The AI Literacy Revolution: Why Understanding AI Is Now Essential

The AI revolution is no longer coming—it's here. With 200 million weekly ChatGPT users today and projections of over 700 million AI users by 2030, understanding what AI literacy truly means has become mission-critical for professionals across every industry.

TLDR:

• Unlike digital literacy which developed over decades, AI capabilities are transforming dramatically within months
• 85% of the workforce will be AI users rather than AI builders, requiring different approaches to AI literacy education
• The EU AI Act coming into effect in 2024 includes specific requirements for AI literacy with enforcement beginning February 2025
• Organizations face challenges in building AI literacy including overcoming skill gaps, addressing resistance, and keeping pace with rapid technological changes
• "Supercharged professionals" are those who strategically leverage it to enhance their existing skills
• Companies implementing AI literacy initiatives are seeing significant productivity gains
• Building an AI literate organization requires establishing fundamentals, promoting practical proficiency, encouraging critical evaluation, instilling ethical responsibility, and fostering continuous learning

Drawing from CFTE's comprehensive white paper, Google NotebookLM AIs explore how AI literacy has rapidly transformed from a specialized technical skill to an essential competency for everyone. 

Much like internet literacy evolved from simply accessing websites to critically evaluating online information, AI literacy now encompasses five core components: understanding basic AI concepts, effectively using AI tools, critically evaluating AI outputs, recognizing ethical implications, and developing confidence in working alongside these powerful technologies.

Unlike digital literacy that developed gradually over decades, AI systems like GPT-4 and Claude are making quantum leaps in capability within months. This acceleration means AI literacy isn't a one-time achievement but requires continuous learning and adaptation.

Most importantly, we unpack the distinction between AI builders (roughly 15% of the workforce) and AI users (about 85%) highlighting that most professionals don't need to code AI systems but must understand how to work effectively alongside them. 

This distinction shapes how organizations should approach AI literacy training, from establishing foundational knowledge to promoting critical thinking and ethical responsibility.

Those who develop these competencies will become what CFTE calls "supercharged professionals" leveraging AI to amplify their uniquely human capabilities while navigating this technological transformation with confidence and responsibility.

Full Research: 2025 AI Literacy Whitepaper

What does your AI literacy journe

Chapters

• 0:00 Introduction to AI Literacy
• 7:35 Defining AI Literacy Challenges
• 22:50 Evolution of Literacy Concepts
• 35:19 Five Core Components of AI Literacy
• 54:15 The Rise of Supercharged Professionals
• 1:07:50 Building an AI Literate Workforce
• 1:21:00 Challenges and Implementation Strategies
• 1:29:20 Key Takeaways and Future Focus

Transcript

Speaker 1: 0:00

All right, welcome back to the Deep Dive. Today we're talking AI, something that's honestly everywhere these days.

Speaker 2: 0:06

Yeah, it's exploding. It's really incredible to see.

Speaker 1: 0:08

I mean, just look at Chad GPT. Right, they hit a million users in what like five days.

Speaker 2: 0:13

Five days, yeah. And now it's what? 200 million weekly users, huge yeah.

Speaker 1: 0:18

And the projections are saying we could have over 700 million people using AI tools by 2030.

Speaker 2: 0:24

It really makes you stop and think like this is massive, this is changing everything.

Speaker 1: 0:28

And that's why we're doing this deep dive today. We're not trying to turn you into some kind of you know, ai expert.

Speaker 2: 0:33

Right, we're not coding anything today.

Speaker 1: 0:35

Exactly, but we want to talk about something that affects all of us AI literacy.

Speaker 2: 0:42

It's not just about using the tools. It's about understanding them.

Speaker 1: 0:44

Yeah, ai literacy. It's not just about using the tools, it's about understanding them. Yeah, like, how do these things actually work? What are the implications, you know, for society, for our jobs?

Speaker 2: 0:50

And the regulations. I mean the EU AI Act, for example. That's a whole other layer.

Speaker 1: 0:55

It's serious stuff. You could actually face penalties if you don't understand the rules around AI.

Speaker 2: 1:00

So AI literacy is becoming less of a nice to have and more of a need to have Big time yeah.

Speaker 1: 1:06

So, to help us unpack all of this, we're going to be looking at a really interesting white paper from CFTE.

Speaker 2: 1:12

It's called AI Literacy Understanding and Implementing AI Literacy.

Speaker 1: 1:17

Catchy right.

Speaker 2: 1:18

Well, it gets the point across.

Speaker 1: 1:20

And this is the updated version, version 0.3, for 2025. So it's right on the cutting edge.

Speaker 2: 1:25

This paper really lays out what AI literacy actually means and how we can start bringing it into different industries.

Speaker 1: 1:32

It's about going beyond, just like clicking around in some AI tool. It's about understanding the guts of the thing. You know what it can do, what it can't do and what your responsibility is when you're using it.

Speaker 2: 1:43

And, it's interesting, even this paper itself. They acknowledge that they used AI tools in the writing process.

Speaker 1: 1:48

Oh really.

Speaker 2: 1:48

Yeah, generative AI specifically.

Speaker 1: 1:50

So, for those who might not know, generative AI is like tools that can write stuff, create images, all that based on what you tell it to do.

Speaker 2: 1:57

Exactly so. Even in a paper about AI literacy, ai is already playing a role, but, of course, the core ideas, you know, those human insights. That's where the real value is. It's that human element that's irreplaceable, and it also highlights this increasing need for transparency around how we're using AI.

Speaker 1: 2:15

Right, because it's everywhere. So today our mission is pretty straightforward we're going to unpack this whole AI literacy thing, figure out why it matters so much right now and then see how we can actually put it into practice.

Speaker 2: 2:27

All based on what the CFTE white paper has to say.

Speaker 1: 2:30

All right, you're ready to dive in?

Speaker 2: 2:31

Absolutely.

Speaker 1: 2:33

So, right off the bat, the paper talks about these hidden gaps in how we understand AI literacy.

Speaker 2: 2:39

Like we haven't quite grasped it fully yet.

Speaker 1: 2:41

Yeah, and the first thing that jumped out at me was just how like fuzzy the definition is. What even is AI literacy Depends on who you ask.

Speaker 2: 2:49

There's no one agreed upon definition.

Speaker 1: 2:51

Right. You have the EU with the AI Act and they're coming at it from a legal perspective focusing on high risk AI applications.

Speaker 2: 2:58

So making sure it's transparent, that it's fair, that it's accountable.

Speaker 1: 3:02

And then you have UNESCO right and they're trying to apply this broader definition of literacy to AI.

Speaker 2: 3:10

They talk about being able to identify, understand, interpret, create, communicate and compute.

Speaker 1: 3:15

It's a mouthful, but basically, with AI that means everything from like knowing how to use a basic tool to really being able to explain what its outputs mean and how it got there.

Speaker 2: 3:26

It's a very broad spectrum. And then this leads to a question the paper asks Are we talking about building AI, deploying it or simply using it?

Speaker 1: 3:34

And the answer, of course, depends on who you are.

Speaker 2: 3:37

Right, like, if you're building AI systems, then obviously AI literacy is going to look different for you than for someone who's just using those systems in their work.

Speaker 1: 3:48

Absolutely so. For those who build AI you know, the developers, the data scientists it's very technical, but for policymakers, it's more about understanding the big picture.

Speaker 2: 3:53

The societal impact, the ethical considerations, the legal frameworks.

Speaker 1: 3:57

But for most people, for most professionals, it comes down to being able to understand what the AI is telling us.

Speaker 2: 4:03

And being able to spot potential problems like is it biased, Is it making mistakes?

Speaker 1: 4:08

And the paper makes a really important point here, which is that, without a clear shared understanding of what AI literacy means, companies are just going to come up with their own definitions.

Speaker 2: 4:19

Which could lead to some serious gaps in how people are trained and prepared.

Speaker 1: 4:23

It's like everyone's trying to play the same game, but with different rule books.

Speaker 2: 4:27

And then the paper goes on to talk about these fragmented approaches within companies.

Speaker 1: 4:31

Which basically means that the people building the AI and the people using the AI often aren't on the same page.

Speaker 2: 4:38

They're in silos right.

Speaker 1: 4:39

Exactly, and the paper uses the finance industry as an example. You might have analysts who are great at understanding the data that comes out of an AI model.

Speaker 2: 4:47

But then the executives making decisions based on that data might not understand the limitations of the model.

Speaker 1: 4:52

Or even how to properly interpret the results.

Speaker 2: 4:55

And that can lead to some risky situations. You could end up making bad decisions, missing opportunities or even running into regulatory issues.

Speaker 1: 5:02

It's like driving a car without knowing how the engine works. You might be able to get from A to B, but you're going to be in trouble if something goes wrong.

Speaker 2: 5:10

Which brings us to another important point. The paper makes the danger of treating AI literacy as just a box-ticking exercise.

Speaker 1: 5:18

Like, oh, we did the training, we're good. But without really understanding the underlying concepts we're good, but without really understanding the underlying concepts. It's like giving someone a super complex piece of machinery with only like a two-page instruction manual.

Speaker 2: 5:31

They can probably do the basic stuff, but as soon as they run into a problem they're lost.

Speaker 1: 5:36

Exactly, and the paper really stresses that true AI literacy goes beyond just knowing how to use the tools.

Speaker 2: 5:43

It's about understanding the data that goes into these systems.

Speaker 1: 5:47

Recognizing their limitations.

Speaker 2: 5:48

And being able to question the outputs.

Speaker 1: 5:50

Because we've seen examples of AI going wrong right.

Speaker 2: 5:53

Yeah, cases where it's been biased or inaccurate.

Speaker 1: 5:56

If you're blindly trusting the AI, that can lead to some serious consequences.

Speaker 2: 6:00

So critical thinking is a huge part of AI literacy. Don't just accept what the AI tells you. Question it, dig deeper.

Speaker 1: 6:07

OK, so let's move on to part two, where the paper really tries to define AI literacy in a more structured way.

Speaker 2: 6:14

And they start by looking at how the concept of literacy itself has evolved over time.

Speaker 1: 6:18

Right, because being literate doesn't just mean being able to read and write anymore. It's much broader than that, yeah, like back in the 19th century. That's basically all it meant, but things have changed.

Speaker 2: 6:28

Yeah, UNESCO, for example, their definition of literacy from 2004 is much more about understanding and using information effectively.

Speaker 1: 6:35

They talk about being able to, like, identify, understand, interpret, create, communicate and compute using written materials.

Speaker 2: 6:43

So it's not just about passively consuming information, it's about actively engaging with it.

Speaker 1: 6:48

And the paper draws a parallel here to AI literacy. It's not just about having a surface-level awareness of AI.

Speaker 2: 6:55

It's about understanding how it works, what its implications are and how it's changing society.

Speaker 1: 7:00

And they also make this interesting comparison to Internet literacy, which we all went through back in the 90s and 2000s.

Speaker 2: 7:05

Yeah, remember when the internet first came out. It was all about just being able to get online.

Speaker 1: 7:10

Right, like I can access a website, I'm good.

Speaker 2: 7:12

But as the internet became more integrated into our lives, internet literacy had to evolve as well. Because it wasn't enough to just be online you had to be able to evaluate the information you were finding online.

Speaker 1: 7:22

Tell if a website was credible or not.

Speaker 2: 7:24

Protect to evaluate the information you were finding online.

Speaker 1: 7:25

Tell if a website was credible or not Protect your personal information, and the American Library Association. They actually came up with a definition of digital literacy in 2013 that captures this really well. They say it's about being able to find, evaluate, create and communicate information using technology, and it's really interesting. The paper points out that the UN declared Internet access a human right in 2016.

Speaker 2: 7:46

Which shows just how important digital literacy had become for participating in society and the economy.

Speaker 1: 7:54

It was no longer a luxury, it was a necessity.

Speaker 2: 7:56

And it seems like AI literacy is on a similar trajectory.

Speaker 1: 7:59

Absolutely and recognizing the power of AI, the EU Commission released their guidelines on trustworthy AI back in 2019.

Speaker 2: 8:07

Which emphasized ethical considerations, transparency and accountability.

Speaker 1: 8:11

And they specifically said that people need AI literacy to understand how AI is impacting their lives.

Speaker 2: 8:17

So fast forward to the 2020s, and this is where the paper says AI literacy really started to emerge as its own distinct concept.

Speaker 1: 8:24

the paper says, ai literacy really started to emerge as its own distinct concept, and they highlight the EU AI Act here, which came into effect in 2024 and actually includes requirements around AI literacy.

Speaker 2: 8:33

Which is huge. Now organizations actually have a responsibility to make sure their employees have enough AI literacy to do their jobs safely and effectively.

Speaker 1: 8:41

And the paper points out that those requirements are going to start being enforced in February 2025. So it's not far off.

Speaker 2: 8:47

There's a real sense of urgency now.

Speaker 1: 8:49

For sure, and the paper also mentions the first academic definition of AI literacy from 2020.

Speaker 2: 8:54

It was by Jerry Long and Brian McGurko.

Speaker 1: 8:56

And they define it as a set of competencies that enables individuals to critically evaluate AI technologies, communicate and collaborate effectively with AI and use AI as a tool online, at home and in the workplace.

Speaker 2: 9:09

It's a mouthful, but it basically covers all the bases.

Speaker 1: 9:12

It's pretty comprehensive. And then we have CFTE's own definition, which the paper presents as the ability to understand, evaluate and confidently use AI technologies. Evaluate and confidently use AI technologies, recognizing both their capabilities and limitations in personal, professional and societal contexts.

Speaker 2: 9:30

It involves not only practical interaction with AI tools, but also critical thinking, informed decision-making and ethical responsibility.

Speaker 1: 9:38

So it's not just about using the tools, it's about using them responsibly and thoughtfully.

Speaker 2: 9:42

And CFTE breaks AI literacy down into five core components, which are really helpful for understanding what it actually means in practice.

Speaker 1: 9:50

Okay, let's go through those. So the first one is core knowledge of AI concepts.

Speaker 2: 9:54

This is your foundation, your basic understanding of what AI is, the different types of AI and what they can and can't do.

Speaker 1: 10:00

The paper uses a good analogy here. They compare it to understanding browsers and websites in the early days of the internet.

Speaker 2: 10:06

Like back when we were all using dial-up.

Speaker 1: 10:08

Yeah, you needed that basic knowledge to even navigate online.

Speaker 2: 10:11

And it's the same with AI. If you don't understand the basic concepts, you're going to have a hard time engaging with it in any meaningful way.

Speaker 1: 10:18

OK, so the second component is foundational interaction with AI tools.

Speaker 2: 10:24

This is about being able to actually use AI tools effectively.

Speaker 1: 10:28

Giving them clear instructions, refining the results and understanding their strengths and limitations.

Speaker 2: 10:33

The paper compares this to learning how to use search engines effectively. Like it's not enough to just type in a few words. You need to know how to formulate a good search query.

Speaker 1: 10:43

And it's the same with AI tools you need to know how to get the most out of them.

Speaker 2: 10:46

All right. The third component is critical evaluation of AI outputs.

Speaker 1: 10:50

This is where your critical thinking skills really come in.

Speaker 2: 10:53

It's about being able to assess the credibility of AI-generated content, recognizing potential biases and questioning the reliability of the results.

Speaker 1: 11:02

The paper makes a great comparison to the online world. Here it's like learning to tell the difference between a credible news source and like a fake news website.

Speaker 2: 11:10

You can't just believe everything you read online, and you can't just believe everything an AI tells you, either everything you read online, and you can't just believe everything an AI tells you either.

Speaker 1: 11:17

Okay, the fourth component is awareness of AI risks and ethical considerations.

Speaker 2: 11:21

So, just like with the Internet, there are risks associated with AI and we need to be aware of them.

Speaker 1: 11:26

Like AI, can be used for good or bad, and it's important to understand the potential downsides.

Speaker 2: 11:31

Like bias in AI systems, is a big concern and we need to be able to identify it and mitigate it.

Speaker 1: 11:37

Then there's the whole issue of privacy and data security.

Speaker 2: 11:40

And the paper compares this to understanding online privacy risks and learning how to protect your data.

Speaker 1: 11:46

Like, we've all learned to be careful about what information we share online, and we need to apply that same caution to AI.

Speaker 2: 11:53

Right, because AI systems are often collecting and processing huge amounts of data.

Speaker 1: 11:57

And finally, the fifth component is comfort and confidence in engaging with AI.

Speaker 2: 12:02

This is about feeling comfortable using AI tools, recognizing where they're being used around you and developing a balanced perspective on AI.

Speaker 1: 12:10

It's like remember when online banking first came out. A lot of people were hesitant to use it.

Speaker 2: 12:14

They didn't trust it. They were worried about security.

Speaker 1: 12:17

But now most of us use online banking without even thinking twice about it.

Speaker 2: 12:21

And it's the same with AI as we become more familiar with it, we'll start to feel more comfortable using it.

Speaker 1: 12:27

And importantly, this comfort can also help us feel less anxious about the future.

Speaker 2: 12:32

Like we're not going to be replaced by robots tomorrow. Hopefully not, but AI is going to change the way we work and live, and the more comfortable we are with it, the better prepared we'll be.

Speaker 1: 12:45

So those are the five core components of AI literacy, and in part three the paper takes these components and turns them into what they call minimum criteria to be AI literate.

Speaker 2: 12:55

So it's like a checklist of sorts.

Speaker 1: 12:56

Yeah, it's about making AI literacy more concrete by setting out some basic standards.

Speaker 2: 13:01

And the paper really stresses that meeting these criteria is essential for making good decisions in a world that's increasingly driven by AI.

Speaker 1: 13:08

It's like think about traditional literacy If you can't read or write, you're going to have a hard time participating in society.

Speaker 2: 13:14

And it's the same with AI literacy If you don't understand or write, you're going to have a hard time participating in society. And it's the same with AI literacy If you don't understand the basics, you're going to be at a disadvantage.

Speaker 1: 13:20

So let's go through these minimum criteria For foundational knowledge of basic AI concepts. The minimum is just having a grasp of what AI is and what it can do.

Speaker 2: 13:30

For foundational interaction with AI tools. It's about being able to use common AI applications and understand the basic results.

Speaker 1: 13:38

For critical evaluation of AI outputs. It's being able to question AI-generated content and check if it's reliable.

Speaker 2: 13:46

For awareness of AI risks. It's about recognizing potential problems with AI and understanding the importance of using it responsibly.

Speaker 1: 13:54

And finally, for comfort and confidence in engaging with AI. The minimum is feeling comfortable using AI in your everyday life, recognizing where it's being used.

Speaker 2: 14:02

And the paper suggests that meeting these minimum criteria is what allows you to thrive in an AI-driven future. Catchy right, it definitely gets the point across.

Speaker 1: 14:10

All right, so let's move on to part four, which is called Bonus Beyond the Basics.

Speaker 2: 14:14

And here the paper makes it clear that having a foundational understanding of AI literacy is really just the first step.

Speaker 1: 14:20

It's like you've learned to read, but now you need to learn how to write a novel.

Speaker 2: 14:24

Exactly Because AI is evolving so quickly, continuous learning and adaptability are absolutely crucial.

Speaker 1: 14:32

You can't just learn the basics and expect to be good for the rest of your career.

Speaker 2: 14:35

You need to keep up with the latest developments.

Speaker 1: 14:38

And the paper references a book here called the AIfication of Jobs by Huren Guyen-Tri, which talks about how AI is going to transform different industries.

Speaker 2: 14:49

And the key takeaway is that while AI will automate some tasks, it's also going to create new opportunities. Will automate some tasks.

Speaker 1: 14:55

it's also going to create new opportunities and it's going to emphasize the importance of those uniquely human skills like strategic thinking, creativity and empathy.

Speaker 2: 15:02

So the future isn't about being replaced by robots. It's about working alongside AI and figuring out how to use it to our advantage.

Speaker 1: 15:09

And the people who thrive in this new world are going to be those who are adaptable and willing to learn new things.

Speaker 2: 15:14

And CFTE calls these people supercharged professionals.

Speaker 1: 15:18

So they're not just using AI, they're using it strategically to enhance their existing skills and become even more effective.

Speaker 2: 15:25

It's like you're already good at your job, but now you're using AI to amplify your abilities.

Speaker 1: 15:30

And the paper makes a really interesting point here, which is that the pace of change in AI is much faster than what we saw with digital literacy.

Speaker 2: 15:38

Like the core concepts of digital literacy, have stayed pretty consistent over time, even as new tools have come and gone.

Speaker 1: 15:45

But with AI things are changing so rapidly.

Speaker 2: 15:48

Like just a couple of years ago, AI was still pretty limited in its capabilities.

Speaker 1: 15:52

But now it can create entire virtual world and automate complex tasks that were previously thought to be impossible for machines to do.

Speaker 2: 16:00

And the paper gives some specific examples of this rapid advancement, like look at OpenAI's chat, gpt.

Speaker 1: 16:05

Yeah, it's gone from GPT-3 to GPT-4.0 in a very short amount of time. Yeah, it's gone from GPT-3 to GPT-4.0 in a very short amount of time.

Speaker 2: 16:09

And GPT-4.0 is significantly better at understanding patterns, generating creative text formats, being more accurate and reducing hallucinations.

Speaker 1: 16:17

And it even has this new thinking capability in O1 Preview for complex reasoning tasks.

Speaker 2: 16:22

And then there's Anthropic's CLAWD 3.7 Sonnet model, which is faster, more transparent in its reasoning process and has a new tool called Claude Code that can even help with software development.

Speaker 1: 16:34

So the point here is that if you want to stay ahead of the curve, you need to be continuously learning about AI.

Speaker 2: 16:41

You can't just learn the basics and expect to be set for life.

Speaker 1: 16:44

You need to keep up with the latest tools and technologies.

Speaker 2: 16:47

And the paper highlights some research that shows that professionals are actually starting to recognize this.

Speaker 1: 16:52

Like a LinkedIn study found that a large majority of European professionals are eager to integrate AI into their work and believe it will boost their careers.

Speaker 2: 17:02

And the World Economic Forum is predicting a 51% change in required job skills by 2030.

Speaker 1: 17:08

So it's clear that AI is going to have a significant impact on the future of work.

Speaker 2: 17:12

And the people who are going to succeed are those who embrace this change and are prepared to learn and adapt.

Speaker 1: 17:17

And the paper ends with this great concept of the supercharged professional.

Speaker 2: 17:21

They're not just AI literate. They're using AI strategically to enhance their human skills and become even more productive.

Speaker 1: 17:27

And we're already seeing evidence of this happening.

Speaker 2: 17:37

LinkedIn found that there's been a 177% surge in AI literacy skills added to member profiles since 2023. And studies have shown that companies that adopt AI are seeing significant productivity gains.

Speaker 1: 17:43

So it's clear that AI literacy is a good investment, both for individuals and organizations.

Speaker 2: 17:48

All right, let's move on to part five, which is all about building an AI literate workforce.

Speaker 1: 17:54

And the key point here is that, as AI continues to transform industries, we need to be thinking about the AI literacy needs of different roles within those industries.

Speaker 2: 18:04

Because it's not a one size fits all approach.

Speaker 1: 18:06

Right, and the paper makes a really important distinction here, which is that the vast majority of the workforce something like 85% are going to be AI users.

Speaker 2: 18:14

Not AI builders.

Speaker 1: 18:15

So only about 15% of the workforce are actually going to be developing the AI systems.

Speaker 2: 18:19

The rest of us are going to be interacting with those systems in our everyday work.

Speaker 1: 18:22

So the focus of AI literacy efforts needs to be on those users.

Speaker 2: 18:25

They need to be able to effectively operate AI tools.

Speaker 1: 18:29

Understand the insights those tools provide.

Speaker 2: 18:31

And critically assess the outputs.

Speaker 1: 18:33

The paper gives some good examples here, like in retail, you have customer service chatbots that are powered by AI.

Speaker 2: 18:39

And in healthcare there are AI diagnostic tools that can help doctors make more informed decisions.

Speaker 1: 18:45

And the LinkedIn 2024 Future Work Report found that, while AI and machine learning are some of the most in-demand skills right now, less than 30 percent of the global workforce feels confident in their AI abilities.

Speaker 2: 18:58

So there's a big gap there and we need to address it.

Speaker 1: 19:00

And to do that, the paper suggests a structured approach to AI literacy education, and they use Bloom's taxonomy as a framework.

Speaker 2: 19:08

Which is basically a way of organizing learning into different levels.

Speaker 1: 19:11

It goes from remembering basic facts to creating new knowledge.

Speaker 2: 19:14

And the paper applies these different levels to different segments of the workforce.

Speaker 1: 19:18

So, for the 15% who are building AI, the focus is on the create level, which is about designing, developing and programming AI systems.

Speaker 2: 19:26

For business leaders and executives. The focus is more on the evaluate and analyze levels.

Speaker 1: 19:31

They need to be able to make decisions about how to adopt AI, assess the risks and understand the implications.

Speaker 2: 19:38

And then for frontline workers and general employees, the focus is more on the apply and understand levels.

Speaker 1: 19:45

They need to be able to use AI tools effectively in their daily tasks and understand how those tools work.

Speaker 2: 19:51

So this targeted approach helps to ensure that everyone gets the right level of AI literacy training.

Speaker 1: 19:56

Makes sense. And then the paper outlines five practical ways to actually embed AI literacy within an organization.

Speaker 2: 20:03

So the first one is to establish a strong understanding of AI fundamentals.

Speaker 1: 20:08

And this involves providing some basic introductory training on AI concepts.

Speaker 2: 20:12

And the paper suggests using relatable examples like how Netflix recommends movies or how Siri works.

Speaker 1: 20:17

The second way is to promote practical proficiency with AI tools.

Speaker 2: 20:21

So this is about providing task-specific training on the AI tools that are relevant to different roles within the organization.

Speaker 1: 20:28

And the paper draws a parallel here to how we all learn to use email and digital calendars.

Speaker 2: 20:33

They were new tools at one point, but now we use them every day without even thinking about it.

Speaker 1: 20:37

The third way is to encourage critical evaluation of AI outputs.

Speaker 2: 20:41

And this is about creating a culture where people feel comfortable questioning the results they get from AI tools.

Speaker 1: 20:47

The paper suggests having critical thinking sessions where teams can analyze AI recommendations and discuss their validity.

Speaker 2: 20:54

It's like when we were all learning about the internet, we had to learn how to evaluate the credibility of websites.

Speaker 1: 20:59

And it's the same with AI. We can't just blindly accept what it tells us.

Speaker 2: 21:03

The fourth way is to instill responsible and ethical use of AI.

Speaker 1: 21:09

So this involves providing training on things like bias and AI, data privacy and relevant regulations like GDPR and the EU AI Act.

Speaker 2: 21:18

And it's important to have clear guidelines for how AI should be used within the organization.

Speaker 1: 21:23

Like back in the early days of the internet, there were a lot of public awareness campaigns about data privacy.

Speaker 2: 21:27

It's like don't share your personal information online.

Speaker 1: 21:30

And we need that same level of awareness around the ethical use of AI.

Speaker 2: 21:33

And finally, the fifth way is to foster a culture of continuous learning and adaptability.

Speaker 1: 21:38

So this means providing regular opportunities for employees to learn about new AI technologies and how they can be applied to their work.

Speaker 2: 21:46

And encouraging experimentation.

Speaker 1: 21:48

It's like we all had to adapt when smartphones and cloud computing came along.

Speaker 2: 21:52

And now we're going to have to adapt to things like AI-generated media and advanced automation.

Speaker 1: 21:58

So those are the five ways to embed AI literacy within an organization, and the paper also acknowledges that there are some challenges that companies might face when trying to do this.

Speaker 2: 22:08

Like. One challenge is overcoming skill gaps.

Speaker 1: 22:11

Which is basically when employees who don't have a technical background feel overwhelmed by AI.

Speaker 2: 22:17

And the paper suggests using familiar tools as a start point.

Speaker 1: 22:20

Like Google Assistant or Grammarly.

Speaker 2: 22:22

They're both powered by AI, but they're not intimidating.

Speaker 1: 22:25

Another challenge is resistance to AI adoption.

Speaker 2: 22:28

Which can often come from a fear of job displacement.

Speaker 1: 22:30

Like, the robots are coming for our jobs.

Speaker 2: 22:31

But the paper provides some examples of companies that have successfully reskilled their workforce to work alongside AI.

Speaker 1: 22:38

Like Walmart, implemented an AI system for inventory management.

Speaker 2: 22:43

And instead of laying off employees, they retrain them to work with the new system.

Speaker 1: 22:47

Another challenge is keeping pace with technological change.

Speaker 2: 22:52

Because AI is evolving so quickly, it can be difficult to keep training programs up to date.

Speaker 1: 22:57

And the paper suggests conducting regular AI skill audits to make sure that employees are staying current.

Speaker 2: 23:03

Then there's the challenge of choosing the right training partner.

Speaker 1: 23:06

Because companies can either develop their own AI literacy programs or partner with an external provider.

Speaker 2: 23:12

And both approaches have their pros and cons.

Speaker 1: 23:15

The paper highlights some successful partnerships here, like the Central Bank of Egypt partnering with CFTE to develop a scalable AI literacy program.

Speaker 2: 23:23

And finally, there's the challenge of training as a budget-driven checklist.

Speaker 1: 23:27

Which is when companies focus more on meeting training quotas than on actual skill development.

Speaker 2: 23:32

It's like they're just checking boxes instead of really investing in their workforce.

Speaker 1: 23:36

And the paper cites a CIPD study from 2023 that found that this is a real problem.

Speaker 2: 23:42

Companies are prioritizing budget compliance over meaningful upskilling.

Speaker 1: 23:46

So, to wrap things up, let's go back to the conclusion of the white paper.

Speaker 2: 23:49

They do a great job of summarizing the key takeaways.

Speaker 1: 23:51

Absolutely. The main point is that AI literacy is no longer optional. It's a vital competency for both individuals and organizations.

Speaker 2: 24:00

It's about understanding AI, thinking critically about it and being able to adapt as it continues to evolve.

Speaker 1: 24:05

And the paper restates CFTE's definition of AI literacy, which is the ability to understand, evaluate and confidently use AI technologies, recognizing both their capabilities and limitations, in personal, professional and societal context.

Speaker 2: 24:20

It involves not only practical interaction with AI tools, but also critical thinking, informed decision making and ethical responsibility.

Speaker 1: 24:28

So it's about using AI in a thoughtful and responsible way.

Speaker 2: 24:31

And the paper also reiterates that AI literacy isn't a one-time thing. It's an ongoing process.

Speaker 1: 24:36

We need to be continuously learning and adapting as AI continues to develop.

Speaker 2: 24:40

Which brings us back to that concept of the supercharged professional.

Speaker 1: 24:43

They're not just AI literate. They're using AI to amplify their human skills and become even more effective in their work.

Speaker 2: 24:50

And the paper emphasizes the importance of enterprise-wide AI literacy.

Speaker 1: 24:54

It's not just about the technical folks. It's about everyone in the organization having a basic understanding of AI.

Speaker 2: 25:01

Because the majority of us are going to be AI users, not AI builders.

Speaker 1: 25:05

And we need to be equipped to interact with AI effectively and responsibly.

Speaker 2: 25:09

And while this deep dive has covered a lot of ground, it's really just the tip of the iceberg.

Speaker 1: 25:13

There's so much more to explore in terms of how to best assess AI literacy, how to develop effective training programs and how to sustain AI literacy over time.

Speaker 2: 25:23

And we'll definitely be diving deeper into those topics in future episodes.

Speaker 1: 25:26

So, as we wrap up today, I want to leave you with a final thought to ponder.

Speaker 2: 25:30

AI literacy isn't just about understanding the technology itself.

Speaker 1: 25:33

It's about shaping the future with that technology.

Speaker 2: 25:36

So what does your own journey towards becoming AI literate look like?

Speaker 1: 25:40

How are you going to contribute to shaping this AI-driven world in a positive and inclusive way?

Speaker 2: 25:47

It's a question worth thinking about.

Speaker 1: 25:48

Thanks for joining us on the Deep Dive.

Speaker 2: 25:50

See.