Olivier Godement, head of product for business products at OpenAI, has identified three major industries poised for significant AI-driven automation in the coming years: life sciences, customer service, and software engineering. Speaking on the “Unsupervised Learning” podcast, the ChatGPT maker’s executive outlined how artificial intelligence will fundamentally transform these sectors.
Life sciences and pharmaceutical companies top Godement’s list of industries facing imminent disruption. Working with companies like Amgen, he explained that drug development involves two key components: research and experimentation, plus administrative processes that consume months or even years. “The time it takes from once you lock the recipe of a drug to having that drug on the market is months, sometimes years,” Godement noted. AI models excel at aggregating and consolidating massive amounts of structured and unstructured data, spotting document changes, and streamlining these time-intensive administrative tasks.
Software engineering represents the second industry on the automation horizon. While Godement acknowledges we haven’t reached a point where “any white collar job” can be automated overnight, he sees clear progress in coding automation. “The automation is probably not yet at the level of automating completely the job of a software engineer, but I think we have a line of sight essentially to get there,” he stated. This prediction aligns with broader industry trends—an Indeed study from October revealed that software engineers, quality assurance engineers, product managers, and project managers were the four tech positions most affected by recent layoffs and reorganizations. AI-assisted coding has rapidly entered most companies’ workflows, making this one of 2024’s most contentious tech debates.
Customer service and sales roles complete Godement’s trio of at-risk industries. He cited his collaboration with T-Mobile to enhance customer experience through AI automation, noting they’re “starting to achieve fairly good results in terms of quality at a meaningful scale.” Godement predicts surprises ahead: “My sense is we’ll probably be surprised in the next year or two on the amount of tasks that can be automated reliably.”
Godement, who joined OpenAI in 2023 after eight years developing products at Stripe, isn’t alone in these predictions. Geoffrey Hinton, the “Godfather of AI,” warned in June that AI will eventually “get to be better than us at everything,” though physical jobs like plumbing remain safer. Hinton specifically identified paralegals and call center workers as highly vulnerable, stating bluntly: “For mundane intellectual labor, AI is just going to replace everybody.”
Key Quotes
The time it takes from once you lock the recipe of a drug to having that drug on the market is months, sometimes years. Turns out like the models are pretty good at that. They’re pretty good at aggregating, consolidating tons of structured, unstructured data, spotting the different changes in documents.
Olivier Godement, OpenAI’s head of product for business products, explained why pharmaceutical companies are prime candidates for AI automation, highlighting how AI models can dramatically accelerate the administrative burden of drug approval processes.
The automation is probably not yet at the level of automating completely the job of a software engineer, but I think we have a line of sight essentially to get there.
Godement provided a measured but concerning assessment of AI’s capability to automate software engineering roles, suggesting complete automation is on the horizon even if not immediately achievable.
My sense is we’ll probably be surprised in the next year or two on the amount of tasks that can be automated reliably.
Speaking about customer service automation based on his work with T-Mobile, Godement predicted that AI’s automation capabilities will exceed current expectations within a very short timeframe.
For mundane intellectual labor, AI is just going to replace everybody.
Geoffrey Hinton, the ‘Godfather of AI,’ offered a stark warning that reinforces Godement’s predictions, specifically identifying paralegals and call center workers as highly vulnerable to AI displacement.
Our Take
What’s particularly striking about Godement’s predictions is the specificity and timeline. Unlike vague futurism, he’s working directly with Fortune 500 companies implementing these solutions today, giving his forecasts credibility. The convergence of opinions between OpenAI executives and independent AI researchers like Hinton suggests we’re past the speculation phase—this disruption is actively unfolding. The irony that software engineers, who built AI systems, may be among the first knowledge workers significantly displaced highlights AI’s rapid capability expansion. Most concerning is the compressed timeline: “the next year or two” leaves little room for workforce retraining or policy adaptation. The pharmaceutical industry automation could be genuinely beneficial if it accelerates life-saving drug approvals, but the customer service and engineering predictions represent potential mass displacement without clear alternative employment paths. Organizations must immediately prioritize workforce transition planning rather than viewing AI purely as a cost-cutting opportunity.
Why This Matters
This analysis from a senior OpenAI executive provides crucial insight into near-term AI disruption across major economic sectors. The pharmaceutical industry’s potential transformation could accelerate drug development timelines, potentially saving lives through faster medication approvals while displacing administrative workers. The software engineering prediction is particularly significant given the tech industry’s central role in the global economy—if AI can automate coding at scale, it fundamentally reshapes one of the highest-paying, most secure career paths of the past two decades.
The customer service automation forecast affects millions of workers globally, as call centers and customer support represent massive employment sectors. Godement’s real-world examples with Fortune 500 companies like Amgen and T-Mobile demonstrate this isn’t speculative—it’s already happening. His timeline of “the next year or two” suggests imminent workforce disruption, giving workers and policymakers limited time to prepare. This aligns with broader warnings from AI pioneers like Geoffrey Hinton, creating a consensus among industry leaders that white-collar job automation is accelerating faster than most anticipated. Organizations and workers in these sectors must urgently develop adaptation strategies.
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Source: https://www.businessinsider.com/openai-exec-3-jobs-ai-risk-automation-olivier-godement-2025-12