Artificial Intelligence has dominated headlines for over a year, creating excitement and anxiety. From creating marketing copy to writing complex code, it seems there is very little these new tools cannot do.
This rapid evolution has led many professionals to ask the question: If AI can process data faster than any human, is my role still necessary?
Companies don't just need raw data, they need people who can interpret it, question it, and use it to drive strategy. This skill set is known as data literacy and is becoming highly valuable.
What AI can (and can't) do
To understand your place in this new landscape, it’s helpful to look at the pros and cons. AI is powerful when it comes to volume and speed. It’s an incredible tool for efficiency, automating many tasks.
However, AI operates in a vacuum. It processes data based on the parameters it has been given, without much understanding of real-world context. It doesn't know that a dip in sales might be due to a competitor's flash sale, or that a spike in website traffic coincided with a viral social media trend, unless that data is explicitly fed into it.
Furthermore, AI can struggle with nuance. It cannot “read the room”. It might present a technically accurate data point that is culturally insensitive or strategically irrelevant to the business goals.
The importance of data literacy
Data literacy is the ability to read, write, and communicate data in context. It’s not just about being good at maths or knowing how to write code. It’s about looking at a set of figures and understanding what they represent in the real world, then communicating that insight.
In the past, this was seen as a specialist skill for data scientists or financial analysts. Today, it is a core competency for many roles. Marketing managers need to interpret campaign metrics to justify budgets. HR professionals need to analyse retention data to improve company culture. Even creative roles are increasingly driven by data.
Data literacy is the bridge between the tool (AI) and the outcome (business success). Without it, a company is left with sophisticated tools but no one to guide them.
Human skills that complement AI
As AI becomes more integrated into our workflows, your value will come from the skills that machines can’t replicate. These human-centric skills act as the perfect complement to AI's raw processing power.
Critical thinking and contextual analysis
AI is prone to what experts call "hallucinations", confidently presenting false or misleading information as fact. A data-literate professional applies critical thinking to spot these errors. You have the knowledge and industry experience to look at a result and say, "That doesn't look right".
Effective communication and storytelling
Data on its own is rarely persuasive. To get buy-in from stakeholders or influence a decision, you need to contextualise that data within a story. This involves empathy, understanding what your audience cares about and framing the insights in a way that resonates.
Ethical considerations and bias detection
AI models are trained on historical data, which often contains biases. Without human oversight, AI can perpetuate or even amplify these biases in hiring, lending, or customer targeting. A data-literate professional understands the sources of the data and can spot potential ethical pitfalls, ensuring that the company uses data responsibly.
Developing your data literacy skills
If you feel your skills aren't quite where they need to be, don't worry. Data literacy is a learned skill, not an innate talent. You can start small and build your proficiency over time.
Data literacy courses
One of the most effective ways to upskill is through formal education. Data literacy courses are designed to take you from the basics of understanding data types to advanced interpretation. Kaplan offers a range of financial and data courses that are tailored to different skill levels, ensuring you don't get overwhelmed.
Use the right tools
You don't need to be a coding expert to be data literate. Familiarise yourself with business intelligence tools like Power BI or Tableau. Many data literacy training programmes focus specifically on these platforms, teaching you how to manipulate data and create dashboards without needing to write complex SQL queries.
Frequently asked questions
Do I need to be good at maths to be data literate?
Not at all. While basic numeracy helps, data literacy is more about logic, critical thinking, and communication. It is about understanding the logic behind the numbers rather than performing the calculations yourself, especially since AI can now handle the maths for you.
Will AI eventually replace the need for data literacy?
It is likely to be the opposite. As AI makes data more accessible, there will be more data floating around organisations than ever before. This creates a greater need for people who can filter the noise, validate the findings and apply the insights strategically.
Empower your career with data literacy training
The rise of AI is not a signal to step back; it’s an invitation to step up. By combining the speed of AI with human critical thinking and storytelling, you can become an invaluable asset to any business.
If you are ready to future-proof your career and gain confidence in your analytical abilities, explore Kaplan's range of courses today. Whether you are looking for specific data literacy courses or broader professional qualifications, we have the flexible, expert-led training you need to succeed.