IDC predicts that global spending on artificial intelligence-related technology will reach US$337 billion by 2025, and is expected to double to US$749 billion in 2028. This has driven enterprises to actively explore and apply generative AI, many companies have incorporated generative AI into their core businesses, such as Dairyland Power Cooperative uses large language models to automate documents and manage power grids, while Marsh McLennan has implemented about 40 generative AI application. This article will explore in-depth the investment and application of enterprises in the field of generative AI, as well as the opportunities and challenges that will be brought about, including key issues such as AI governance and security.
According to the latest forecast by research firm IDC, global spending on artificial intelligence (AI)-related technologies will reach $337 billion by 2025, and this figure is expected to double to $749 billion by 2028. As IT leaders in various industries continue to promote the implementation of AI strategies, future application scenarios will be more diverse.
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Under this trend, more and more enterprises are starting to experiment with generative artificial intelligence (Gen AI) and are already being used in production. Take Knight Melby, chief information officer of Dairyland Power Cooperative, as an example, the company has developed a large language model (LLM) that not only automates document summary but also manages the power grid during storms. Meanwhile, global professional services firm Marsh McLennan has implemented about 40 generative AI applications in production, and CIO Paul Beswick expects this number to increase rapidly to meet C-level executives’ efficiency and innovation demand.
JPMorgan Chase has also invested in generative AI in its investment business, travel services, customer centers and other fields. Generative AI is a transformative technology that will use an application-based approach to realize value in the future.
IDC also noted that in 2025, 67% of AI spending is expected to come from companies embedding AI capabilities in their core businesses. Enterprises can quickly seize opportunities by using ready-made solutions from SaaS vendors like Salesforce and ServiceNow. Meanwhile, large cloud service providers such as Amazon AWS, Microsoft Azure and Google Cloud will also promote the experimentation and deployment of generative AI.
Research shows that about 34% of businesses plan to leverage the built-in AI capabilities in existing enterprise applications. Another 53% of enterprises plan to start with pre-trained models and expand with enterprise data. Currently, most companies are still focusing on application scenarios for automation and productivity improvement, although higher-value applications require large-scale organizational changes.
Against this backdrop, CIOs are establishing internal AI committees and governance rules to reduce the risks posed by “shadow AI”. For example, Melby emphasized that companies need to invest carefully and adjust according to the company's risk tolerance. Governance and security issues have also become the areas of focus for major enterprises.
Key points:
Global AI spending will reach $337 billion by 2025, and is expected to double to $749 billion by 2028.
Most businesses will quickly start AI projects with AI capabilities or pre-trained models built into existing applications.
Enterprise CIOs are strengthening AI governance to ensure security and risk control and prevent the emergence of "shadow AI".
In short, the rapid development of generative AI is profoundly changing the operating model of enterprises. Enterprises need to actively embrace AI technology and pay attention to AI governance and security in order to better use AI technology to create value and effectively deal with potential risks. In the future, AI application scenarios will be more diversified, bringing more opportunities to enterprises.