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This is the second of two posts from Glen Cathey on why companies need to provide direction and tools so their workforces can use AI safely. Here’s a link to the first post, “Why Giving Employes the AI Tools and Training They Want Is a Win-Win.” 

Because generative AI tools like Copilot, ChatGPT, Gemini, and Claude understand natural language, many people assume they’re completely intuitive to use. 

Don’t be fooled.

As Yuval Noah Harari, author of Sapiens and Homo Deus, has pointed out: “We cannot take AI adoption for granted: AI is not equivalent to smartphones, and we will need to help people understand how to best use it in their daily and professional lives. Massive investment in AI literacy upskilling is needed worldwide.” 

AI training should include broad foundations as well as role-specific guidance

The reality is that getting maximum benefit from generative AI tools takes a specific mindset that does not come naturally to most users. As a result, companies should develop and deploy training on the effective use of generative AI.

This would include understanding the basics of generative AI and how large language models (LLMs) work as well as their limitations, the ideal way to think about and interact with generative AI tools, and various prompt engineering best practices.

In addition to these foundational training elements, it would be ideal for companies to develop training for specific roles (recruiting, marketing, sales, finance, legal, etc.) and use cases.

While prerecorded online training is table stakes and certainly the easiest to scale across a company, I have found that the most effective way to learn how to get the best results from AI tools comes from hands-on, experiential learning. 

Experiential learning is absolutely essential for building AI literacy

As I often say, online learning can provide people with knowledge, but if you are truly going to upskill people, skills are gained through the practical application of knowledge.

It turns out that I am not alone in this thinking. Steven Randazzo, visiting research fellow at Harvard University and head of innovation at Altruistic AI, stresses: “AI literacy is experiential and training investments are immediately needed for the 20-year-old and the 60-year-old alike.” 

In the Randstad Advisory group, I’ve created and delivered experiential, hands-on workshops customized with practical tasks associated with the roles of the attendees. These workshops consistently get extremely high satisfaction ratings and we continue to develop and refine them both internally and externally with clients. We’ve recently taken the concept one step further and have developed a train-the-trainer resource program to effectively scale these hands-on workshops so that they can propagate through every corner of our global company.

You can explore creating and delivering these kinds of experiential workshops yourself, or you can reach out to me to learn more about ours.

At a minimum, I believe successful AI literacy programs should take a multifaceted approach: 

1. Foundational knowledge

• Basic generative AI concepts and terminology
• Understanding LLMs
• Ethical considerations and responsibilities
• Security and privacy best practices

2. Role-specific training

• Customized use cases by role and department
• Industry-specific applications
• Compliance considerations
• Department-specific best practices

3. Hands-on experience

• Interactive workshops
• Real-world scenario practice
• Peer learning opportunities
• Ongoing skill development

AI adoption and innovation is about more than training; it’s about creating a supportive culture

Imagine walking into an HR meeting and instead of just discussing time-to-fill and cost-per-hire metrics, teams were excitedly sharing how AI has transformed their work. Sourcers would showcase how they’re finding perfect-fit candidates for hard-to-fill roles in minutes instead of hours. Recruiters would demonstrate how they’re crafting personalized outreach campaigns that are doubling response rates. HR business partners would present how they’re developing comprehensive compensation analyses and engagement strategies in a fraction of the usual time. 

This isn’t a future scenario — it’s happening now in organizations that have successfully cultivated a culture of AI innovation.

To truly foster AI adoption and innovation, you need more than just initial training — you need to create a culture and an ecosystem that supports and celebrates effective AI use. Let me break this down into three key pillars:

First, create a centralized knowledge repository where people can share their success stories and find inspiration. While some might think of this simply as a prompt library, it needs to be much more — think of it as your organization’s living playbook for AI innovation. This should include not just prompts, but real success stories, best practices, troubleshooting guides, and regular updates as new use cases emerge.

Second, identify and leverage your internal champions. Every organization has early adopters and power users who are already pushing the boundaries of what’s possible with these tools. These are your natural AI champions — the people who can lead by example, run hands-on workshops, and train others who can then train their teams. It’s a powerful way to recognize your innovators and to scale knowledge organically through your organization.

Third, make generative AI use and innovation part of your daily conversation. Talk about it and celebrate creative and effective use in team meetings and one-on-ones, and create regular opportunities for people to share their discoveries. This could include hosting AI office hours, organizing innovation challenges, or creating dedicated channels for sharing tips and insights.

You can create an AI supportive ecosystem with these practices

Here’s what these three pillars look like in practice:

1. Create a central AI knowledge hub, comprised of:

• Curated prompt libraries
• Success stories and case studies
• Best practices documentation
• Troubleshooting guides
• Regular updates and improvements

2. Leverage internal champions to:

• Identify and support power users
• Document innovative use cases
• Create mentor networks
• Facilitate peer learning
• Recognize and reward innovation

3. Maintain regular engagement by:

• Hosting AI office hours
• Organizing hackathons and innovation challenges
• Featuring AI success stories in team meetings
• Creating channels for sharing tips and discoveries
• Establishing feedback loops for continuous improvement

The key is creating a culture where AI innovation isn’t just allowed — it’s expected and celebrated. When people see their colleagues finding creative ways to use these tools and getting recognition for it, they’re naturally motivated to explore and innovate themselves.

Generative AI is reshaping how all knowledge work is done

Even if you haven’t felt it yet yourself, the world of work has fundamentally changed. Generative AI isn’t just another technology trend — it’s transforming how all knowledge work is performed, from entry-level tasks to executive decision-making.Let’s be crystal clear about what’s at stake:

• Your employees are already using AI tools, whether you’ve provided them or not
• Without proper training, they may be creating unnecessary risks
• Without clear guidelines, they’re likely working in the shadows
• Without cultural support, you’re missing massive opportunities for innovation
• Without a comprehensive AI strategy with a core of literacy, you’re at risk of falling behind competitors

One of the most amazing things about generative AI is how it has democratized access to incredibly powerful technology. However, this democratization also means that access alone provides no competitive advantage — your edge can only come from how effectively you:

1. Provide secure, approved AI tools where possible, and develop clear policies about acceptable use of public AI tools where private solutions aren’t feasible
2. Train your people in the safe and responsible use of both private and public AI tools — remember, they’re likely to use both
3. Create clear role-specific guidelines that enable rather than solely restrict, explicitly stating what data can and cannot be used with different types of tools
4. Foster a culture that celebrates AI innovation while maintaining security and compliance
5. Scale successful practices and share learnings across your organization

Final thoughts: Without a comprehensive strategy for AI literacy, your company is at a competitive disadvantage

Here’s your call to action: Start by assessing where your organization stands today. Are you among the Prepared, the Partially Prepared, the Restrictive, or the Avoidant? Then I recommend you take these steps:

1. If you haven’t provided secure AI tools, start evaluating options now
2. If you haven’t developed training programs, begin with the frameworks outlined in this article
3. If you haven’t created clear guidelines, use the examples I provided to develop role-specific guidance
4. If you haven’t built a culture of AI innovation, implement the three pillars that I’ve laid out

Remember, the goal isn’t to unnecessarily control or restrict AI use — it’s to enable your workforce to leverage these powerful tools safely and effectively. The longer you wait, the further behind you fall.

Without a comprehensive strategy for AI literacy and adoption, you’re not just missing opportunities — you’re actively putting your company and employees at a competitive disadvantage. The time to act is now.

Glen Cathey is a strategic thinker and global keynote speaker with extensive experience in talent acquisition and leadership. He is passionate about making a difference, developing others, and solving problems. Glen has served as a thought leader for sourcing and recruiting strategies, technologies, and processes for firms with more than 2 million hires annually. He has played a key role in implementing and customizing ATS and CRM systems, and has hired, trained, and developed large local, national, global, and centralized sourcing and recruiting teams. Glen has spoken at numerous conferences, including LinkedIn Talent Connect, SourceCon, Talent42, and Sourcing Summit Europe.

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