Global generative AI spending poised to reach $644 billion in 2025

According to a recent forecast by Gartner, worldwide spending on generative artificial intelligence (AI) is projected to reach US$644 billion in 2025, marking a 76.4 percent increase from 2024. This surge is largely attributed to the integration of AI capabilities into hardware devices such as servers, smartphones and PCs, with hardware investments expected to comprise 80 percent of generative AI spending.

Also, according to data from McKinsey, 63 percent of executives characterize the implementation of generative AI as a “high” or “very high” priority. Further, research from Microsoft and research/ analyst firm IDC found that generative AI usage jumped from 55 percent in 2023 to 75 percent in 2024 among surveyed organizations.

“Modern operational excellence (OPEX) relies on advanced technology, teamwork, sustainability and customer satisfaction,” says Abhishek Soni, an IT strategy advisor to a leading oil and gas company.

A decline in expectations

However, despite the substantial financial commitment, Gartner's analysis indicates a paradoxical trend: while foundational model providers are investing heavily to enhance generative AI models' performance and reliability, there is a noticeable decline in expectations because of high failure rates in initial proof-of-concept (POC) projects and dissatisfaction with current generative AI outcomes. John-David Lovelock, Distinguished VP Analyst at Gartner, notes that this paradox will persist through 2025 and 2026.

For businesses focusing on process excellence and digital transformation, this development presents both opportunities and challenges. The significant investment in AI-enabled hardware suggests an impending transformation in business operations and consumer products. However, the high failure rates in POC projects underscore the importance of strategic planning and risk assessment. As organizations integrate generative AI into their processes, they must ensure that these technologies align with their operational goals and deliver measurable value.​

Why do gen AI projects become abandoned?

Also, Gartner predicts that by the end of 2025, at least 30 percent of generative AI projects will be abandoned after the POC stage because of challenges such as poor data quality, inadequate risk controls and difficulties in demonstrating return on investment (ROI). This highlights the necessity for organizations to adopt a structured approach to generative AI implementation, emphasizing robust data strategies, comprehensive training and effective change management to overcome internal resistance and maximize ROI.​ For example, as outlined in a PEX Network report, implementing generative AI means more than simply adopting the technology. It requires careful reevaluation and reorchestration of wider business processes and operations.

“Rather than looking at how to adopt generative AI, you need to look at how you can transform entire process and value chains, with AI as an enabler,” says Priyank Mangal, senior director, sales and solutions, EMEA at EdgeVerve. This is how you drive true business value, and it cannot be done with AI alone.

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