10 Skills You Need For A Career In AI

Jobs requiring AI skills carry a significant wage premium, with some roles offering up to a 25 per cent increase in wages, notes Manoj Nagpal, vice president, professional services, OpenText, an information management company.

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In a world where artificial intelligence is no longer a futuristic concept, 'work profiles' are undergoing a seismic shift.

From automating mundane tasks to enabling complex decision-making, AI is redefining how we interact with technology and, by extension, with each other.

According to a recent report (external link) by the World Economic Forum, 50 per cent of all employees will need reskilling by 2025.

Additionally, with AI capabilities being among the most sought after, this field is expected to create 97 million new jobs by 2025 while simultaneously displacing 85 million old ones.

This domino effect will also have a bearing on organisations because cultivating AI skills across the workforce can lead to transformative outcomes.

As the labour market grows, it has become a stated requirement that AI skills will be essential for career advancement, organisational efficiency and industrial growth.

1. Machine learning: The cornerstone of AI

Machine learning remains an in-demand foundational AI skill.

Mastery of algorithms, data pre-processing and model evaluations is essential.

Platforms like TensorFlow and scikit-learn serve as excellent starting points.

As businesses increasingly rely on predictive analytics and automated decision-making, expertise in machine learning will unlock doors across various industries.

2. Programming languages: Python and beyond

Python is one of the most in-demand programming languages for AI roles.

In fact, it is mentioned in 52 per cent of job postings as per a report (external link) by market research firm IOT Analytics.

The TIOBE Index (an indicator of programming languages that is updated monthly) consistently ranks Python among the top programming languages, reflecting its widespread adoption and utility.

Its flexibility and rich ecosystem of libraries and frameworks such as TensorFlow, Keras, PyTorch and scikit-learn offer pre-written code for creating neural networks, machine learning models and other AI components, significantly reducing development time and effort

Other important languages include R for statistical computing, Java, Julia, Scala, C++, Lisp and Prolog.

3. Natural language processing (NLP)

NLP skills witnessed a 35 per cent rise in job postings in 2023.

With the proliferation of chatbots, virtual assistants and advanced language models, NLP skills are highly sought after.

Familiarity with libraries like NLTK (Natural Language Toolkit) and spaCy enhances capabilities in this area, making it invaluable for improving customer interactions and automating communication tasks.

4. Deep learning

Deep learning skills are in high demand, with a growing trend of job postings from 2022 to 2023.

Mastering neural network architectures and training techniques, along with frameworks like PyTorch and Keras, is becoming essential.

Deep learning applications span computer vision, speech recognition and other complex AI tasks, positioning professionals as experts in cutting-edge technologies.

This market is projected to grow from $3 billion in 2020 to $18 billion by 2025.

5. Data science and analytics

Data science skills remain crucial, with a large number of companies planning to increase their data science teams in 2024.

Proficiency in data manipulation, visualisation and statistical analysis using tools like Python's pandas library and Tableau are essential.

6. AI ethics and governance

As AI adoption grows, the need for ethical AI implementation becomes paramount.

Organisations now consider AI ethics a top priority. Studying bias detection, fairness in AI and privacy-preserving techniques is essential.

Familiarity with AI governance frameworks and regulations ensures responsible AI development and deployment, safeguarding organisations from potential pitfalls.

7. Cloud computing for AI

Cloud-based AI services are increasingly important, with many enterprises utilising cloud-based AI in 2024, with Forbes Global indicating an EBITDA value of $3 trillion.

Learning major cloud platforms like AWS, Azure and Google Cloud, particularly their AI and machine learning services, is necessary for career advancement.

Cloud skills combined with AI expertise can make professionals valuable assets in organisations embracing digital transformation.

According to IDC Research published in July 2024 (external link), cloud AI services are projected to grow at a compound annual growth rate (CAGR) of 23 per cent through 2025.

8. AI-powered automation

Robotic process automation enhanced with AI is transforming business operations.

Exploring various tools and understanding how to integrate AI into automation workflows are vital for improving efficiency and reducing costs in various industries.

Deloitte's recent research explains in detail how AI-driven automation can lead to a reduction in operational costs, improved efficiency and employee creativity.

9. Explainable AI (XAI)

As AI systems make more critical decisions, the ability to interpret and explain their outputs becomes crucial.

This skill is particularly important in regulated industries like finance and healthcare, where decision rationale is often required to build trust.

10. AI security

With increasing reliance on AI systems, securing them against vulnerabilities is paramount.

Understanding concepts like adversarial machine learning and AI model security, along with learning techniques for protecting AI systems against attacks and data breaches, is crucial.

The broader impact of AI skills

The value of AI skills extends beyond individual job fits.

According to PwC, sectors more exposed to AI are experiencing nearly five times higher labour productivity growth than those less exposed.

Organisations using AI reported a 19 per cent increase in revenue and a 16 per cent reduction in costs.

Jobs requiring AI skills carry a significant wage premium, with some roles offering up to a 25 per cent increase in wages.

Moreover, the global AI market is expected to grow to over $1.3 trillion by 2030, driven by a 25 to 35 per cent compound annual growth rate.

AI is an evolving field and some of these skills mentioned above will continue to develop.

Professionals must adopt a mindset of continuous learning to stay ahead.

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