Gartner releases Chinese Enterprise Artificial Intelligence Trend Wave 3.0

June 13, 2023 – At the recently held 2023 Greater China Executive Exchange Conference, Gartner released the latest survey results showing that Chinese companies are shifting artificial intelligence projects from prototypes to In production, most companies no longer worry about why they need AI capabilities, but pay more attention to the construction of AI engineering capabilities, with the goal of data-driven decision-making, and continue to create value for the business. Leading Chinese AI companies have adopted generative AI and other new AI technologies to establish original AI companies in different scenarios.

Although CIOs generally believe that AI has great value to the business, board members are skeptical of AI and its actual effects have failed to meet expectations. However, the launch of ChatGPT allowed board members and business executives to be exposed to the huge potential of generative AI for the first time, and began to believe that generative AI can bring changes and huge value to the business. CIOs are feeling anxious and stressed because they worry about missing out on opportunities to invest in AI generation.

Gartner released China Enterprise Artificial Intelligence Trend Wave 3.0, which aims to help enterprise chief information officers (CIOs) better plan AI capabilities and improve business results.

成和 innovation

Currently, Chinese companies have deployed an average of more than 5 AI use cases, and each company has begun to deploy an average of 24 AI use cases. Although many business users or business executives think that AI is as simple as installing a plug-in, in fact, operating AI involves data processing, business indicator sorting, data integration, business integration, continuous monitoring and optimization, etc., and requires overall consideration. End-to-end AI use cases and processes. Only one of the five Chinese companies' AI can fully meet business needs. This is why more and more leading companies no longer regard AI as an investment in a single project, but in the form of product operations and combined operations. Operate AI as a whole from an end-to-end, business results-oriented perspective, so that it can continue to produce business effects throughout the entire life cycle.

Fang Qi, senior research director at Gartner, said: "Most companies will maintain their existing business results and use generative AI to carry out local innovations such as algorithm improvements if they have the ability. Innovate the company's overall capabilities Processes, algorithms and systems may bring more valuable applications, but they also carry greater risks. According to the latest Chinese enterprise survey, 75% of enterprises believe that the future capabilities of generative artificial intelligence may exceed the capabilities it brings Risks. Although companies currently have a low perception of risks, once a risk occurs, it may cause huge loss of goodwill and customer loss to the company."

balance risk and value

Businesses usually Risk avoidance measures will be taken to apply generative AI technology, and the technology will only be used where it will not cause serious consequences or potential controversy. This cautious attitude is reasonable, but it may also result in missing some potential business opportunities. Therefore, enterprises need to find a balance between realizing business value and managing risks.

Fang Qi, senior research director at Gartner, said: “In order to balance value and risk, we should continue to consolidate existing investments, continue to respond to known risks, and devote our energy to opportunities or continued investments with high business value and low risks. Medium. For high-risk and low-value use cases, we should decisively remove them. At the same time, we can also pursue high business value and high-risk use cases from an innovative perspective, protect user data privacy through privacy computing and other methods, and through data Statistical values ​​help businesses continue to realize their value and build differentiated capabilities."

In order to ensure the credibility and explainability of AI applications, companies should adopt transparency and explainability methods to ensure the accuracy of the AI ​​decision-making process. Transparency, and the ability to provide explanations and justifications for AI decisions. When applying generative AI, companies need to carefully evaluate the ethical, legal and social issues that may be involved and ensure compliance with relevant regulations and ethical standards. By establishing a clear regulatory and governance framework, companies can realize the commercial potential of AI while balancing innovation and risk.

fusion team

Once we have clarified the risks and values, we need to consider how to select talents and adjust the organizational structure to help us implement the AI ​​strategy. When Chinese companies implement AI, more than half of them believe that talent is the biggest challenge. Relatively speaking, less than 30% of foreign companies believe that AI talents are the biggest challenge. This may be because different organizations have different requirements for talent and organizational relationships. The leading edge of institutions lies in their ability to integrate different business knowledge, IT skills and data science skills to apply AI in a more comprehensive and complete way, thereby achieving more effective implementation.

Fang Qi, senior research director at Gartner, said: "When it comes to implementing AI, selecting the right talents is the first priority, but the important role of organizational structure and corporate culture in talent adaptation cannot be ignored. By adhering to principles and taking risks Three concepts of management and talent selection, and more strategic planning, implementation and application of corresponding artificial intelligence capabilities."

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