Artificial intelligence is booming and may drive future growth, shaping what the new world order could look like. It will most likely change how we work. However, some experts argue that AI is most likely to affect workers whose tasks are relatively simple and therefore easiest to automate. At the same time, AI will also create new professions and new types of jobs that did not previously exist. While it may be difficult to predict which job profiles will become less relevant or disappear in the future, it is not difficult to identify the types of jobs that are likely to be in high demand and command higher compensation as AI reshapes work and society.
Here are three roles (beyond data scientists and software engineers) that show immense potential in the AI era.
AI trainer
While data scientists and AI engineers who build the architecture may be in high demand, the role of AI trainer should not be overlooked. Many people may not be familiar with what AI trainer do, but they are responsible for ensuring that AI systems are accurate and ethical. The job of AI trainers is to ensure that these systems perform well in real-world scanner when they are available out of labs. Being an AI trainer, you curate and label training data, evaluate and refine AI-generated responses, test edge cases, and fine-tune models, especially large language models (LLMs), to meet business, compliance, and industry-specific requirements.
As an AI trainer, your role involves collaborating closely with engineers and data scientists to ensure that models perform according to the company’s internal goals. AI trainers rely heavily on data-labeling platforms such as Scale and Labelbox, as working with large volumes of labeled data is a core part of training AI models. Once the data is prepared, trainers often use specialised tools to adapt and refine models and then validate model outputs.
To become an AI trainer, one needs both technical knowledge and strong soft skills to succeed. The key prerequisites include technical skills such as data annotation and quality assurance, an understanding of natural language processing (NLP) and machine learning, basic Python proficiency, and knowledge of large language model (LLM) tools and platforms such as Hugging Face and OpenAI’s Playground. Freelance and remote opportunities are plenty for AI trainers, and compensation is competitive, with entry-level salaries starting at around $50,000 per year.
AI auditor
Financial audits may be familiar to many, but the concept of AI auditing is still largely unheard of. However, as regulators tighten oversight, there is a growing demand to monitor AI systems and ensure compliance with established standards. This is where AI auditors step in. An AI audit is essentially a comprehensive health check for an AI system, ensuring it operates fairly, safely, and in compliance with regulations. Audits can be internal or external and typically involve examining system performance across demographic groups to detect disparities, identifying biases in AI outputs, ensuring compliance with regulations such as the EU AI Act, testing system vulnerabilities to prevent failures, and reviewing privacy and data-handling safeguards.
Key skills needed to become an AI auditor include understanding machine learning algorithms and model architectures, risk assessment and management, cybersecurity and threat modeling, regulatory compliance (including GDPR, CCPA, and the AI Act), software testing and quality assurance, and statistical analysis with hypothesis testing. An AI auditor typically starts as a Junior Auditor and can progress through the ranks to Chief AI Risk Officer. In the US, an AI auditor earns an average salary of $95,000 per year.
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AI integrator
An AI integrator is a high-demand role that commands a competitive salary. Also called an AI specialist, this role is not an IT position – it requires someone who understands both technology and business. Simply put, an AI integrator should be familiar with major AI technologies and platforms and know how to implement them at the organizational level. The primary responsibility of an AI integrator is to use AI systems to solve business problems. This involves understanding the data, framing the problem, and ensuring that the AI solution effectively addresses the business opportunity.
While soft skills are important, a deep understanding of underlying mathematics and strong analytical skills are also essential. Individuals with qualifications such as degrees in Econometrics, Physics, or Engineering, who understand the relevant data, are particularly suited for this role. To become an AI specialist, a strong foundation in AI and data science is required. Salaries for an AI specialist in the US start at around $80,000 per year.
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