These are the new type of jobs created when companies use AI
What type of new jobs will be created when companies use artificial intelligence? 67% of mature organisations are creating new roles for GenAI and 87% of them have a dedicated AI team, according to a survey in Germany, UK and US by market research firm Gartner. Overall, the data and analytics (D&A) team should appoint a Head of AI who is accountable for the development and implementation of strategies within the organisation, Jorg Heizenberg, VP Analyst at Gartner says at the company’s website.
“Advances in AI are creating more different and complex skills such as real-time analytics, in-context learning, or training, versioning and deployment of the ML (machine learning) model.”
He says that in the context of GenAI, chief data and analytics officers should consider hiring a knowledge engineer who focuses on developing ontologies, knowledge graphs, rules or other symbolic models to represent the collective intelligence of the organisation, or insights into a specific business process or domain.
“A model manager should also be on their radar. Model managers ensure the ML model is set up correctly and the processes around it behave as expected through all the steps of its life cycle, including drift monitoring and the selection of existing (foundation) models for (re)use.”
“The addition of an AI ethicist to the D&A team should also be considered. An AI ethicist thinks through the unintended consequences of the use of data and AI and determines how to manage risks and opportunities.”
An earlier survey predicts that globally 90% of companies will use AI by 2025, but Heizenberg says that despite this adoption of new technology, humans are needed. They are giving AI context and drive the adoption of data, analytics and AI in the organisation and change employee behaviours.
“AI’s ability to unpredictably generate false information means that its conclusions can only be used where the results are evaluated and controlled by a human, and where humans can correct errors. So data governance becomes a core aspect.”
He says that efforts to drive decision automation without considering the human role in decisions will result in a data-driven organisation without conscience or consistent purpose.
“Humans remain the key decision makers.”
He also stresses the importance of developing AI skills in general within the company.
D&A leaders must develop data literacy and AI literacy programs for their teams and the enterprise.
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