How Events Can Help Bridge B2B’s AI Learning Gap

AI use is rising, but training isn’t keeping up. Here’s where events can help.

According to PwC’s 2026 Global Workforce Hopes and Fears Survey there is a striking divide in how workers are adapting to AI: 56% are still building capabilities and finding their footing, while only 14% qualify as AI “Front-runners.”   

Daily AI use is rising, but most workers still don’t use it every day. And the report points to lopsided access to learning and development, especially for workers who are less comfortable with AI. 

This divide is about more than just fluency. Front-runners are 1.5 times as likely as the average worker to be rewarded for challenging how work gets done, pointing to a widening opportunity gap in the global workforce.  

For companies, AI adoption shouldn’t be about rewarding the tech-savvy but upskilling an entire workforce to increase productivity across the board. That means creating space to explore where people feel supported and confident enough to figure out where AI fits in their own day-to-day. 

AI Fluency Should Start with Human Interaction 

Most B2B professionals know AI is here to stay. But knowing about AI and knowing how to use it are two very different things. 

A training exercise can introduce a tool, but people also need a chance to connect it to the tasks, decisions, and deadlines they face every day. That’s where understanding starts to become practical. 

Getting comfortable with new technology usually takes relevant examples, a chance to try it in a familiar context, and room to ask questions without embarrassment. Those experiences should also reinforce how much human judgment still matters. 

Events are uniquely equipped to create those kinds of environments: low-risk, exploratory set ups, built around real work, that feel more engaging than a webinar, and social enough that people can learn from one another as well as from the person onstage. 

Design for Different Starting Points 

Audiences won’t show up with the same skills, confidence, or concerns. A successful experience accounts for those differences by offering a few ways to participate: watching and asking questions, trying tools hands-on, talking with peers, or learning through guided exercises or games. 

There are plenty of great ways to introduce AI training at an event, and only one mistake to avoid: assuming a single demo or session will meet everyone’s needs. 

Give attendees a chance to explore tasks they recognize, see where AI helps, and use their own judgment to assess the results. It’s an experience offering the realism and relevance a demo cannot, sparking interest and intrigue around the possibility AI represents.  

The challenge for event professionals is to create experiences that scale, so they can help more people engage with AI whatever their starting point.

What It Looks Like in the Room 

A well-designed experience starts at the end: articulate the behavior you want people to take back to work, then build backward from there.  

Breakouts can support behavior change when they give people time to test things out: try a task, see what works and what doesn’t, adjust and try again. Ideally, they do this next to other people working through the same challenges. Working alongside peers makes it easier to compare results, share useful prompts, and ask questions as they come up. 

That’s how access can start to become understanding: people leave with a clearer sense of what AI can help them do. Thinking shifts from “I have access to this” to “I get how this helps.”   

Events Are Just the Beginning 

An event can bring people with different AI fluency levels into the same room to build shared understanding and confidence. It can make collective progress visible: where people get stuck, which shortcut helps, and when more hands-on training is required. These observations can give incredibly useful data about what needs to happen next. For the event marketer who’s just been handed AI adoption as the goal of their next event, that’s the shift worth designing for. 

But remember: one great experience won’t make anyone an AI expert. Follow-up communication, sustained training, useful resources, and ongoing discussion are needed to build on that momentum and help people apply what they’ve learned to their own work. Events are where important dialogues start. Follow up is helps it feel like a conversation and not a mandate. 

The AI Race Needs a More Human Starting Line 

The organizations that move forward on AI won’t do it by cultivating a few Front-runners and hoping the rest can keep up. More people need the chance to explore what AI could do in their specific roles and gain the confidence to experiment in their work. Ideally, they can learn with a facilitator’s guidance and alongside their peers. 

One way to understand whether that learning is making an impact is to look at usage before and after the event: how often are people reaching for the tool, and are they still using it a month later? It’s one indicator of progress that, considered alongside other program measures, can help show where AI learning is taking hold and where more support is needed. 

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