According to the latest forecast from research firm IDC, global spending on artificial intelligence (AI) technologies is projected to reach $337 billion by 2025, and is expected to double to $749 billion by 2028. As IT leaders across industries continue to drive the implementation of AI strategies, future applications will become more diverse and abundant.
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In this trend, an increasing number of enterprises are beginning to experiment with Generative AI (Gen AI) and have already implemented it in production. Taking the Chief Information Officer of Dairyland Power Cooperative, Nate Melby, as an example, the company has developed large language models (LLM) that can not only automate document summarization but also manage 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 the efficiency and innovation needs of C-level executives.
JPMorgan Chase has also invested in Generative AI across various domains including its investment business, travel services, and customer centers. The company's CIO, Gill Haus, stated that Generative AI is a transformative technology and that future value will be realized through an application-scenario-based approach.
IDC also noted that by 2025, it is expected that 67% of AI spending will come from enterprises embedding AI capabilities in their core businesses. Companies can quickly seize opportunities by using off-the-shelf solutions provided by SaaS vendors like Salesforce and ServiceNow. Meanwhile, major cloud service providers such as Amazon AWS, Microsoft Azure, and Google Cloud will also facilitate 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% plan to start with pre-trained models and expand them with enterprise data. Currently, most enterprises are focusing on applications that automate and enhance productivity, although higher-value applications require significant organizational changes.
In this context, CIOs are establishing internal AI councils and governance rules to mitigate the risks posed by "shadow AI." For instance, Melbi emphasizes that enterprises need to invest cautiously and adjust according to the company's risk tolerance. Governance and security issues have also become key areas of focus for major enterprises.
Key Points:
💰 By 2025, global AI spending will reach $337 billion, expected to double to $749 billion by 2028.
🛠️ Most enterprises will quickly start AI projects through AI capabilities built into existing applications or pre-trained models.
🔒 Enterprise CIOs are strengthening AI governance to ensure security and risk control, preventing the emergence of "shadow AI."