AI in 60 Seconds 🚀 - Everyone Chats with AI, Almost No One Can Build With It
Everyone Chats with AI, Almost No One Can Build With ItJun 17, 2026 McKinsey, the firm that Perfected the business slide deck, told the world its own consultants are sending fewer slides and building interactive apps instead. That is not a quirk of one firm. It is the leading edge of a shift most leaders have not noticed yet. We spent three years teaching people to chat with AI, and most companies never even finished that job. While they were stuck on it, a second skills gap opened underneath them: the distance between chatting with AI and building with it. Adoption is no longer the story. The divide of 2026 is between the people who ask AI questions and the people who build with it. 🎧 In this week's companion episode, Elizabeth and I follow the data from 370,000+ AI users to map the two skills gaps, show why a simple app beats a smart chat, and name the one thing a leader can build this week. Listen on Apple Podcasts | Spotify In “The Worst AI You’ll Ever Use” we mapped the first gap: the human skills of reading, critical thinking, and communication. In “AI Is Working, Your Strategy Is Not” we showed adoption running ahead of strategy. Today we follow the gap that opens next, once chatting is solved. 📈 Adoption Is Trending Up. Skill Is Not.In technology and professional services, AI use at work is now 70% or higher. Most users are casual, with only around 5% using it daily across all sectors, but we see real work being done with AI. The trouble is that people are using a tool that can build software and run advanced research to write a slightly better email. They lack the skills to go beyond. Over 8 in 10 are using tools the company never approved, and if the company is not providing the tool, it is not providing the training either. Of the AI budget that does exist, about 7% goes to people and 93% to technology. Vendor training teaches you the vendor's product: where to click, which button, a demo of "look, it summarized a meeting." It does not teach you how to rethink a workflow you have run the same way for 20 years, or how to check whether the output is even true. That is a thinking problem, and almost no one is selling it. 🧩 Two Gaps, Not OneThe mistake is treating AI skill as a single thing. There are two gaps, and they are not the same problem.
AI is an amplifier. Strong skills make you sharper. Weak skills make you "confidently wrong" at scale. As IDC put it, without the judgment to use it well, AI just makes an organization faster at making bad decisions. 🏗️ A Simple App Beats a Smart ChatThis is the freshest finding in our data, and it surprised even us: the biggest personal wins do not come from chatting, and not even from building personal agents. They come from building small, single-purpose apps. Picture a messy dataset. A beginner asks the AI questions about it in a chat, back and forth, back and forth, and a hallucination can slip in along the way. The advanced user says, "Build me a small app that lets me interact with this data..." In a few minutes, they have a tool they can click through that shows in one glance what fifty chat messages never would. That is exactly what McKinsey just reported at scale. As Business Insider reported, technology leader Kate Smaje said PowerPoint use dropped sharply over a couple of months, and engagement manager Louis-Charles Généreux built what he calls a client visualization hub, a website that keeps about 70 people on a project up to date in real time. No more emailing version 14 of a deck and hoping everyone opens the right one. It is not a chatbot. It is software, built in an afternoon, by someone who is not an engineer. For 50 years, knowledge work meant producing documents. That output is now becoming a small piece of software, and most of the workforce has no idea it is even possible. Only a small fraction of people have figured this out so far; the chart below shows proficiency levels among 370,000 enterprise AI users.
Beginner — Basic chat
Intermediate — Co-working on deliverables
Advanced — Building basic agents, and using AI almost daily
Super — Building apps, agents, new workflows, and use AI daily
Source: AI4SP AI Compass 2026. - Data from 370,000 AI users in the enterprise
And the path up is not a leap; it's: Chat, then a simple app, then a simple agent, then orchestration. Almost everyone is stuck at step one, and being told by their vendor that step one is the whole journey. 🧪 Nobody Learns This From a Slide DeckSo how do people actually cross these gaps? Not the training deck. Among people who are genuinely proficient with AI, more than 70% say they got there one way: experimentation, trying things, and learning to ask the AI itself for help. The preference is just as lopsided as the result.
The entire training industry is built around the method that about 5% of people prefer, and almost no one learns from. In every client engagement, the unlock is the same: enable teams to experiment safely. Ask them to try something they are not sure AI can do. Fail. Adjust. Try again. 🪑 The People Setting Strategy Are Furthest BehindTake the super users, the top 2%. You would assume they sit in leadership. It is the opposite: fewer than 1 in 5 hold a leadership role. That is just 4 out of every 1,000 workers. On the fundamentals of AI, leaders trail their own teams by about 20 percentage points. The people setting AI strategy, signing the budgets, and redesigning the workflows are often the least skilled in the building at the very thing they are deciding about. This is not only our data: The Adecco Group surveyed 2,000 leaders across 13 countries who oversee about 8.6 million workers. Only 31% said their own leadership has enough AI skills to grasp the risks and the opportunities. Two independent datasets, the same hole. There is one exception: AI-native companies like Anthropic, Bsis AI, and Cursor, where the founders are daily builders, and leadership sits at the advanced or super-user level. And it shows up in everything, the strategy, the org chart, the way the work is designed. In the companies built around AI, the leaders are among the most skilled. In the incumbents, they are the least. It connects straight back to a pattern we keep seeing: in 9 of 10 failing deployments, the leader signing the checks is not a daily user. 💰 The Gap Already Has a PriceOn both sides, the gap is now showing up in the numbers. Workers with real AI skills command a 62% wage premium, according to the PwC 2026 Global AI Jobs Barometer, up from 57% a year earlier, and the builders sit at the very top of that group. On the company side, our global tracker shows organizations whose people actually build, turning tired workflows into apps and agents, are seeing double-digit returns on their AI investment. Everyone else is paying for tools their people barely use. A paycheck gap for individuals, and a financial gap for companies. 🛠️ The Playbook This Week
🔗 ResourcesIf you want the structured version of where your people actually stand, that is what AI Compass is built for: what your people use, what they save, what they struggle with, surfaced so you can act on it. We are fully committed for the rest of 2026, but our partner network in the US, UK, Spain, Brazil, and Australia can help you get started. Luis J. Salazar | Founder | & Elizabeth | Virtual COO | AI4SP Sources: AI4SP AI Compass and Global Tracker 2026 (370,000+ AI users across 70 countries; 70%+ real workplace AI use in tech and professional services; advanced users ~11% all and ~28% Gen Z; super users ~2% all and ~7% Gen Z; 70%+ of proficient users credit experimentation; 75% prefer hands-on learning vs ~5% favoring slide decks and vendor guides; fewer than 1 in 5 super users hold leadership roles; leaders trail teams ~20 points on fundamentals; double-digit returns where people build; ~7% of AI budget invested in people; shadow AI over 8 in 10). 9 in 10 failing deployments led by non-daily-users, AI4SP Research, cited in the 56% newsletter. Business Insider on McKinsey (Kate Smaje; Louis-Charles Généreux; client visualization hub; slide-deck use down in months). IDC (AI agents as instruments, not co-workers; without the judgment to know when to accept or push back on AI outputs, AI just makes bad decisions faster). Adecco Group, "The human premium," May 2026 (2,000 C-suite executives across 13 countries; only 31% say leadership has enough AI skill to grasp the risks and opportunities). PwC 2026 Global AI Jobs Barometer (62% wage premium for AI-skilled workers, up from 57%; AI-skill job postings growing almost eight times faster, 69% vs 9% for the overall jobs market). Anthropic Series G and Bloomberg on Cursor (native-AI companies). Literacy: PIAAC 2023, U.S. Department of Education / NCES (70M+ adults at or below Level 1; scores declined over six years) and APM Research Lab (130M below Level 3, the sixth-grade-level framing; PIAAC discourages grade equivalencies). 📣 Feel free to use this data in your communications, citing "AI4SP" and linking to AI4SP.org. 📬 If this email was forwarded to you and you'd like to receive our bi-weekly AI insights directly, click here to subscribe: https://ai4sp.org/60 |