AI Jobs in Future: Many competent and educated people are concerned that Artificial Intelligence (AI) may disrupt or possibly replace their careers given the explosive growth in the use of ChatGPT and other AI technologies across industries. But according to tech experts, AI is just one more tool in a long line of advancements in technology innovations meant to support rather than replace people.
In fact, when AI becomes more widely used, managing it will probably need experts with completely new skill sets, which will increase demand for the creative work done by the millions of qualified employees who currently have jobs. Twenty Forbes Technology Council members discuss potential new careers that artificial intelligence (AI) could produce below, along with current specialties that may see an increase in demand as AI becomes more prevalent.
8 AI Jobs in Future with High Demand
Engineer for Artificial Intelligence (AI)
AI engineers are experts who take advantage of AI and machine learning techniques to create applications and systems that assist businesses become more effective. AI engineering is concerned with the creation of tools, methods, and procedures that allow AI to be applied to real-world situations. Algorithms are “trained” by data, which allows them to learn and perform better. Ai engineers can help decrease expenses, enhance efficiency and revenues, and provide business recommendations.
Designers of Interfaces and Interactions
Even if you believe ChatGPT is simple to understand, not everyone does. Interface and design professionals may be responsible for making AI products easier to use and accessible for more people.
OpenAI, the creator of ChatGPT, recently released a version of the chatbot that responds to voice commands, which was most likely the result of the work of AI designers.
Today, generative AI relies on current data, most of which is repetitive and tedious. Writers and influencers who can create intriguing, attention-grabbing content for AI systems will be in high demand in the future. Consider today’s influencers, but on a far larger scale. Mitek Systems’ Chris Briggs
Engineer in Machine Learning
Machine learning engineers are people that conduct research, design, and create the AI that is responsible for machine learning. A machine learning engineer typically acts as a point of contact with other data science team members, collaborating with data scientists who create models for AI systems. They execute trials and testing, statistical analysis, and the development of machine learning systems.
Data Curators and Educators
AI technologies such as ChatGPT are trained using massive amounts of data from books, papers, and web pages, but the quality of a chatbot’s output is just as high as the data used to train it.
Data curators and trainers will be in charge of monitoring and assessing the data that feeds into AI models.
“Data quality and integrity checks are critical, and will lead to the development of a dedicated, specialized workforce,” according to a World Economic Forum research.
Manager of AI Compliance
With rising regulation and scrutiny around AI applications, companies will inevitably require professional compliance officers who understand the complexities of AI-related rules and norms. To mitigate potential legal and reputational concerns, these professionals will guarantee that AI systems adhere to legal and ethical norms, dealing with data protection, bias, and algorithmic transparency. – Intellisystem Technologies, Cristian Randieri.
Engineers in robotics provide robotic applications for a wide range of sectors, including automotive, industrial, defence, and medicine. Some may operate on-site at a manufacturing factory, supervising the production of robots, while others check their performance in the field. Robotics engineering blends mechanical and electrical engineering aspects with computer science.
Primary responsibilities: In controlled experiments, research scientists collect data and information. In a range of businesses, including AI research, they may design lab experiments, investigations, and testing. Specific responsibilities may include designing experiments, collecting data, analyzing it, publishing research articles, and presenting findings at scientific conferences.