In which sectors will AI bring about the biggest upheavals?
Generative AI holds the potential to significantly impact industries worldwide over time. For instance, PwC estimates that generative AI could contribute to as much as 14% of global GDP by 2030. We anticipate these impacts to be extensive, affecting various work functions, roles, and industries.
From a functional perspective, we foresee the most substantial impacts around the productivity enhancements this technology could offer to white-collar workers. From a sectoral viewpoint, we believe that life sciences, healthcare, manufacturing, media, and education sectors could be most affected. We also consider the implications of generative AI adoption for social policies and politics at large.
What jobs, or functions, will be most impacted by generative-AI adoption?
Administrative functions, particularly those involving document summarization, calendar management, and data entry, will be significantly impacted as generative AI can already automate a substantial portion of these tasks. This is noteworthy, given that McKinsey estimates managers spend 54% of their time on administrative tasks. Therefore, automating these workflows can significantly impact people's workday.
Coding will also be affected as code generation and code review can already be accomplished by generative AI in certain instances. There will still be a significant need for innovative code authoring and troubleshooting by humans, but this will be supplemented by a generative AI assistant, leading to substantial productivity gains. Microsoft, the owner of GitHub, conducted a study on the impact of its GitHub Copilot product on developer productivity and found that developers who used the technology could complete a task 56% faster than those who did not. Another survey from the company reveals that 92% of US-based developers are already using AI. Additionally, Replit, a software company that enables developers to write, run, and share code, has estimated that its generative AI products for coders boosted productivity by over 30%.
Customer service functions will be disrupted by task automation, efficiency improvements, and enhancements to the overall customer experience. While there will always be a need for human interaction in these functions, the resolution rate through chatbots or voice assistants should significantly reduce the need for customer support agents. McKinsey estimates that generative AI could increase productivity at a value ranging from 30 to 45 percent of current function costs. Similarly, an NBER research paper also estimates productivity gains of up to 35% for support agents, with average increases of 14%. These productivity gains could impact the workforce in this segment. Gartner predicts potential cuts of 20-30% of customer service agents by 2026, while a more dire outlook from Barclays sees up to a 50% reduction in the contact center workforce.
Graphic design is another field that will be impacted by generative AI, with tools like Adobe’s FireFly. Adobe recently shared that over 55% of creative professionals using generative AI tools are experiencing more than 20% time savings.
Which industries could see the most profound impact from the rise of generative AI?
In the life sciences and drug discovery, generative AI can accelerate and improve the drug discovery process, including the creation of new drug molecules, target identification, and drug repurposing. For instance, Insilico Medicine's inClinico, a generative AI tool, has demonstrated a 79% accuracy in predicting the outcomes of Phase II clinical trials. Over 20 pharmaceutical companies are already leveraging their platform, streamlining the drug development process, which is crucial given that 90% of drug development fails at the clinical stage, resulting in significant economic loss.
Healthcare services could also see significant impacts from generative AI, particularly due to the large amount of administrative work in the sector, such as clinical documentation and electronic health records entry. Administrative spending and waste are a significant issue in the U.S. healthcare sector, with a Health Affairs report finding that 15-30% of total health spending is attributed to administrative costs, at least half of which is considered ineffective or wasteful. Furthermore, generative AI can help create personalized treatment plans for patients automatically, based on medical history, symptoms, and physician feedback.
In the manufacturing industry, generative AI can be used to design new products by generating many possible designsand selecting the most optimal ones. Companies like General Motors are already using generative design algorithms to optimize parts and reduce weight in their vehicles.
The media industry, including visual and audio creation for films, short content, video games, and more, should be significantly impacted by generative AI. The technology can assist in creating complex animation, visual effects, or musical sequences that would be time-consuming and expensive to produce manually. How long until we get the first AI generated movie to win an Oscar?
Education services are expected to be impacted by generative AI as well, with personalized lesson plans and educational content for learners. Students can use the technology to research topics more effectively, while faculty can use it for optimized lesson planning.
What could generative-AI mean for social policies, and politics more generally?
With the benefits of generative-AI being mostly centered around worker productivity, this raises questions around the labor force in the future. For instance, Goldman Sachs estimates that two-thirds of US jobs are exposed to AI automation to some degree.
Hence, if generative AI impacts the economy and our professional lives as much as we anticipate, we also expect an inevitable reshaping of social policies.
As automation increases, it's likely that policymakers will need to reassess social safety nets, particularly for those in occupations at high risk of automation. Job retraining programs may become a focal point, helping to equip workers with the skills needed in an AI-driven economy. If AI instead has detrimental effects on human employment, at what point do concepts like universal basic income (UBI) come into play?
However, the policy implications are not limited to employment and federal budgets. AI has the potential to significantly impact privacy and data security, necessitating a fresh look at existing regulations. We could also see malicious use of AI in political spheres on social media. Hence, policymakers will need to address the increasing threat of misinformation and its impact on democratic processes. A problem already pervasive in many countries that will only be amplified.
As with any technological advancement, the key will be in balancing the immense potential benefits of generative AI with the novel challenges it presents.
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