ChatGPT’s creator and OpenAI’s founder Sam Altman predicts artificial general intelligence (AGI), or AI agents, will join the workforce in 2025, “materially [changing] the output of companies.”
In this context, we turned to two prominent AI models, OpenAI’s o1 Pro and xAI’s Grok 2. We looked for insights on which jobs and professions could suffer the most with AI agents’ developments in a first moment. Even though, the industry and the markets could benefit from increased productivity and arguably better results, according to Altman’s “Reflections.”
Looking at o1 Pro insights, the advanced model sees three working fields “likely to feel the impact of AI-driven automation.”
First, “customer support and call center roles” could see a drastic change with advanced large language models (LLMs) developments. These LLMs, according to o1, can handle most routine queries, troubleshoot common issues, and escalate the most complex cases.
“Data entry and basic administrative positions” make it the second most-affected job positions by AI agents, given their repetitive nature. The “rules-based work” is “precisely what AI systems excel at,” wrote the artificial intelligence. This could completely eliminate the “manual element” of these roles, for example for categorizing documents.
Finally, “content production and routine copywriting” is the third sector likely to suffer the most from AGI joining the workforce. As explained, a “human touch” may still be need for some specific tasks, but “basic marketing copy, product descriptions, and short-form articles” are activities that AI text generators can already deliver with a satisfactory level – reducing the demand for entry-level copywriters or content creators.
3 most-affected job positions by AI agents, according to OpenAI’s o1 Pro
xAI’s Grok on working positions at risk with AGI developments
Notably, Grok 2 has named the same first two job positions as OpenAI’s o1 Pro. The xAI’s flagship product also mentioned “customer service representatives” and “data entry and administrative assistants” as the top two working positions at risk, for similar reasons.
According to the AI, that can scan the X social media in real time, users are already reporting automation for these roles through chatbots and virtual assistants, which can increase with the advancement of capable AI agents.
As the third item, however, Grok mentioned “translators and interpreters” being potentially highly affected by AGI.
“AI agents can provide real-time, high-fidelity translations across multiple languages, potentially outpacing human translators in speed and accessibility. The efficiency and cost-effectiveness of AI in language translation are already diminishing the demand for human translators.”
Sam Altman, CEO of OpenAI, has declared that 2025 will see AI agents entering the workforce, potentially reshaping productivity. He claims OpenAI knows how to build artificial general intelligence (AGI), with these agents set to autonomously handle complex tasks.
Altman envisions these AI systems contributing significantly across sectors like customer service and research.
Nevertheless, skepticism surrounds Altman’s AGI timeline, with experts questioning the feasibility of such advancements by 2025. Critics highlight challenges in achieving genuine understanding and reasoning. Yet, Altman argues that iterative development and user feedback will guide safety and functionality. Despite the doubts, he sees AI agents as a step towards superintelligence, promising vast scientific and economic benefits.
The introduction of AI agents is expected to be gradual, allowing adaptation in business practices and society. Altman emphasizes a focus beyond AGI towards superintelligence, aiming for tools that could exceed human capabilities.
In conclusion, professions that involve rule-based and repetitive tasks are more vulnerable to AI joining the workforce in 2025. AI agents could perform these tasks with increased productivity, potentially causing job displacement in these sectors. At the same time, these advancements could create new jobs in areas that did not exist in the past.