The UK government is doing everything it can to improve AI literacy. From elementary school to graduate school, the plan is to create a pipeline of AI-savvy graduates—people who grew up using AI. Artificial Intelligence Tools as naturally as their parents used calculators or Google.
Some of these uses will be “official” (sanctioned by professors and coursework), some not so much (hello, essays written on ChatGPT).
Chief Curriculum Officer, Pluralsight.
Either way, this new wave of talent will enter the job market with skills that may seem almost magical to the uninitiated.
This is a gift for organizations that are willing to use it. And for those who are not? Well, let's just say Hogwarts graduates without a headmaster are more chaos than magic.
Improving AI literacy from the ground up
The flagship project is TechFirst, a £187 million program aimed at integrating AI education into the school curriculum and equipping a million young people with essential digital skills. At the university level, the government is even funding master's degrees in AI at selected universities.
The vision here is ambitious: an “arc of artificial intelligence learning” that stretches from childhood to higher education, ensuring that students leave university fluent in the technologies shaping the future of work.
The AI workforce is different.
For business leaders, this means that a workforce change is already underway. Soon you'll be hiring employees who are more fluent in new technologies than their managers.
These workers will expect workplaces that reward innovation, encourage experimentation, and allow them to expand their capabilities through artificial intelligence.
And here's the rub: While companies across industries are clamoring for AI skills, many are completely unprepared to harness the talent that's about to walk through their doors.
Five shifts that organizations should work
1. Hiring
In some ways, the fundamentals of hiring won't change. Strong leadership skills still matter. In fact, a recent NBER study found a striking correlation between effective human leaders and effective AI agent leaders. It turns out that good leaders are good leaders, whether they run silicon or carbon.
But in the future, with the support of AI, the value of critical thinking and emotional intelligence (EQ) will grow even higher. To get the most out of AI, you must ask it the right questions, know how to identify and test assumptions, and clearly communicate analysis and findings. EQ will become increasingly important as workers will have to navigate networks of people as well as machines to achieve cooperationAlgorithms for teamwork, persuasion and trust-building skills cannot achieve this.
2. Registration
Traditional onboarding often focuses on mechanics, things like logins, expense systems, and compliance modules that no one remembers. It won't help. AI developers need context: a big picture of the industry, customers, competitors, and strategic challenges. This is the type of knowledge that is often acquired over many years of work, but needs to be transferred more quickly and in a targeted manner to new employees early on.
If they don't understand how their work aligns with the organization's goals, they won't be able to effectively manage AI tools. Imagine throwing a brilliant chess tactician into the rugby coaching staff without explaining the rules of the game or providing him with any information about the team or the opponent. Skills are wasted. Context matters.
3. Goal management
If you're not already using OKRs (objectives and key results), now is the time. AI workers need clarity about what matters most so they can focus their efforts on achieving meaningful results. Otherwise they will be very busy…producing little of value.
4. Software and security
If your IT processes are unnecessarily cumbersome, you will quickly frustrate AI developers. They need access to the right tools at the right time. Endless approval chains kill innovation and employee retention.
Certainly, safety still matters. AI tools can become vulnerable targets if not managed properly, and cyber threats are only increasing. Achieving the balance between speed and security will require an agile security team, clear and pragmatic processes, and clearly defined policies.
5. Networking
Artificial intelligence natives are accustomed to instant answers. But in organizations, not all the answers are in database. They live in people. This means that relationships matter.
Strong EQ will help these employees connect quickly—by sending a Teams message to the right colleague, picking up the phone when needed, and, yes, showing up in person. Team building, informal coffee and casual evenings at the pub are “not good”; they are the social glue that makes AI-powered work actually work.
Lifelong learning: the real difference
This is the biggest one. If there is a single competitive advantage in the age of artificial intelligence, it is whether your culture supports continuous learning.
The education system is being restructured to offer students a starting point on their “artificial intelligence learning path,” but employers need to pick up where schools leave off so that once students become professionals, they can continue to learn new skills throughout their careers.
This will allow employees to keep up with changing technologies. Learning is lifelong, and as technical education evolves, employers have a new role to play.
Why? Because most organizations are already failing due to lack of AI readiness, and we are only at the beginning stages of this revolution. Our research shows that nearly two-thirds (65%) of companies have been forced to abandon AI projects due to a lack of internal skills. It looks like this:
- Using AI to solve the wrong problems
- We launch projects without understanding the tools
- Lack of data or infrastructure needed for success
Meanwhile, the gap between generations is widening. Millennials are 1.4 times more likely than older peers to be deeply familiar with generative AI and 1.2 times more likely to expect major changes to work processes within a year. Compare this to the 91% of senior executives who say they exaggerate their knowledge of artificial intelligence. Yes, you read that right – nine out of ten.
Leaders can't fake it. You don't need to learn to lead in the age of artificial intelligence Pythonbut you need to know what AI tools can (and can't), where they're useful and where they're dangerous. This requires professional development that is continuous, built into workflows, and delivered in formats that are relevant to how people actually learn (on-demand, in short form, in real life). This will ensure you are truly prepared for the next generation of talent.
And the cultural shift isn't just about supporting new hires. Existing employees also need to adopt artificial intelligence tools. Think of it as two groups speaking different dialects: one fluent in “artificial intelligence,” the other in “organizational wisdom.” Both have value, but unless they learn to talk to each other, knowledge will remain fragmented and potential will be wasted.
Final thought
The generation of artificial intelligence is coming, whether it is ready for it or not. They will arrive with new skills, new expectations and, yes, a different language. The question is not whether they will change your organization, but whether you allow that change to be intentional or accidental.
So ask yourself: Will your company be a place where AI will thrive and drive the transformation you envision? Or will you continue to fiddle with the textbook while your competitors score?
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