Generative AI, a type of technology that uses vast amounts of data to create new content like text, videos, images, and more, is expected to replace around 2.4 million jobs in the United States by 2030, according to a recent report by Forrester. This means that automated systems will take over these tasks, making human workers unnecessary.
The report highlights that this impact will primarily affect white-collar jobs. Occupations such as technical writers, social science research assistants, proofreaders, copywriters, and administrative roles could be at risk. In total, it’s estimated that around 11 million jobs in the US may be influenced by generative AI, with a particular focus on white-collar positions.
The report stresses that generative AI is coming after white-collar jobs and that automation, in general, will replace about 4.9 percent of US jobs by 2030. However, it’s important to note that some of these losses will be due to automation technologies that assist frontline workers, as we saw with physical robotics during the COVID-19 pandemic in 2020.
Generative AI is expected to account for nearly 30 percent of the jobs lost to automation by 2030. This means that it will play a significant role in the changing job landscape.
But it’s worth mentioning that the impact of generative AI on jobs in the next few years may not be very noticeable until certain issues are addressed. These issues include intellectual property rights, copyright, plagiarism, model refresh rates, model bias, ethics, and the reliability of model responses.
While generative AI has great potential, it can sometimes produce content that doesn’t make sense. For example, models like ChatGPT may generate text that is coherent but doesn’t provide meaningful customer service, requiring manual intervention to correct.
Companies looking to adopt generative AI will need to hire new talent, including developers, business analysts, prompt engineers, and ethicists. Finding these experts may be challenging as the demand for such skills grows. Additionally, there’s a possibility that automating certain tasks could result in subpar outcomes, but companies might still choose to embrace AI.
To do this effectively, companies will need to identify which jobs benefit the most from automation and provide training to employees in skills like prompt engineering and refining input to achieve specific goals.
In conclusion, the report recommends that companies prepare for the evolving landscape of generative AI by building a workforce strategy that includes investments, guidelines, and checkpoints to navigate the challenges and opportunities it presents.