Job Creation vs Automation
Artificial Intelligence is known for improving efficiency, delivering accurate results, and streamlining all processes.
A number of people aren’t very accommodating of AI because they worry that AI automation will steal and destroy their jobs. Fortunately for all of us, the truth is that artificial intelligence creates a whole lot of jobs and opens up many avenues.
World Economic Forum said that AI automation would create 97 million new jobs by 2025.
Data sourcing involves collecting and classifying data from various internal and external sources. These data sources are the origination points for all the data that you need. It may be a database, file, or API. Data sourcing gives you access to innumerable data that is like gold in today’s data-driven world.
Not all documents are the same. Even after the AI model has been adequately trained with different datasets for AI automation, there may be errors or doubts in classifying certain documents. In such circumstances, data sourcing specialists provide feedback and help enhance the performance of the AI model.
Data Annotators and Data Labelers
AI automation only works when you have a trained model. Now, who trains the AI model to function? It is us, humans. Data annotation and labeling involve collecting text, audio, image, and video data to build and train the AI model.
Hence, AI creates many job openings for data annotators and data labelers. In fact, the market size of the global data annotation tools is predicted to grow at a CAGR of 27.1% from 2021 to 2028.
You must understand that even with AI automation, humans will always have the ultimate control. Data analysts surf through loads of data and convert it into something more meaningful.
Automation through AI might make the job simpler and quicker for data analysts, but ultimately, you are the one who has to make the decisions based on the available information. The AI model cannot make that decision for you.
One such AI specialist role is an AI Developer. Like data annotators and data labelers, AI automation cannot function without the human involvement of AI developers.
The name says it all. As AI developers, you will have to develop artificial intelligence and integrate it into software and applications.
Today, you can integrate machine learning and AI automation into any process or product to deliver better results. You can use AI and ML in manufacturing and retail, or you can integrate them with a camera to detect vehicles, assess the quality of food, and a whole lot more.
With so many integrations into different processes from all sectors, AI automation has opened up many avenues in DevOps, AIOps, and MLOps, instead of just ITOps.
These avenues require experts who can set up the AI/ML infrastructure and deploy its models, manage and maintain the model and logistics, and improve it for better efficiency.
The scope is also high in our mobile-first world, where around 97% of mobile users use AI-powered, voice assistants. These assistants heavily rely on ML models, thus creating opportunities in Dev/AI/ML Ops.
AI automation is definitely on the track where it creates new jobs for everyone. 63% of CEOs predicted that AI would create more job openings and positively impact the job market, just like the internet had done.
All you have to do is positively embrace this technology and work hand-in-hand with it to deliver more value to all customers.