The launch of OpenAIâs new GPT-5.2 model has once again stirred concerns about how Artificial Intelligence could reshape jobs across industries. Adding to the debate, a senior OpenAI executive has pointed out three professional fields that could see the fastest impact from AI-led automation in the near future.
Olivier Godement, OpenAIâs head of product for business products, shared his views during a recent appearance at Redpointâs AI Podcast. While he clarified that large-scale white-collar job losses are not expected to happen overnight, he warned that the pace of change in certain sectors is moving much faster than many anticipated.
AIâs growing role in life sciences and coding
Godement highlighted life sciences and pharmaceutical companies as being especially ready for AI-driven automation. He explained that many of their processes are slow and heavily dependent on documentation, making them well-suited for AI tools.
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âMy bet is often on life sciences, pharma companies,â Godement said. He pointed out that the time-consuming administrative side of drug development could benefit the most. âThe time it takes from once you lock the recipe of a drug to having that drug on the market is months, sometimes years.â
According to him, AIâs ability to âaggregate, consolidate tons of structured and unstructured data, and spot the different changes in documentsâ can significantly shorten these timelines.
Coding is another area seeing rapid transformation. Godement noted that AI-powered developer tools are already boosting productivity for engineering teams around the world. While AI has not fully replaced software engineers yet, he believes the direction is clear.
âThe automation is probably not yet at the level of completely automating the job of a software engineer, but I think we have a line of sight to essentially get there,â he said. He also remarked that removing AI tools from engineers today âwould likely cause a riot.â
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Customer support is the third sector facing major change. Godement cited OpenAIâs work with companies like T-Mobile as proof that AI models are already delivering âfairly good results in terms of quality at a meaningful scale.â He added that people may be âsurprised in the next year or twoâ by how reliably these roles can be automated.
Overall, while AI may not replace all white-collar jobs immediately, coding, customer service and pharma appear to be at the front of the transformation curve.