Transform 2026 Takeaways: 4 AI Trends Reshaping How Global Teams Learn and Perform

I just returned from Transform 2026 in Las Vegas, where 4,200+ HR and people leaders gathered to wrestle with a question every leadership team is now facing: how do we scale workforce capability at the same speed as our business?

After three days of demos, panels, and candid conversations with CHROs, CTOs, and founders, four trends emerged that I believe will define how we train and enable global teams in the AI era.

The biggest surprise at Transform wasn't the enthusiasm for AI. It was the fear.

Every CHRO I spoke with wanted to move faster with AI adoption. But they're paralyzed by a very real concern: compliance risk. Companies are facing class action lawsuits based on their AI governance. Even when using established LLMs like Anthropic or OpenAI as the underlying technology, organizations are being held liable for outcomes.

The solution isn't to slow down. It's to scale with guardrails.

What I heard repeatedly was that the companies winning at AI adoption are those that are radically transparent about data usage. They communicate clearly to employees about what data is collected, how it's stored, and what it's used for. This transparency isn't just good ethics. It's the foundation of employee trust that makes AI adoption possible.

The takeaway: Don't let compliance concerns delay your AI strategy. Let them empower you to move with greater confidence. Build your AI initiatives on a foundation of transparency and clear data governance from day one.

Here's what surprised me most about the Transform expo floor: we are in the middle of a learning revolution defined by speed and context.

While leaders are demanding real-time, contextual learning, I saw booth after booth showcasing elaborate, structured courses and manual content creation tools that would have felt cutting-edge five years ago. Some things are moving at breakneck speed in our industry, yet many tech providers haven't kept pace with what's actually happening in the market.

Here's what the data shows: no effective employee learning module is longer than 15 minutes. The era of hour-long training that employees click through while checking email is over.

There is a fundamental shift happening in L&D. The CHROs I spoke with aren't focused on traditional company-wide training anymore. Their priorities have shifted to hyper-speed learning customized for different geos, especially for global teams; GTM effectiveness, including real-time coaching for sales teams; and in-the-moment feedback, instead of waiting until after a call to provide coaching.

One CRO put it perfectly: "Why can't we have a more sophisticated agent to train sales reps right on the call using data directly from the call? Waiting till the call is over to record and then provide coaching is time wasted."

The future of L&D isn't courses. It's continuous, contextual coaching embedded directly into the flow of work.

Every product leader and founder I met was grappling with the same question: How do we make our AI solutions feel more human?

The consensus was clear on several points.

Stop calling them "agents." The term is confusing and creates distance. Call them AI teammates. I'll admit that when this idea came up internally at Smartcat over a year ago, I was skeptical. Now I'm an advocate.

Make them proactive. If your AI doesn't have triggers to proactively raise topics, questions, and insights, it will be seen as too manual and eventually abandoned. The best AI teammates don't wait to be asked. They surface relevant information when it matters.

Let employees personalize them. Those pre-set quirky AI names that companies assign, like "Talk to Marcy!", are confusing and annoying. Let employees name their AI teammates and customize their appearance. The more connected someone feels to their AI teammate, the more they'll use it.

At Smartcat, we've seen this firsthand with our internal AI teammates. Every single company I showed my AI teammate to, without exception, thought it was the coolest thing they'd seen at the conference. They wanted to know how we built it and whether we could do the same for them. The enthusiasm wasn't about the technology. It was about having an AI teammate that actually understands your company's context and can help with real work. By the way, I named my AI teammate Sunny. The sun makes me smile, and working with AI does the same.

The implication for L&D teams is significant. You're no longer just training employees on static processes. You're enabling them to continuously learn and adapt as the tools they use evolve in real time.

Here's the uncomfortable truth that CTOs and CPOs were wrestling with at Transform: release cycles have moved from months to days, but customer enablement hasn't kept up.

When your product changes weekly, traditional documentation and training become obsolete before they're published. Customers are drowning in release notes they don't have time to read and missing features that could improve their workflows.

The solution emerging across the industry is AI-powered customer enablement.

Companies are deploying customer-facing AI agents that walk users through new product releases in real time. Instead of sending a changelog email that gets ignored, imagine an AI teammate that notices you're struggling with a workflow and says, "Hey, we just released a feature last week that could help with exactly this. Want me to show you?"

One insight that stuck with me was that the most forward-thinking companies are having their engineers, not just product managers, sit directly with customers every week. This allows them to fix bugs and issues on the spot, creating a feedback loop that's impossible to achieve through traditional channels. It also allows engineers to see firsthand how their code is used and the impact their hard work has on the customer. It creates a win-win that's faster, more accurate, and far more connected to real customer behavior.

All four of these trends converge on one reality: the companies that win will be those that can scale learning and enablement globally, instantly, and continuously.

This is exactly the problem we've been solving at Smartcat with our Learning Content Agent for course creation. It’s designed to move beyond traditional course authoring with an AI course creation tool that helps teams generate and adapt learning content faster. It's an AI teammate that can create and translate training content simultaneously across 280+ languages, and generate microlearning modules that respect the 15-minute attention span reality. It also supports enterprise eLearning workflows by integrating directly with your LMS, learning from your experts to maintain brand voice, compliance standards, and quality.

When your product team ships a new feature on Tuesday, your global workforce can have localized training content by Wednesday, not next quarter.

Transform 2026 made one thing crystal clear: AI isn't being blocked by capability. It's being blocked by confusion.

The biggest opportunity isn't building more features. It's making AI feel intuitive, transparent, and immediately useful in daily workflows.

What leaders actually have an appetite for is scaling while controlling risk and having human collaboration and training built into the AI mix.

For L&D and People teams, that means shifting from training to real-time enablement. If learning doesn't happen in the moment, it's too late. It means designing AI as a teammate, not a tool. If AI doesn't feel like a teammate, it won't be used. It means closing the gap between product speed and learning speed. If enablement lags product, customers and employees fall behind. It also means building trust as your foundation for scale. If trust isn't built early, adoption stalls.

AI doesn't change what great teams look like. It raises the bar for how fast they need to learn.

The companies that figure this out won't just train faster. They will operate more effectively, with teams that learn, adapt, and execute in real time. They will move at the speed their business demands.

And in 2026, that's the only speed that matters.

Stacey Richey is VP of People at Smartcat, where she leads initiatives to scale global workforce capabilities through AI-powered learning and enablement. Connect with her on LinkedIn: https://www.linkedin.com/in/staceyrichey/