What does an artificial intelligence specialist do?

2 Skills of an AI specialist

To become an AI specialist, one needs to have a strong background and proficiency in mathematics, statistics, computer science, and programming. An AI specialist should be familiar with the fundamental concepts and techniques of AI, such as algorithms, data structures, optimization, search, logic, and probability. An AI specialist should also be able to use various tools and frameworks for AI development, such as Python, R, TensorFlow, PyTorch, Scikit-learn, or Keras. Additionally, an AI specialist should have good communication, problem-solving, critical thinking, and creativity skills, as well as a curiosity and passion for learning new things and solving complex challenges.

3 Responsibilities of an AI specialist

The responsibilities of an AI specialist may differ based on the type, scope, and stage of the AI projects they are involved in. Generally, they may be responsible for conducting research and literature review on the state-of-the-art methods and solutions in the relevant AI domain, defining and analyzing objectives, specifications, and constraints of the AI system or application, collecting, processing, and exploring data sources and features for the AI system or application, developing, training, testing, and evaluating AI models and algorithms using appropriate tools and frameworks, deploying, monitoring, and maintaining the AI system or application in the target environment and platform, and documenting and presenting results and insights of the AI system or application to stakeholders and users.

4 Career opportunities for an AI specialist

The demand for AI specialists is increasing rapidly as organizations and sectors are increasingly integrating AI solutions into their operations and services. According to the World Economic Forum, AI is expected to create 133 million new jobs by 2022, while displacing 75 million existing ones, thus providing ample career opportunities for AI specialists in various fields and roles. For example, an AI researcher focuses on the theoretical and practical aspects of AI and publishes their findings, an AI engineer builds and implements AI systems, an AI architect designs the overall structure of the AI system, an AI analyst uses data and analytics to measure the performance of the system, and an AI consultant provides expert advice on best practices for using and adopting AI solutions.

5 Challenges for an AI specialist

AI specialists must be aware of the ethical and social implications of their work, such as potential bias, discrimination, privacy, security, accountability, and transparency issues that may arise from the use and misuse of AI systems and applications. They must also be able to handle technical and operational difficulties that may arise during the development and deployment of AI systems and applications, such as data quality, availability, scalability, model robustness, reliability, and explainability issues. Additionally, AI specialists must stay up-to-date with the fast-paced and dynamic nature of the AI field by constantly updating their knowledge and skills to remain competitive.