Gartner projects that global spending on generative artificial intelligence (GenAI) will reach $644 billion in 2025, marking a 76.4% increase from 2024. This surge is primarily driven by substantial investments in hardware, which are expected to account for approximately 80% of the total GenAI expenditure. Specifically, spending on AI-enabled devices is projected to nearly double to $398.3 billion, while server investments are anticipated to reach $180.6 billion, reflecting a 33.1% growth.
Despite this significant financial commitment, many enterprises are encountering challenges in realizing the full potential of GenAI. High failure rates in initial proof-of-concept (PoC) projects have led to tempered expectations among Chief Information Officers (CIOs). Common obstacles include inadequate data quality and quantity, resistance to adopting new technologies, and insufficient returns on investment.
In response to these challenges, there is a notable shift among organizations from developing in-house GenAI solutions to adopting commercial off-the-shelf products. This transition aims to achieve more predictable implementation outcomes and tangible business value. John-David Lovelock, Distinguished VP Analyst at Gartner, highlighted that while foundational model providers are investing heavily to enhance GenAI models’ performance and reliability, CIOs are increasingly focusing on integrating GenAI features from existing software providers rather than pursuing self-developed initiatives.
The emphasis on hardware investments is further underscored by the integration of AI capabilities into consumer devices such as smartphones, PCs, and servers. Manufacturers are embedding AI as a standard feature, leading to projections that AI-enabled devices will dominate the consumer market by 2028. This trend is largely supply-driven, with consumers acquiring AI-enhanced devices as manufacturers standardize these features across their product lines.
As GenAI becomes increasingly integral to business operations and consumer products, organizations are advised to strategically align their investments with their operational readiness and long-term objectives. Prioritizing partnerships with established software providers and investing in robust data management practices can enhance the likelihood of successful GenAI adoption and maximize returns on investment.
