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What is AI literacy?

By Team Multiverse

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Contents

  1. What is AI literacy? Definition and examples
  2. Why is AI literacy important?
  3. How build AI literacy across the organizational structure
  4. Strengthen AI literacy across your workforce

The excitement created by AI is palpable.

Leaders and workers alike are seeking opportunities to increase productivity, transform the customer experience, and unlock new product capabilities using AI tools.

But if workers aren’t also equipped with basic AI literacy to help them leverage new tech effectively and responsibly, AI may only create more headaches – rather than curing them.

Successful AI adoption is often held back by a lack of workforce skills, and leaders name AI as their most significant skills gap. Despite this, many workers still lack access to AI literacy resources, with the majority of workers (51%) having received under 5 hours of training so far.

In this article, we’ll assess how the AI literacy gap forms, and what employers can do about it.

What is AI literacy? Definition and examples

AI literacy refers to employees’ understanding of AI as a technology and how it can be applied in daily work. This includes understanding what types of AI exist, identifying use cases for AI, and knowing the basics of how to use it safely.

Basic examples of employee AI literacy can include:

  1. Using AI tools – leveraging the likes of Microsoft Co-pilot or ChatGPT in their day-to-day role
  2. Spotting use cases for AI – for example, streamlining processes or increasing speed of outputs.
  3. Using AI safely and responsibly - protecting sensitive data, understanding ethical considerations, and mitigating risks.
  4. Technical skills - to build or develop AI tools, or integrate AI into systems, like data analysis, data engineering, or machine learning.

Why is AI literacy important?

Many employees may well have started their journey to AI literacy– most commonly, they may already be experimenting with generative AI tools like ChatGPT to increase their personal productivity.

But if teams haven’t been equipped with a strong foundation in AI skills, challenges can easily appear.

Taking AI from “toy to tool”

A lack of AI literacy may mean employees struggle to identify use cases for new tech, or select the wrong AI tool for the problem they’re trying to solve.

In this scenario, AI won’t be used to its full potential to deliver real results or solve a genuine business issue. The new technology never fully becomes a tool – it remains a toy.

This can create headaches for teams down the line. Not only can they find themselves with the wrong solution in place, but they’ll also struggle to get the desired value back from any financial or time investment.

Offering AI literacy training can help teams to think critically about how and when to leverage AI, and select the correct solution for their needs.

Mitigating risks

As well as technical skills, employees will require AI literacy training to understand and mitigate the risks associated with the technology.

Leaders and workers cite risk as their top barrier to full AI adoption – yet only a small proportion of leaders strongly agree that their organization has established best practice in providing governance structures to limit AI risk (28%), and less than half of strongly agree their business is ensuring responsible use of AI in business practices (43%).

Training teams on AI ethics, and how to identify and manage risks around data usage, can help to prevent pitfalls early on.

How build AI literacy across the organizational structure

AI literacy is best considered across the org chart, acknowledging the different types of skills employees may need, depending on their role and seniority.

Team level

A ‘bottom-up’ approach begins with building a strong foundation of AI literacy at a team level – arming teams with the basic know-how to use AI safely and effectively in their day-to-day roles.

At this stage you can also nominate designated AI champions within your teams, responsible for spotting new opportunities for AI use cases, sharing findings, and building your AI Center of Excellence (COE).

To avoid the ‘toys, not tools’ conundrum, those AI champions take an analytical and evaluative mindset to problem-solve through the lens of AI.

Management and leadership level

Business leaders and managers are then involved as they look to place their strategic bets on AI and deliver tangible return on investment from emerging tech.

In addition to developing their individual AI skills, leaders and managers can benefit from additional training in strategic thinking and change management - to help them empower and motivate employees at all levels to adopt AI solutions and use them in a way which aligns with their goals and strategy.

Strengthen AI literacy across your workforce

If you want to unlock potential in your business using AI, it starts with a strong AI literacy foundation.

Discover our guide to building AI-enabled teams, and learn how to equip employees with the essential skills needed to deliver impact from AI.

Team Multiverse

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