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Technology> Artificial Intelligence Updated: 14 Aug 2020

New jobs that will arise in the next decade in the data industry

Over the next decade the labor market around Big Data will be shaped by artificial intelligence and automation. Experts predict that in the future there will be new data-related jobs, such as algorithm trainers and maintainers. These are new job positions that will emerge as information management becomes increasingly complex and valuable.


Artificial intelligence business developer, algorithm trainer or personal memory curator. These are just some of the jobs that will arise in the coming years, according to a paper published in 2017 by the Center for the Future of Work. Technology is striding ahead and, with it, the new demands of the labor market. Automation, artificial intelligence and increasing use of robots will mark a “before” and an “after” in the data industry.

By 2019, several emerging Big Data jobs started to take off, according to the report ‘Estado del mercado laboral en España’(‘State of the labor market in Spain’) issued by InfoJobs-ESADE. Supply chain specialists are now in vogue with the rise of e-commerce: they handle the acquisition, production and distribution of goods that a company markets to its customers. The job involves managing a huge volume of data from different sources to optimize supply chain operations. The report stresses that this specialty is not yet part of a university degree course—it consists of a master’s degree that supports specialization.

Another emerging occupation is that of ‘blockchain’ programmer: the role speeds up the exchange of information and valuable assets between the several agents involved in a given process. While data science experts analyze data to extract practical information, the blockchain allows data to be recorded and validated securely and traceably. People hoping to fill this position must be trained in software engineering, telecommunications or electronics.

AI business developers and trainers

This trend is just a sample of how over the next decade companies will have to live with digitalization and focus on mass data analysis to remain competitive. Many of the new jobs that will emerge in future will require specific training not currently provided by universities. Personal memory curators will partner with patients to create virtual environments from their memories using virtual reality, while managers in the genome industry will specialize in the analysis of genetic data. Artificial intelligence business developers, for their part, will specialize in understanding, defining and communicating the business benefits of solutions based on AI technology. “Artificial intelligence is increasingly at the center of product development efforts. However, there is still one thing that artificial intelligence cannot do: sell itself,” says the report in a hypothetical job offer for this profile would be an imaginable reality within the next few years.

IESE Business School Professor José Ramón Pin Arboledas stresses that many jobs that will arise in the coming years will be related to the development of artificial intelligence systems fed by vast amounts of data. “All research work at universities and research centers or in practice--markets or customers--will be enhanced by artificial intelligence machines and algorithms,” he predicted.

In addition to algorithm designers, he also believes that there will be experts who train algos and “help them learn how to make decisions.” Fighting biases in data and understanding which path a model takes to reach a given conclusion are among the greatest challenges for the coming decades. Pin Arboledas thinks that in future it will be a full-time job to explain the usefulness of these algorithms to other humans.

If a model breaks down, there will also be the algorithm maintainers, who will measure and correct faults that build up over time. While some developers give life to new artificial intelligence systems, there will also be those who will prune away the deadwood: “There will be managers who will track the performance of algorithms and switch them off when they make too many mistakes.”