A report by PwC finds that AI could add $15.7 trillion to the global economy in 2030, potentially boosting GDP by up to 26% in many countries. This surge in economic value is driven by the increased productivity and higher consumer demand. Considering this impact, the ability to leverage AI effectively will be critical for businesses and employees alike to achieve success.

To remain competitive, businesses and employees must develop advanced AI skills that will prepare them for success and help them understand the human benefits they offer, including technical expertise, critical thinking, and ethical understanding. Having such skills allows employees to work effectively with AI tools, whilst also developing AI systems and addressing any challenges and opportunities that come with it.

The top AI skills to consider

• Programming

Programming is a fundamental skill for AI development, and Python remains a popular programming language due to its simplicity and the vast array of libraries, such as NumPy, pandas, and TensorFlow, which support AI and machine learning applications.

• Machine learning

Machine learning is potentially one of the most important skills to have. Understanding different types of learning such as supervised, unsupervised and reinforcement learning – is key to developing AI systems. It also involves implementing algorithms like decision trees, neural networks and support vector machines, enabling AI practitioners to build intelligent solutions that improve over time.

• Data analysis and visualisation

Some additional skills such as data cleaning, processing and visualisation are equally important for preparing data for AI models and interpreting the results. It’s one thing to have data, and another to have ‘good’ data. When well-equipped, workforces can better clean and analyse raw data, removing duplicates or filling in missing values, before training any AI model.

• Problem solving

AI is often used in tackling complex, open-ended problems. Having strong analytical skills and creativity are essential for designing algorithms that can effectively address these challenges and improve over time.

• Ethics and bias awareness

AI systems can unintentionally reinforce biases found in their training data. Recognising these issues and implementing strategies to mitigate bias is essential for creating fair and ethical AI applications. For instance, when developing a hiring algorithm, it's crucial for developers to ensure that the training data does not disproportionately favour certain demographics. Techniques such as using balanced datasets or fairness-aware algorithms can help address potential biases.

• Communication skills

AI professionals often collaborate with cross-functional teams and need to explain technical concepts to stakeholders who may not have a technical background. For example, an AI developer might present the results of a predictive sales model to a marketing team, breaking down how the model works and how it can drive actionable insights. Clear communication ensures that AI solutions are understood and effectively integrated into business processes.

Adapting to change: preparing for the future

As AI continues to redefine industries, the need for AI-related skills is becoming increasingly critical. Businesses that effectively integrate AI into their operations are better positioned to succeed in today’s competitive landscape. AI is a known driver of innovation, yet also boosts productivity, which makes it a critical asset for any business aiming to stay ahead. However, the evolution of AI is not just about understanding complex algorithms but also about recognising the broader impacts that these technologies will have in organisations.

A crucial point to understand is that, to fully leverage AI, employees must focus on both technical proficiency and the development of power skills such as critical thinking, collaboration, and ethical reasoning. It is not enough to program or design AI systems – businesses must also consider the social and ethical implications of AI technologies, ensuring that these tools are used responsibly and inclusively. This is because AI systems can often perpetuate any biases present within training data.

Moreover, as businesses begin to adopt AI more widely, it’s clear that the workforce needs to prepare for ongoing change. Skill development is no longer a one-off event but a continuous journey, which means organisations should, by all means, invest in employee training. In addition, employees must be agile and proactive in learning new tools and techniques, ensuring they stay relevant in an increasingly AI-driven world. To build an effective training strategy, it's crucial to first assess the AI knowledge and skills of your workforce. Conducting baseline evaluations helps identify existing capability gaps, enabling leaders to design a training program that directly addresses those needs. Tracking progress over time ensures that employees continue to develop their skills and remain competent as AI technologies evolve.

Tailored development plans, which include regular feedback and guidance, empower employees to grow in their roles while fostering confidence in their ability to work with AI. Understanding how your organisation intends to use AI, including specific use cases, and comparing these needs with the skills of your workforce is vital.

As AI becomes a more integral part of business strategies, investing in the development of key AI skills will be crucial for success. Companies and employees who embrace this shift and prioritise both technical expertise and ethical understanding will be best equipped to navigate the future of work, driving innovation and maximising the benefits of AI technology for years to come.