Artificial intelligence is rapidly changing the job market by creating new roles while automating routine ones. According to a report by the IMF, AI integration is expected to create 2.7 million new tech jobs in India by 2030. This expansion is predicted to benefit various industries, including retail, finance, healthcare, and education. As the job market evolves, it is important for you to keep up with how AI is likely to affect tech roles and create opportunities.
AI trainers and prompt engineers
AI systems like ChatGPT work on a conversational model where the user enters a prompt, and the system responds. AI tools like these learn by interacting with the users. Therefore, businesses and organisations need artificial intelligence trainers and prompt engineers to train these systems according to their business needs. Artificial intelligence trainers feed data into the system by creating appropriate prompts to produce precise and relevant responses. AI training professionals are in charge of providing the system with accurate data, assessing its replies, and ensuring that accuracy rates improve with time.
Machine learning (ML) engineers
ML engineers are tech professionals who develop and train AI systems so that the system can learn on its own and adapt over time. ML engineers need to have a strong background in computer science, math, and statistics, along with knowledge of programming languages like Python. They create AI models and algorithms for a variety of institutions, including governments, commercial companies, and international organisations. As the need for AI tools and systems continues to develop, there will likely be a considerable growth in the requirement for machine learning engineers.
Experts in AI policy and ethics
With AI’s rapid development, ethical issues are growing increasingly common. AI ethics and policy specialists are experts who concentrate on the various ethical and policy implications of AI. They ensure that AI systems used by tech companies and others adhere to ethical standards. This means ensuring that AI systems are developed and used in an ethical manner, that the data they produce is free from bias, and that AI technology conforms with data privacy laws.
Cybersecurity specialists
Threats and attracts are becoming more sophisticated with the use of AI, making cybersecurity one of the most promising fields of employment today. Companies hire AI cybersecurity specialists to use machine learning models and create systems that detect and prevent cyber threats. These systems are also capable of neutralising cyber threats in real time to ensure optimum risk management.
Robotics Process Automation (RPA) developers
New job opportunities for RPA developers are expected with AI advancements. RPA developers integrate AI-powered automation into existing business models to help streamline operations. They are responsible for designing, developing, and deploying software bots that automate repetitive tasks like customer queries to improve efficiency and reduce costs. Companies across tech, finance, healthcare, retail, and logistics sectors hire RPAs to leverage AI.
Data scientists
Data scientists are expected to have a 36% growth in employment between 2023 and 2033, according to the US Bureau of Labor Statistics, making this occupation one of the fastest-growing occupations. Data scientists work together with ML engineers and software developers to create and improve AI systems. To identify trends and patterns in programming languages, they are responsible for collecting, analyzing, and understanding complex data sets. Data scientists design experiments used for training and testing AI models to help them become more reliable and accurate. They also help businesses and organizations understand the data generated by AI systems so they can make better decisions.
Skills required to build AI-driven careers
Although artificial intelligence is extending current career prospects and opening up new ones, there is a discrepancy between the supply and demand for workers with AI training. The following abilities are now necessary to establish a successful AI-driven tech career:
- Programming language proficiency: Knowledge of key programming languages like Java, Python, and C++ is required in order to write and develop AI models.
- Data expertise: Understanding data processing, warehousing, and modelling is essential.
- Expertise in machine learning: It is essential to have knowledge of deep learning frameworks and reinforcement learning.
- Natural language processing: In order to create AI programs that can comprehend and process human languages, natural language processing is crucial. It is employed in the creation of chatbots that have speech recognition capabilities.
Problems with implementing AI
The use of artificial intelligence by the technology sector raises the following concerns:
- Concerns about the stability of employment for people performing manual labour that will soon be automated.
- Skills gaps in the workforce that prevent AI from being used effectively.
- Ethical concerns about data privacy and unfairness in AI algorithms.
Summing it up
The integration of AI has changed every aspect of our lives – from lending organisations like NBFCs to shopping platforms like online marketplace. This influence also extends to work. Advancements in AI are changing the future of work in the tech industry rapidly. The widespread adoption of AI is not replacing workers but simply reshaping roles and responsibilities. It is creating an array of new job opportunities for tech workers, including positions like AI trainers, AI ethics specialists, and machine learning engineers. However, the growth of opportunities in the tech sector is linked to the reskilling of workers to help them transition into new roles.
