?"

Four of the five ways AI moves your P&L aren't sales. Most CEOs only fund the fifth. Cost. Productivity. Speed. Acquisition cost. Then sales. Efficiency alone is where most AI budgets quietly go to die.

80% of companies set efficiency as their AI objective. 39% report any EBIT impact. The gap isn't the technology. It's that efficiency is one of five levers and most CEOs only fund one of the other four by accident.

Four of the five ways AI moves your P&L aren't sales. Most CEOs only fund the fifth. The five levers: Lower operating costs — every dollar permanently out of operations flows almost dollar-for-dollar to operating profit. Higher productivity — hours reclaimed from reporting, quoting and data entry get redeployed into work that creates value. Faster execution — a proposal in 2 days instead of 2 weeks wins business you're losing today because someone else moved faster. Better customer acquisition — sharper targeting and follow-up that doesn't go cold lowers what every new customer costs you. Direct sales lift — real, but rarely the first place to look. McKinsey: 80% of companies set efficiency as an AI objective. The ones capturing the most value set growth or innovation as objectives too. Only 39% report any EBIT impact at all. Efficiency alone is where most AI budgets quietly go to die. That's a strategy question, not a software question. Answer it before buying another tool.

Your employees didn't wait for an AI strategy. They built one without you. I recently asked a CEO how much his company spends on AI. He gave me his Salesforce number to the dollar. The AI number took a week and came back as a range. - Marketing has one platform. - Sales is testing another. - Someone in ops built a workflow that saves hours a week. - Finance has its own tools. None of it is bad. The problem is that AI adoption is moving faster than AI ownership. Six months from now, those experiments will become embedded workflows, duplicate subscriptions, and disconnected data before anyone decides what should scale. Then the board asks, "What are you getting back from all that AI spend?" Nobody has a clean answer. I don't start by recommending another tool. I start by mapping what exists, what's being used, who owns the outcome, and what's actually producing value. If leadership can't see the company's AI activity on one page, buying more AI isn't the next move. Visibility is.

AI just got 80% cheaper. Your competitive advantage didn't. Three weeks after launching GPT-5.6, OpenAI cut the price 80% — then announced a billion active users the next day. Here's what those two facts mean for every CEO: Access to intelligence is no longer an advantage. Your competitors run the same models you do. So does the 22-year-old founder coming for your market — at 20 cents per million tokens. When a resource gets radically cheaper, value migrates. Computing got cheap → advantage moved to software. Software got cheap → advantage moved to distribution. Intelligence is getting cheap → the advantage is moving to integration and orchestration. The winners won't be the companies with access to AI. Everyone has access. They'll be the ones who rewired real workflows around it: the proposal that drafts itself overnight, the ticket resolved before the second email, the report nobody builds anymore. Cheap intelligence is the great equalizer. Execution is now the differentiator. The price of AI dropped 80%. The price of waiting just went up. If intelligence were free tomorrow, what's the first workflow you'd rebuild?

You can buy the ad slot next to ChatGPT's answer. You still can't buy the answer. 51% of B2B buyers now start vendor research in an AI chatbot — not Google. Here's what that means for your brand: Yes, ChatGPT sells ads now. But they sit below the answer, clearly labeled, and only reach free and low-cost tiers. The recommendation itself is still earned. And the recommendation is where the money moved. G2's 2026 Answer Economy report: 69% of buyers chose a different vendor than planned because of AI guidance. 1 in 3 bought from a vendor they'd never heard of before the conversation started. Forrester found 94% of business buyers used AI in their most recent purchase. The shortlist is being written before your website gets a visit. How brands earn their way in: → Content that answers real buyer questions, not keyword bait → A site structured so AI can extract and cite it (I just saw this up close: a client's redesign looked great to humans — the AI couldn't read some of the key data behind the code) → Third-party trust: reviews, citations, mentions Visibility isn't given anymore. It's earned. Quick test: ask ChatGPT, Claude, Gemini, or Perplexity what they say about your company. If the answer surprises you, your buyers already saw it first.

MIT studied 300 enterprise AI deployments. 95% delivered zero measurable ROI. The 5% that worked didn't chase pilots. They picked one workflow, went deep, and measured P&L. The winners weren't smarter. They were narrower. Which workflow would you automate first?