Google Cloud released a report on the application of generative AI in the media and entertainment field. This time, an in-depth investigation was conducted on 263 companies with annual revenue exceeding US$10 million.

The results show that 64% of respondents in the media and entertainment industry stated that they have applied generative AI in actual business; 24% are evaluating or testing generative AI use cases. This shows that the media and entertainment industry has reached an inflection point in the application of generative AI and has become one of the important daily tools.

Many early adopters of generative AI have achieved significant results: 63% of respondents said that generative AI has helped companies improve the acquisition of potential customers and new customers; 65% of respondents successfully created a new product or service.

In terms of business benefits, 72% of companies that have used generative AI said they have achieved ROI on at least one actual business use case. These business use cases include: personalized content recommendations through AI algorithms , can increase audience participation, reduce user churn, thereby increasing subscriber retention rate;

Applying AI in the production process It can automate tasks such as script analysis, character development and visual effects production, significantly reducing production costs and shortening production cycles, allowing studios to respond to market trends faster;

AI-driven advertising platforms can also help Accurately target specific audience groups, deliver personalized ads, improve advertising effectiveness, and maximize return on investment.

In terms of content creation, generative AI can assist artists and creators by providing creative inspiration, automating the editing process, and even creating music and scripts completely independently. The application of this technology not only improves creative efficiency, but also broadens the possibilities of artistic expression. For example, by analyzing large amounts of historical data and popular trends, generative AI can predict which types of programs or music are more likely to attract audiences, thereby helping creators make more targeted creative decisions.

In terms of planned investment, 62% of media and entertainment companies plan to spend at least half of their future AI budget on generative AI. This decision reflects the industry’s confidence in the long-term value of generative AI technology. They believe that by continuing to invest in generative AI, they can stay ahead of the competition and continue to explore new avenues for innovation.

When considering how to reap the benefits of investing in generative AI, companies typically focus on a few key areas: 43% of respondents plan to use these benefits to find new revenue streams, including developing new products and services, or explore new monetization models such as data-based personalized advertising or subscription services.

41% of companies plan to use proceeds to improve profit margins, mainly by automating and optimizing business processes to reduce costs, or by improving efficiency to increase output. Through these measures, companies can maintain stable revenue whileAchieve higher profits.

In terms of effectively implementing generative AI use cases, companies need to adopt some key strategies to execute: First, they need to ensure that they have a clear innovation vision and strategy. This should include a deep understanding of market trends, as well as an accurate assessment of the organization's own strengths and capabilities.

Secondly, organizations need to establish an organizational culture that supports innovation. This includes encouraging employees to come up with new ideas and providing them with the necessary resources and support to implement those ideas. In this way, organizations can stimulate the innovation potential within them and ensure that innovation activities are aligned with the organization's overall strategy.

In addition, organizations also need to establish effective innovation management processes. This includes rigorous evaluation and monitoring of innovation projects and making adjustments when necessary. In this way, organizations can ensure that their innovation investments generate the greatest return.