Your Transformation Station - 137. AI at Work 2026: Why Adoption Has Stalled but Power Users Are Pulling Ahead

Episode Date: February 17, 2026

AI isn’t sweeping across the workforce the way the hype promised — but something far more important is happening beneath the surface. Gallup’s newest national Workforce Study reveals a surprising shift: AI adoption has stalled, but AI mastery is accelerating. A small group of power users is pulling ahead while the rest of the workforce stands still. In this episode of Your Transformation Station, Gregory Favazza breaks down the latest Gallup data to uncover what’s really happening inside American organizations. You’ll learn: Why nearly half of U.S. workers still never use AI Why daily and frequent AI use continues to rise How leaders use AI 2× more than their teams Why remote‑capable roles are adopting AI at double the rate of on‑site workers Which industries are accelerating — and which are falling behind What employees actually use AI for (hint: it’s not coding) The #1 barrier stopping organizations from wider adoption Gregory also explains how Gallup collects this data, why it’s considered the gold standard for workforce insights, and what these trends mean for the future of work, leadership, and digital capability. If you want to understand the real state of AI in the workplace — beyond the hype — this episode gives you the clarity and data you need. Sources Gallup. (2025). AI in the Workplace: 2025 Workforce Trends. Gallup Workforce Study, Q4 2025. Gallup, Inc. IBM SkillsBuild. SkillsBuild Learning Platform. https://skillsbuild.org PODCAST INFO: Podcast website: ⁠⁠https://www.ytsthepodcast.com⁠⁠ Apple Podcasts: ⁠⁠https://www.ytsthepodcast.com/apple⁠⁠ Spotify: ⁠⁠https://www.ytsthepodcast.com/spotify⁠⁠ RSS: ⁠⁠https://www.ytsthepodcast.com/rss⁠⁠ YouTube: ⁠⁠https://www.ytsthepodcast.com/youtube⁠⁠ SUPPORT & CONNECT: - Facebook: ⁠⁠https://www.ytsthepodcast.com/facebook⁠⁠ - Instagram: ⁠⁠https://www.ytsthepodcast.com/instagram⁠⁠ - TikTok: ⁠⁠https://www.ytsthepodcast.com/tiktok⁠⁠ - Twitter: ⁠⁠https://www.ytsthepodcast.com/x⁠⁠ - Pinterest: ⁠⁠https://www.ytsthepodcast.com/pinterest⁠⁠ - Linkedin: ⁠⁠https://www.ytsthepodcast.com/linkedin⁠ Learn more about your ad choices. Visit megaphone.fm/adchoices

AI isn't sweeping across the workforce the way the hype machine promised, but something far more interesting is happening beneath the surface. The number of people using AI isn't exploding anymore, but the people who are using it, they're using it more often, more deeply, and more strategically than ever. The story is, AI adoption has stalled, but AI mastery is accelerating. This is your transformation station,

and this is your host, Greg Favaza. Ladies and gentlemen, welcome back to Your Transformation Station, the show where we cut through the noise and get into the behavioral truth behind how people work, lead, and transform. If you have not subscribed to the show, go ahead and hit that subscribe button. And after the show, if you have enjoyed what we have talked about, leave a review.

I'm your host, Gregory Fabaza, and today we're diving into Gallup's latest national data on AI use at work. Now, this isn't speculation. This isn't hype. This is what actually is happening inside American organizations. What is Gallup? When I reference Gallup, I'm referring and talking about one of the most respected research organizations in the world. Gallup is a nonpartisan analytics and advisory firm, and has been measuring public opinion and workplace trends for decades. They're known for their rigorous methodology, massive sample size, and probability-based surveys that reflect the actual U.S. workforce. not just whoever happens to respond online.

Their workforce studies, which I'm using throughout this episode, are built from nationally representative samples of full-time and part-time U.S. employees. Gallup recruits participants through random sampling, not volunteers, and the weight of results to match national demographics. In other words, when I cite Gallup's numbers, I'm pulling from some of the most reliable workplace data available today. How we read this data. Now, before we dive in, here's how Gallup structures is reporting. You're going to hear me say things like Q3 and Q4.

So let's get aligned. Gallup's released its workforce studies. every quarterly, every three months. For those that know, you know what I'm talking about. For those that don't, Q1, January through March, Q2, April through June, Q3, July through September, and Q4, October through December. So when I say Q4, 2025, I'm talking about the data collected in the final quarter of 2025. These surveys include tens of thousands of U.S. workers using probability-based sampling and demographic weighting.

These numbers aren't guessed. They're nationally representative snapshot of how Americans are actually using AI at work. Now, what do I mean by AI when I talk about AI? I'm not talking about robotics or sci-fi. machines. I'm talking about everyday tools people use often without realizing they're using artificial

intelligence. Here are some examples of AI in the workplace. It would be like chat bots, virtual assistance, tools like co-pilot chat GTP or customer services bots that answer questions or generate content.

Writing and editing tools, AI that drafts emails, rewrites text, summarizes documents, or improves clarity, transcription and meeting assistance, tools that record meetings, create transcripts, and generate action items, coding assistance, AI that helps write, debug, or explain code, analytics and data tools, systems that identify patterns, generate insight, or automate reports, task and project management tools, AI that prioritizes tasks, schedules, work, or predicts deadlines. Search and research tools.

AI that finds information, summarizes sources or answers complex questions. Images, videos, audio generators, tools that create visuals, edit media, or produce forsovers. Automation tools, AI that handles redidative workflows like sorting emails or processing. forms. Yeah, I feel like I covered most of it. These are the kinds of tools Gullup is measuring when they are talking about AI use in the workplace. It's not futuristic. It's not hypothetical. Their software people are already using to think faster, write faster, and solve problems faster. All right. With that foundation in place, let's get into the story the data already tells. segment one, the big picture adoption flat using usage rising.

Now, Gallup's newest data shows a fascinating split in the workforce. On one hand, total AI adoption has gone flat. Nearly half of the U.S. workers, 49% still say they never use AI in their role. I mean, if we were to look at a, I mean, I feel like I want to dive in here, if we were to look at a online classroom and we were to ask students, this very question, I would say the majority hasn't, isn't using AI, because then are they really checking that information when they are turning in their assignments? because you're supposed to cite that information. But however, I've seen the opposite. But that's neither here or there. And the percentage of total users didn't grow at all in the Q4.

Okay. But on the other hand, frequent use continues to rise. Now, daily AI use increased from 10 to 12%. That's a frequent use daily or a few times a week. That's climbed to 26%. And this pattern, it has been consistent throughout 2025. So what does this mean? It means the AI curious aren't joining,

but the AI committed, they're leveling up. That's your friend, your neighbor, your coworker. they're using it to improve themselves. If you have not got on this train, it's going to affect you later on by trying to catch up with everybody. This rise of AI power use, it's a small but rapidly advancing segment

of the workforce that's pulling ahead of everyone else. Segment two. So organizational adoption, confusion at the top. Now let's talk about organizations. In Q4, that's 38% of employees said that their organization has integrated AI tools. 41% said no. And 21% said they don't know. That I don't know number is important because it tells us something about communication,

that individual contributors are the most in the dark. 26% say they don't know whether their organization uses AI at all. Leaders, only 7% say the same. This isn't, this gap isn't about technology. It's about visibility, communication, and proximity to decision making. Organizations are integrating AI, but they're not explaining it. They're not training people and they're not creating clarity. And when employers don't understand the value of adoption,

if they don't understand the value, adoption stalls. Industry differences. The AI has and have nots. AI use varies dramatically depending on where you work. Here's a landscape in Q4, 2025. Technology, 77% total AI users, finance, 64%, professional services, 60%, higher education, 63%. K through 12 education, 56% government and public policy, 42% health care, 41%, manufacturing, 41%. And retail is 33%.

And the growth pattern tells an even sharper story. Finance is plus six points. Professional services is plus five points. Manufacturing plus three points. Retail is a zero change. Technology is a plus one points, but it's already saturated. Knowledge-based industries are accelerating. production and service industries are lagging.

This is the beginning of an, this is the beginning of an AI economic divide, one that will shape wages, productivity, and opportunities for years to come. Lastly, remote versus on-site, the geography of AI use. One of the clearest divides in the data is between remote capable and non-remote roles.

Okay, since 2023, remote capable roles. Total AI use is 28% to 66%. Frequent use is 13 to 40%. Daily use is 8 to 19%. Now, not remote capable roles. Total AI use. 15 to 32 percent. Frequent use, 8 to 17 percent, and daily use is 3 to 7 percent.

Remote capable workers are using AI at double the rate of on-site workers. Why? I mean, because AI thrives in digital workflows, and digital workflows thrive in remote environments. industry differences. AI use varies dramatically depending on where you work. Here's the landscape in Q4 2025. Technology, 77%. Finance, 64%.

Professional services, 60%. Higher education, 63%. K through 12, 56. Government, 42. Healthcare. 41, manufacturing, 41, and retail is 33%. Now, these growth patterns sharpen the divide. We've got finances plus six, professional services plus five, manufacturing is plus three.

Zero, correction. Retail is zero, and technology is plus one, but it's already saturated. Knowledge-based industries are accelerating. and service industries are lagging. This is the beginning of an AI economic divide. Now, remote versus on-site. This is one of the clearest divides is between remote-capable and non-remote work. Since 2023, remote-capable roles.

Total use has gone up from 28% to 66. frequent 13 to 40% now daily that's gone from 8 to 19% non-remote capable roles total use is

from 15 to 32% and frequent 8 to 17% and daily which is 3 to 7% remote capable roles are using AI at double the rate of on-site workers because AI thrives in digital workflows. And digital workflows, well, they thrive in remote environments. Here is where it gets interesting.

The leadership gap. The leadership gap is a widening. Q4. This is at 69% of leadership. Leaders use AI. 55% of managers and 40% of individual contributors. Now, frequent use. Leaders have gone from 17 to 44%.

Managers, 15 to 30%. IECs, 9 to 23%. Leaders use AI more often, more deeply, and with more confidence because they see clear use cases. They have more autonomy and their roles naturally align with AI-driven decision-making. This creates a capability gap

and that will shape promotions, performance, and the leadership pipeline. Lastly, what workers use AI for? I mean, despite the hype most employees aren't using AI, for advanced analytics or coding, unless you're an entrepreneur and you're trying to do everything yourself,

and that can be overwhelming as it is. They're using it for thinking. The top cases, consolidating information, it's at 42%, generating ideas, 41%. Learning new things, 36%. Automating basic task is at 34%. Most common tools will be very spoken. Previously, it's chatbots, which is at 61%, writing and editing, 36%.

Coding assistance, 14% and analytical tools, 13%. AI today is the cognitive amplifier, not a technical one. Now, why has adoption stalled? Well, Gullup found the number one barrier. to AI adoption. It's unclear use case of value proposition. Only 16% strongly agree their organization's AI tools are actually useful.

This explains everything. Adoption is slow when value is unclear. Frequent use rises when value is obvious. Leaders see more utility. Remote workers have more digital workflows. Now, college workers accelerate. Front line workers fall behind. Organizations aren't communicating clearly. AI isn't a technology problem. It's a clarity problem. Now for those that want to learn about AI, the fundamentals, but actually understand it. I'm using, I'm using, IBM skill build.

They have a lot of great courses on there. I'm not, I'm recommending it because I am utilizing it myself to understand project management fundamentals, business design,

and also AI use. There's a lot of great courses. There's hundreds on AI and health care, AI, and business. AI and veterinary medicine, it just keeps going with the amount of AI courses that are available on IBM skill build. If you have not heard of it, check it out. If you have, then you already know it is a great site to, one, to learn more about this technological advance,

but also to level up your resume and get the certificate. Because once you complete the course, you can put that on your resume. And that's a good leg up to have. Now, the survey methods, I mean, before we wrap this up, here's how Gallup has collected this data, because the strength of the insights depends on the strength of the methodology. Gallup's Workforce Studies are probability-based surveys of the U.S. adult working full or part-time. Participants are recruited through random sampling, not volunteers, like I've already said.

The results are weighted to match national demographics. Each quarterly study includes tens of thousands of workers. Now, for example, Q2 2025, that's 19. thousand forty three workers Q2 2024 21,543 Q2 2043 Q2 2023 18,871 the margin of error hovers around one at one to 1.1.1 percentage points this is why the trends we discussed the rise of frequent use, the industry gaps, the leadership divide, the remote work advantage are not speculation, they're grounded in rigorous, nationally representative data. This is your transformation station.

I am Gregory Favaza, and the future belongs to the ones who lane in. Thanks for joining us on this adventure. of growth and discovery. If you're ready to achieve a sustainable transformation, don't forget to hit that subscribe button so you never miss an episode. And hey, if you've enjoyed the show and want to support it, take a moment to leave a podcast review on Apple or your favorite podcast platform. Stay connected with us on social media for behind-the-scenes sneak peeks, inspiring quotes, and the latest updates. You can find us on Facebook, Instagram, TikTok, and YouTube. Just serve. for YTS the podcast.

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