McKinsey Global Survey(McKinsey Global Survey)Points out that generative artificial intelligence (gen AI) tools are rapidly impacting industries and workforces. Respondents to the survey revealed that one-third of organizations are already using gen AI tools frequently in some area of their business, with one-quarter of executives and one-quarter of companies already incorporating gen AI into their workflows and board agenda. Additionally, 40% of respondents plan to increase overall AI investment. Although the application of gen AI may increase the adoption of other artificial intelligence tools, there is little material change in the growth of organizational adoption of these technologies. Only a few organizations in business functions have adopted AI tools.
What output can a generative AI model produce?
Generative artificial intelligence models can produce text, images, code, video, audio, etc. Their output may be similar to human-generated content, but its accuracy and appropriateness are not always guaranteed. Generative AI models are widely used in various fields such as entertainment, writing, and program code generation. Enterprises can benefit from generative AI models to quickly generate manuscripts suitable for practical purposes, reducing time and resource costs. Generative AI can also be used to generate technical materials such as medical images. Although developing generative AI models requires significant resources, companies can choose to use off-the-shelf models or optimize them to fit specific tasks.
According to the report, it is expected that knowledge-based industries such as information technology, financial services, pharmaceutical products, and education will be most affected by generative artificial intelligence (generative AI). Previous research has shown that while all industries are likely to be impacted to some extent, industries that rely on knowledge work will be more likely to be significantly affected and likely to capture more value. Information technology players are expected to have the highest impact from generative AI, equivalent to as much as 9% of global industry revenue. In addition, the banking, pharmaceutical and medical products industry, and education industries may also experience significant impacts, with corresponding values that may be as high as 5%, 5%, and 4% of their respective industry revenues. Relatively speaking, manufacturing industries such as aerospace, automobiles and advanced electronics may be less affected. This is because generative AI has advantages in language activities, rather than areas that require physical labor.
However, according to respondents, the main risk associated with generative AI is "inaccuracy." Their output can contain misinformation and bias, and can be easily abused. To mitigate risk, the initial data for training models needs to be carefully selected to avoid toxic or biased content. Additionally, human review and limiting the use of generative AI models can help avoid inappropriate use and legal risks. As this field evolves rapidly, it is critical to pay attention to regulatory and risk dynamics.
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Introduction to generating AI applications (Cantonese only):
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