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Why only 2% of AI users save 100s of hours (and you are not)?

Oct 22, 2025

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I just came back from a roadshow in California. In every interaction with business leaders, scientists, and students, there is excitement about the AI promise, but adoption is rocky. They all asked the same question in different ways: “How do I build my own agent?”

Everyone is using AI, but they feel stuck

An actress created her agent to support her career. A neuroscientist needed an AI chief medical officer to brainstorm with. A COO told me his team creates new agents weekly and isn’t hiring new team members unless they can demonstrate this skill.

And students? Over 80% use AI, and they’re asking if building agents will eliminate hallucinations and if that would count as “cheating.”

These stories all point to the same massive gap in the professional world:

Over 55% of us now use AI at work, but only 2% are building our own agents.

The secret to running a company with 50 agents, or saving 3,000 hours like Agent Ada did, isn’t about technical wizardry. It’s about making that one simple shift: from user to maker.

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🎯 The Question Everyone’s Really Asking

After our Agent Ada episode, my inbox exploded with variations of the same question:

The answer isn’t a complex new tool. It’s about understanding what’s actually possible and giving yourself permission to stop just using AI and start building with it.

When you feel that frustration, you’re not alone. You’re just hitting the ceiling of what it means to be a “user.” The data tells the real story:

The Reality Check:

• 📊 Over 800 million people now use ChatGPT weekly.
• 📉 But our data shows only 2% are creating their own agents.
• 📈 Yet 40% of knowledge worker job postings already require AI skills.
• 🎯 And 20% of personal agents get shared with teams, sparking grassroots transformation from the bottom up.

This gap between use and creation is the single most significant opportunity for professionals right now. It all starts with a simple change in perspective.

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🔄 The Maker Mindset Shift

What Most People Do:

What Makers Do:

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🛠️ The Three Components

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🏗️ The New AI Landscape: From Apps to Agents

The most important strategic shift happening right now is the move from an app-centric to an AI-centric world.

In the new model, the AI agent becomes the operating layer itself.

Your agent’s job is to manage your tools for you: your Microsoft Office, your Google Workspace, your Slack, and your email.

This is why “building an agent” is an entirely different (and more powerful) concept than just “using AI.”

Top-down enterprise mandates aren’t driving this massive shift. It’s a grassroots revolution, and it follows a clear pattern: Consumer ➡️ Prosumer ➡️ Enterprise.

Two-thirds of the AI agent and workflow companies we track start with a simple, personal product. Individuals (consumers) adopt it, prove its value, become “prosumers” by building with it, and then bring that new capability into their teams and, eventually, the entire enterprise.

Where the “Maker” Journey Begins

This grassroots model explains why the agent-building journey almost always starts with ChatGPT. It’s simply where people are.

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Why the ‘Maker’ Model Wins: The 90-Day Proof

The data becomes even clearer when we focus on what endures. Initial adoption is one thing; sustained daily use is another.

Our research tracking 90-day agent “survival rates” shows a stark difference between bottom-up ‘maker’ agents and top-down corporate tools. Personal agents built by individuals have three to four times better retention.

The grassroots model doesn’t just feel better; it works better.

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🎓 Why This Matters NOW

For Students:

• Building agents provides a clear competitive differentiation for internships and first jobs.
• It’s not “cheating”; it’s building the AI management skills that the COO from our intro is already hiring for.
• Our data shows 40% of students report a positive impact on their academic performance thanks to AI tutors.

For Professionals:

• Professionals with agent-building experience are seeing 35% to 45% higher compensation.
• It’s also about work-life balance. Of the time saved, 33% is used to improve work-life balance, and 40% is reinvested in higher-quality, creative work.
• This is how you scale your decades of expertise—amplifying your impact without a proportional increase in your hours.

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🔮 Your One More Thing: The 48-Hour Challenge

I started this by sharing the one question I hear everywhere: “How do I build my own agent?”

My “one more thing” is simple: Stop asking, and start building.

Stop thinking about AI as something you use. Start thinking about it as something you build with and manage daily.

The shift is here. The tools are accessible. The gap between the 55% of users and the 2% of makers isn’t a technical barrier—it’s a single decision.

Here is your 48-hour challenge.

• Pick one repetitive task that drains your energy.
• Open ChatGPT and write a one-sentence “job description” for an agent to do that task.
• Give it one document; it needs to do that job.

The moment you do that, you’ve made the leap. You’re not a user anymore. You’re a maker.

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🚀 Take Action

• Check potential AI impact: Use our AI ROI Calculator
• Private Access to our AI Compass to assess team readiness for AI, grassroots AI maturity, and opportunities to channel shadow AI. (Contact Luis to get a private access link)
• Workshops & Training: Book sessions for your team
• AI Management Certification - For enterprise groups of 15-20 individuals.

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✅ Ready to transition from a traditional organization to an AI-powered one?

We advise forward-thinking organizations to develop strategic frameworks for evaluating, integrating, and optimizing human-AI production units. Let’s discuss how this applies to your organization. Contact Us.

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Luis J. Salazar | Founder & Elizabeth | Virtual COO (AI)

AI4SP

Sources:

Our insights are based on over 250 million data points from individuals and organizations that used our AI-powered tools, participated in our panels and research sessions, or attended our workshops and keynotes.

📣 Use this data in your communications, citing "AI4SP" and linking to AI4SP.org.

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