Article reprint source: AIGC
Original source: AIGC Open Community
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On October 4, Gartner, a world-renowned information consulting and research organization, released a survey data on its official website, showing that 55% of organizations are using or experimenting with generative AI; more than half of the organizations have increased their investment in generative AI in the past 10 months.
This time, Gartner surveyed a total of 1,419 corporate executives/leaders, 45% of whom said they were in the trial period of generative AI, and 10% had already put it into actual business.
This is a significant increase compared to Gartner's survey data on generative AI applications in March this year (15% were experimenting, 4% had already been applied), which shows that companies are actively trying to implement scenario-based applications of generative AI.
What is Generative AI
Generative AI is a type of AI based on deep learning and neural networks, such as generative adversarial networks and variational autoencoders, combined with massive data pre-training and fine-tuning, which can automatically generate code, pictures, text, video, audio, games, etc. through text question and answering.
The working principle of generative AI is to learn from a large amount of data, understand its underlying patterns and structures, and then create new, similar but not identical data based on this understanding. For example, given 10 papers, generative AI can write a brand new paper based on these data.
Generative AI products represented by ChatGPT, Midjourney, Bard, Claude, and Stable Diffusion have a profound impact on global industries, employment, and the economy, and are reshaping business processes and operating models, thanks to their simple and easy-to-use text conversation methods.
Mainstream industries including finance, art and creativity, education, law, healthcare, e-commerce, transportation, and IT have all been affected by generative AI, accelerating the application of automation.
For example, in the manufacturing industry, generative AI can be used to design new products, generate optimized design solutions through algorithms, and improve production efficiency;
In the media and entertainment industry, generative AI can create new music, artwork, and even write scripts to provide inspiration to creative workers.
Executives believe that the benefits of generative AI outweigh the risks
78% of executives believe that the benefits of generative AI outweigh its risks, compared to 68% in a previous Gartner survey.
"Executives are taking a bolder stance on generative AI because they see the profound ways in which it can drive innovation, optimization and disrupt their business," said Frances Karamouzis, distinguished vice president analyst at Gartner. "Leaders understand that a wait-and-see approach without taking any action will be riskier than investing in generative AI."
In terms of industry attributes, 45% of enterprises are expanding generative AI investments across multiple business functions, of which 22% are expanding across more than three different functions. Software development is the function with the highest adoption or investment rate of generative AI, followed by marketing and customer service.
Thirty percent of respondents cited growth initiatives as the primary business priority for generative AI investments, followed by cost optimization (26%) and customer experience/retention (24%).
Overall, 47% of generative AI application cases focus on customer service, and 30% are used for IT services.