My mother never followed a recipe.
She cooked from memory, from feel, from years of standing at the stove learning what worked. Her comadres would come over, watch her cook, and ask: "How do you know when it's ready?" She would shrug and say, "You just know."
But here is the part nobody saw. Behind the intuition was a system. Her pantry was always stocked the same way. Her spices were in the same spot. Her process was the same every single Sunday: prep the night before, start early, adjust as she went. It looked effortless because everything behind it was intentional.
I think about her kitchen every time I watch someone try AI for the first time. They open ChatGPT or Claude, type a question cold, get a mediocre answer, and walk away thinking: "That wasn't worth the hype."
But that is like walking into my mother's kitchen with all the same ingredients and expecting the same plate to appear. You had the tools. You did not have the system.
This week, two major studies confirmed what I have been seeing firsthand: the gap between people who tinker with AI and people who have built AI into how they actually work is no longer small. It is a canyon. And it is getting wider.
My mother would have had a phrase for this.
No es lo mismo predicar que dar trigo. It is not the same to preach as to give wheat.
In other words, talking about AI is not the same as doing something meaningful with it. And right now, most companies and most professionals are still preaching.
THIS WEEK'S INSIGHTS
The data landed this week, and the picture is clear. Having AI is not the advantage. Knowing how to use it is.
1. 74% of AI's economic value is going to just 20% of companies. PwC's new study of 1,217 executives dropped on April 13, and the headline number should stop every leader in their tracks.
2. AI adoption is now faster than the PC or the internet. Stanford's 2026 AI Index confirms that generative AI reached 53% global adoption in just three years. But speed of adoption does not mean depth of adoption.
3. The gap is not about tools. It is about systems. The companies winning are not using more AI. They are using it differently. They redesigned workflows. They built foundations. They pointed AI at growth, not just efficiency.
TRENDS
Two of the most comprehensive AI studies of the year dropped this same week. Here is what they found and why it matters for you.
PwC: The 74/20 divide is real, and it is widening. PwC's 2026 AI Performance Study, released April 13, surveyed 1,217 senior executives across 25 sectors. The finding: 74% of AI's economic value is being captured by just 20% of organizations. The top performers are generating 7.2 times more AI-driven revenue and efficiency gains than the average company. And the difference is not that they have better tools. It is that they use AI as a reinvention engine, not just a productivity shortcut.
Think of it like two people who both joined the same gym. One shows up, does random machines for 20 minutes, and leaves. The other has a program that tracks progress and adjusts every week. Same gym. Same equipment. Completely different results.
Stanford: AI is spreading faster than any technology in history, but most people are barely scratching the surface. The 2026 Stanford AI Index reports that generative AI reached 53% population adoption in just three years, outpacing both the personal computer and the internet. But here is the nuance: the U.S. ranks 24th globally in adoption at just 28.3%. And 88% of organizations say they have adopted AI, yet the vast majority are still stuck in pilot mode, running experiments that never scale into how they actually operate.
80% of companies are stuck in pilot purgatory. This is the term that keeps showing up across the research. Companies launch AI pilots, build dashboards, run demos, and produce slides. But they never move AI into the workflows and decisions that drive real results. McKinsey found that nearly two-thirds of organizations have not begun scaling AI enterprise-wide. MIT found that 95% of generative AI pilots deliver no measurable business impact. The pattern is the same: impressive experiments, zero operational change.
The winners are redesigning workflows, not layering tools on top of old ones. PwC found that leading companies are twice as likely to have redesigned workflows around AI, rather than simply adding AI to existing processes. They are 2.6 times more likely to say AI improves their ability to reinvent their business model entirely. The strongest factor driving AI performance is not efficiency. It is using AI to pursue new growth opportunities across industry lines.
3 MYTHS TO REFRAME
These are the beliefs keeping smart professionals from making the shift from pilot mode to real results.
Myth #1: "I use AI, so I'm ahead."
Why we believe it: We signed up for the tool. We ask it questions. We feel productive. That must count for something.
Reframe: Using AI is table stakes. The PwC data shows that 80% of companies are using AI and still not capturing meaningful value from it. Having the tool is not the advantage. Building a system around it is. Last week I wrote about AI atrophy: the risk of letting AI dull your skills. This week's data shows the other side: the risk of using AI without a plan is that you stay busy but never move forward.
What to do: Stop asking "Am I using AI?" and start asking "Have I changed how I work because of AI?" If the answer is no, you are in the 80%.
Myth #2: "AI is mostly about saving time."
Why we believe it: Every AI pitch leads with efficiency. Faster emails. Quicker summaries. Less busywork.
Reframe: PwC found that the companies capturing the most value from AI are not focused on time savings. They are focused on growth, reinvention, and new revenue. Efficiency was not the strongest factor driving AI performance. Pursuing opportunities across industry boundaries was. Time savings is the floor, not the ceiling.
What to do: The next time you sit down with AI, skip the quick task. Instead, bring it a harder question: "What am I missing in my strategy?" or "Where could my business expand that I have not considered?" Use AI to think bigger, not just move faster.
Myth #3: "I'll scale AI when I'm ready."
Why we believe it: It feels responsible to wait, to learn more, to run another pilot before committing.
Reframe: The data says the gap is widening, not closing. Companies that are ahead are learning faster, scaling proven use cases, and compounding their advantage. Waiting is not caution. Waiting is how you fall further behind while believing you are being strategic. PwC's Global Chairman said it plainly at Davos: 2026 is the year companies have to prove AI can return value.
What to do: Pick one workflow this week. Not a side project, not a test. A real workflow you do every week. Redesign it with AI at the center. Run it for 30 days. Measure the difference.
TOOLS TO EXPLORE
This week, try the following tools and Prompts to Steal to help you move from tinkering to building a real system.
Claude Cowork as your AI workflow partner
Prompts to steal:
"I want to redesign how I [weekly workflow]. Read my context files first. Then walk me through the current steps I am likely taking, suggest which ones AI should handle, and flag the steps where my judgment is irreplaceable. Ask me questions before you build the new workflow."
Power tip: Cowork mode lets Claude pull directly from a folder on your computer, so it arrives knowing your context before you type a single word. This is the difference between a cold start and a warm partnership.
Perplexity as your strategic research engine
Prompts to steal:
"I work in [industry]. Show me three examples of companies that use AI to pursue growth opportunities outside their traditional sectors. Include the source and the date for each. Then ask me three questions about my own business to identify where I might do the same."
Power tip: Use Perplexity's Pro Search for this one. It aggregates real-time data with citations on every sentence, so you can verify before you act. This is how you move from reading about trends to applying them.
NotebookLM as your competitive intelligence tool
Prompts to steal:
"I have uploaded [industry report/earnings call/competitor analysis]. Summarize the three most important strategic moves mentioned. Identify patterns I should pay attention to. Do not use any information outside of these documents."
Power tip: NotebookLM only answers from what you upload. That means no hallucinations, no guessing. When you are making strategic decisions, grounded answers from your own sources beat general AI output every time.
TRY IT THIS WEEK (Micro Actions)
These are designed to take you from knowing to doing. Share these with the leaders in your circle.
1. Run the 74/20 self audit. Ask yourself honestly: Am I using AI to save time, or am I using it to change how I work? If your answer is "save time," you are likely in the 80%. Write down one workflow you could redesign this week. Not automate. Redesign.
2. Build your first AI system, not just a session. Open Claude, create three simple files (who you are, how you think, what you need), point Cowork at that folder, and run one real task through it. Notice how different it feels when AI starts with your context instead of a blank page.
3. Ask a growth question, not an efficiency question. This week, instead of asking AI to do something faster, ask it to help you think bigger. Try: "Based on what you know about my work, what adjacent opportunity am I not seeing?" The answer might surprise you.
POWER TIP
The PwC study found that the strongest driver of AI performance is not efficiency. It is using AI to find growth opportunities across industry lines. Most people never ask AI to do this because they are stuck thinking of it as a tool for tasks. This week, shift the frame. Ask AI to help you see what you are not seeing. That is where the real value lives.
👉 Are you in the 20% or the 80%? Be honest with yourself. Then do something about it.
Closing Thought
AI is not the advantage. Your system is.
The companies pulling ahead are not using more tools. They are using them with more intention.
Last week, I wrote about keeping your brain sharp while using AI. This week, the data confirmed why that matters. The professionals and organizations capturing the most value are those who stayed in the loop, built real systems, and pointed AI at growth rather than just speed.
The wheat is on the table. It is time to stop preaching and start planting.
♻️ Share this with a leader who is still stuck in pilot mode.
¡Hasta la próxima, un abrazo fuerte! (Until next week, a big hug!)
Monica Marquez
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