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Generative Artificial Intelligence: A Growing Market and its Potential Challenges

Summary

The market for generative artificial intelligence (GAI) is projected to reach $59 billion by 2028, as indicated by recent estimates. This technology is being used in various industries, from marketing to insurance. The fastest growth in this market is expected […]

Generative Artificial Intelligence: A Growing Market and its Potential Challenges

The market for generative artificial intelligence (GAI) is projected to reach $59 billion by 2028, as indicated by recent estimates. This technology is being used in various industries, from marketing to insurance. The fastest growth in this market is expected in the consumer goods sector, with an estimated revenue of around $11 billion, followed by the media and entertainment sectors with $8 billion, and then healthcare, business, and automotive industries.

Generative artificial intelligence can be divided into three categories: creators of “base models” trained on large datasets from the internet, infrastructure providers such as computing power, and software providers that adapt the technology to business tasks or industries. While the first two categories are dominated by a few companies due to the need for significant computing power and expertise, there are many more companies in the third category. These companies offer products that use generative artificial intelligence to automate various tasks, such as creating marketing campaigns or writing posts on social media.

Although there is concern that generative artificial intelligence could threaten jobs or even pose a threat to the human race, companies that use it emphasize that its purpose is to optimize human work rather than eliminate it. For example, Jasper, a marketing company, uses generative artificial intelligence to automate various marketing tasks but claims that it will not lead to layoffs but rather the optimization of work.

Generative artificial intelligence also finds applications in legal services and insurance, where it helps automate important tasks such as data collection, analysis, and document preparation. However, due to certain limitations of this technology, such as generating fake data, careful oversight is crucial. Currently, research is being conducted on how generative artificial intelligence can be used to improve client services and expedite processes in insurance companies, such as enhancing data analysis and risk assessment.

The growing implementation of generative artificial intelligence for consumer purposes is also significant. For instance, the messaging app WhatsApp plans to introduce a feature that can instantly draw custom cartoons. Additionally, Meta, the parent company of WhatsApp, Facebook, and Instagram, is working on developing an assistant that can join group conversations and gather information from the internet on a specific topic, such as holiday planning.

As generative artificial intelligence expands into different industries and sectors, it is important to highlight the potentials that can be achieved but also the challenges that arise from its use. Risk management and a responsible approach are key factors in maximizing the benefits of this technology.

Frequently Asked Questions:

  1. What is generative artificial intelligence?
  2. Generative artificial intelligence refers to technology that can create original outputs or content based on patterns and data it has learned.

  3. How is generative artificial intelligence used in marketing?
  4. Generative artificial intelligence is used in marketing to automate various tasks such as creating campaigns or producing social media content.

  5. Is generative artificial intelligence a threat to human jobs?
  6. No, companies that use generative artificial intelligence emphasize that its purpose is to optimize human work, not replace it entirely.

  7. What are some potential applications of generative artificial intelligence?
  8. Generative artificial intelligence can be applied in industries such as marketing, insurance, legal services, and consumer goods.

  9. What are the challenges of using generative artificial intelligence?
  10. Challenges include the possibility of generating fake data and the need for careful oversight to ensure responsible use.

(Source: [Original Article])