IDC predicts that global spending on artificial intelligence-related technologies will reach a staggering US$337 billion by 2025, doubling to US$749 billion in 2028. This prediction highlights the vigorous development of AI technology in various industries and the active promotion of enterprises in the implementation of AI strategies. The editor of Downcodes will explain to you how companies embrace generative artificial intelligence under this trend, as well as the challenges and opportunities they face.
According to the latest forecasts from research firm IDC, global spending on artificial intelligence (AI)-related technologies will reach $337 billion by 2025, and this number 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 companies are beginning to experiment with generative artificial intelligence (Gen AI) and have already applied it in production. Take Nate Melby, CIO of Dairyland Power Cooperative, for example, which has developed a large language model (LLM) that not only automates document summarization but also manages the power grid during storms. Meanwhile, global professional services firm Marsh McLennan has implemented about 40 generative AI applications in production, a number that chief information officer Paul Beswick expects to grow rapidly to satisfy C-level executives' demands for efficiency and innovation. needs.
JPMorgan Chase has also invested in generative AI in its investment business, travel services, customer center and other fields. Gil House, the company's chief information officer, said that generative AI is a transformative technology and will use an application scenario-based approach to realize value in the future.
IDC also pointed out that in 2025, 67% of AI spending is expected to come from enterprises embedding AI capabilities in core businesses. Businesses can quickly seize opportunities by using off-the-shelf solutions from SaaS providers like Salesforce and ServiceNow. At the same time, 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 approximately 34% of enterprises plan to leverage AI capabilities built into existing enterprise applications. Another 53% of companies plan to start with pre-trained models and expand them based on corporate data. Currently, most companies are still focusing on application scenarios that automate and improve productivity, although higher-value applications require larger-scale organizational changes.
Against this backdrop, CIOs are establishing internal AI committees and governance rules to reduce the risks posed by “shadow AI.” Melby, for example, stressed the need for companies to invest cautiously and tailor their investments to the company's risk tolerance. Governance and security issues have also become key areas of focus for major enterprises.
All in all, the application of generative AI is rapidly expanding, and enterprises need to actively embrace it and manage it carefully to gain competitive advantages in the AI wave and achieve efficient innovation. In the future, the expansion of AI application scenarios will be even more exciting.