How Do You Improve AI Literacy in Your Organization? (2026)

To create AI literacy, train employees on three things:

1. what AI actually is,
2. how to use it effectively, and
3. when to apply it.

When you build these foundational skills, employees use AI 3x more often.

Your company just rolled out Microsoft Copilot to 500 employees. Three months later, usage sits at 18%.

It's not that your team doesn't want to use AI. They don't know how to use it. Or when it's appropriate. Or whether it's safe to feed their meeting notes into ChatGPT.

The gap is AI literacy. And without it, even the best AI tools just don't get used.

This guide shows L&D and HR leaders how to close that gap. You’ll figure out where your team stands right now and how to build a program to help encourage daily use.

Your employees don't need to understand machine learning models or build algorithms. They need to know three core things:

• What AI is (and isn't): AI spots patterns and makes predictions based on training data. It's not a source of truth. It doesn't "know" facts. It can't reason like humans.
  
• How to use AI: Create prompts that deliver useful results, explore AI features in familiar tools, review outputs for accuracy and bias, and understand what information is safe to share.
  
• When to use AI: Use it for summarizing documents, drafting emails, and analyzing data. Keep sensitive conversations, strategic decision‑making, and relationship‑building as human-only activities.

According to Go1's AI Research Report, the biggest barrier to AI adoption is human understanding. 

While 70% of professionals use AI weekly, only 56% feel confident selecting the right tool for their needs. It’s like providing complex tools without clear guidance on how to apply them.

Here's what's stopping them:

• They don't know the basics: Even weekly AI users struggle to match the right tool to the task. Across all job types, many employees say limited AI knowledge as their main barrier to adoption.
  
• They don't see the relevance: Service employees and frontline workers don't think AI applies to their work. They can't picture what practical benefits it could bring to their everyday roles.
  
• They don't trust that it’s safe to use: According to Go1's Content Intelligence, courses on AI awareness and safety had both the highest total enrollments and the steepest growth in participation over the past year. People want to use AI. They just want to know it's safe first.

Without baseline AI literacy, adoption doesn't happen. Employees need to understand what AI is, why it matters to their specific role, and how to use AI ethically and safely before they actually integrate it into their work.

1. Figure out where your team actually stands (not where you hope they are)

Before launching AI training for employees, first understand your team’s current skills and confidence levels. 

You need data, so that means understanding:

• How employees currently feel about AI (excited? terrified? confused?)
• What they're already using (if anything)
• Where they're getting stuck
• What they actually want to learn

Go1's AI Maturity Assessment makes this simple. Instead of guessing where gaps exist as you reskill in the age of AI, you get data-driven insights into four key areas:

• Strategic vision: Are your AI learning initiatives actually aligned with business priorities, or are they just checking a box?
• Use of AI in learning: How do your AI integrations compare to what your peers are doing?
• Ability to measure impact: Can you prove AI training is working?
• Organizational influence: Does your team actually have a seat at the table for AI strategy and governance?

Once you're benchmarked, you'll see where you're ahead and where you're behind. Plus, you’ll get specific next steps to close the gaps.

2. Stop training everyone the same way

The challenge with a single, uniform AI training program is that different teams have different starting points. For example, engineering roles may already work with AI daily, while some customer‑facing teams may see limited relevance.

According to our research, the gap is real. Software engineering roles use AI the most. Sales and customer service employees use it the least. And L&D leaders say designing for these different upskilling needs is the #2 most challenging obstacle to building an AI learning strategy.

You need role-based programming that meets employees where they are, whether they're brand-new to AI or already experimenting.

Go1's Upskilling Playbook shows you how to build that. It includes our AI Upskilling Framework, which helps you create learning paths tailored to specific roles and skill levels. Download the Go1 AI Upskilling Playbook for free.

3. Balance speed with trust (because your team needs both)

AI moves fast. Your employees need to learn quickly. But they also need to trust what they're learning.

Most AI content out there is scraped from Reddit threads and open-source forums. It's fast, sure. But is it accurate? Is it safe? Does it actually apply to your industry?

Your job as an L&D leader is to give your team speed and credibility. That means combining multiple learning strategies that let people move fast while maintaining quality standards they can actually trust.

Here's what that looks like:

• Microlearning for speed: Employees say they have "no time to learn" AI skills. Microlearning breaks complex topics into bite-sized lessons they can consume quickly.
  
• Peer learning for relevance: Your best AI teachers might already be on your team. Employees are already experimenting with AI. Tap into their expertise. Host lunch and learns. Champion specific employees as AI ambassadors who can provide informal support and answer real questions.
  
• Curated content for trust: There's no shortage of AI content online. The problem is quality. Instead of sending people into the wilderness, provide a curated library of vetted resources organized by role, skill level, and use case. 

4. Embed AI literacy into your culture (not just your training catalog)

AI literacy endures when it’s integrated into everyday workflows, not treated as a standalone training topic. The more normal AI usage feels, the more people will use it.

Here's how to make that happen:

• Make AI wins visible: Share effective AI use cases in team meetings, company newsletters, or Slack channels.
  
• Build AI into existing workflows: Don't create separate "AI training time." Integrate it into what people are already doing. Add "AI opportunities" as a standing agenda item in sprint retrospectives. Include "Could AI help with this?" as a checkpoint in project planning meetings.
  
• Create a culture of safe experimentation: Create a dedicated Slack channel where people can share what they tried, what worked, and what didn’t. Host monthly "AI show and tell" sessions where employees demo their experiments, successful or not. 

BCG found that leading companies invest 70% of their AI transformation budget in people and process, not software. And when employees actually understand AI basics, they use it 3x more often.

Your competitive advantage is how fast your people can use them effectively. The right training is essential to achieving this.

Go1 gives you the research, the tools, and the content to build an AI literacy framework at scale, whether you're starting from zero or upskilling teams already experimenting. 

From the AI Maturity Matrix that shows you exactly where you stand, to role-based learning paths that meet employees where they are, to thousands of curated AI courses organized by skill level, Go1 makes AI adoption actually achievable.

Because you can't automate learning. But you can make it faster, safer, and more impactful.

Start building AI literacy with confidence.