AI, particularly generative AI, is rapidly being adopted across various business sectors, automating tasks like data analysis, customer service, and supply chain optimization. The technology can boost efficiency by speeding up services and using customer data for informed decision-making and predictions. It's already deployed in infrastructure planning, for example, helping city engineers detect potholes using cameras and sensors. In retail, AI optimizes supply chains by predicting stock needs and engages with customers through virtual assistants. While AI has been used in retail customer service for over a decade, recent advancements in generative AI are expected to transform these functions by producing conversational text for more sophisticated interactions.
The sectors most significantly impacted by AI are those rich in language processing, such as advertising, journalism, consulting, and law. These industries have already begun adopting generative AI technologies. Conversely, sectors like agriculture, mining, manufacturing, and craft and related trades are considered least likely to be affected by AI automation. Despite some uses of AI in agriculture, for instance, with farmers using sensors to monitor crops, these industries are generally less exposed to large-scale AI disruption of manual labor.
Research indicates that AI driven by large language models could affect approximately 80% of the US workforce. AI's ability to identify objects in images and videos (computer vision) is used in social media for content moderation, in healthcare for tumor detection, and in the automotive industry for self-driving features. AI can also make decisions based on image data, like initiating an emergency stop in vehicles. However, AI is not without its flaws; it can "hallucinate" by presenting falsehoods as facts and exhibit algorithmic bias, as seen in AI-driven mortgage lending that showed discriminatory patterns against Black applicants.
Companies like Morgan Stanley are leveraging AI assistants to streamline tasks for wealth managers, while individual investors like Edward Morris have used AI tools like ChatGPT for due diligence, achieving significant returns. Morris claims ChatGPT improved his understanding of complex financial topics and identified investment opportunities. However, experts caution that AI's investment advice can be unreliable due to hallucinations and biases from its training data, emphasizing the need for critical human oversight. Despite these risks, AI is seen as a "game-changer" in fields like tax and accounting, akin to the shift from typewriters to word processors, by automating complex tasks and allowing professionals to focus on more valuable work.
Adoption of AI by businesses has more than doubled, with about 15% of UK businesses using at least one form of AI technology by January 2022, a figure that predates the major advancements in generative AI. Industries most open to AI adoption include IT and telecoms, finance and accounting, and media. Companies like Meta are developing AI agents to enhance customer interactions, allowing personalized advice and customer support without human intervention. While AI can readily answer FAQs, the lack of personalization and human empathy means it may not fully account for individual financial situations or unique goals, highlighting the ongoing need for human involvement in complex decision-making processes.
