Gartner expects Gen AI spending on reaching $ 644 billion in 2025: What it means to the leaders of the institution’s information technology

Do not mistake it, there are a lot of money spent on artificial intelligence in 2025.

Analysts Gartner has released a new report today that is expected to reach the Global Gen Ai spending at $ 644 billion in 2025. This number represents an increase of 76.4 % on an annual basis on Gen AI spending in 2024.

The Gartner report joins a set of other industry analyzes in recent months, all of which indicate an increase in adoption and spending on Gen AI. Spending It grows 130 %According to the research conducted Amnesty International in WartonResearch Center at Warton College at the University of Pennsylvania. Deloitte mentioned 74 % of institutions have already faced or exceeded GEN AI initiatives.

Although it is not surprising that spending on GEN AI grows, the Gartner report provides a new clarity about where the money is going and where institutions may get maximum value.

According to the Gartner analysis, the devices will demand an amazing 80 % of all Gen AI spending in 2025. The prediction appears:

• Devices will represent $ 398.3 billion (99.5 % growth)
• The servers will reach $ 180.6 billion (growth of 33.1 %)
• Software spending is only $ 37.2 billion (93.9 % growth)
• Total services will reach $ 27.8 billion (growth of 162.6 %)

“The hardware market was the biggest surprise, which is the most driving market on the supply side instead of demand,” John Lukluk, an evaluation vice president analyst at Gartner, told Venturebeat. “Consumers and institutions do not search for artificial intelligence devices, but manufacturers produce and sell them. By 2027, it will be almost impossible to purchase a computer that AI has not been enabled.”

The dominance of the devices will be condensed, and do not decrease for the AI ​​Corporation

With devices demanding about 80 % of the Gen AI spending in 2025, many may assume that this percentage will gradually turn towards software and services with the maturity of the market. Love visions indicate the opposite.

“The proportions turn more in favor of the devices over time,” said Luvlock. “Although more and more programs will contain the features of Gen AI, there will be less money on Gen AI – the AI ​​Gen Ai function will be connected as part of the program price.”

This projection has deep effects on the budget of technology and infrastructure planning. Institutions that expect to transfer spending from devices to the programs over time may need to be calibrated by their financial models to calculate the requirements of continuous devices.

Moreover, the integrated nature of the functions of artificial intelligence in the future means that separate artificial intelligence projects may become less common. Instead, the possibilities of artificial intelligence will increase as features within the current software platforms, making deliberate adoption strategies and government frameworks more important.

POC Cemetery: Why do the internal projects of AI fail

The Gartner report highlights a realistic fact: Many Proof-Pe-TE-TROCESS (POC) projects failed at Gen Gen Ai (POC) to achieve expected results. This has created what Loverock “is a paradox” where expectations decrease despite the massive investment.

When he was asked to clarify these challenges, Loverock select three specific barriers that constantly hinder Gen AI initiatives.

“Latest experienced companies with artificial intelligence have achieved higher success rates with GEN AI, while less experienced companies have suffered higher failure rates.” “However, most institutions failed in one or more of the first three reasons: their data was of insufficient size or quality, its members were not able to use new technology or change to use the new process or the new Gen AI will not have enough investment return.”

These ideas reveal that the basic challenges of Gen AI are not technical restrictions, but the factors of organizational readiness:

1. Insufficient dataMany organizations lack high -quality data for training or implementing the GEN AI systems effectively.
2. Change resistanceWe are struggling with users to adopt new tools or adapt the workflow to integrate the potential of artificial intelligence.
3. Lack of return on investmentProjects failing to provide measurable business value that justifies the costs of implementation.

Strategic axis: from internal development to commercial solutions

Gartner notes expected transformation forecasts of ambitious internal projects in 2025 and beyond. Instead, expecting is that companies will choose external commercial solutions that provide more implementation and commercial value.

This transition reflects the increasing recognition that building the solutions of Amnesty International often represents more challenges than expected. Loveock comments about failure rates confirm why many pivotal institutions for commercial options that provide predictable implementation paths and a more clear investment return.

For technical leaders, this indicates the priority of sellers ’solutions that included the capabilities of artificial intelligence in the current systems rather than building dedicated applications from the zero point. As noticed, these capabilities will be increasingly provided as part of the standard program functions instead of separate Gen Ai products.

What does this mean for the Foundation’s AI’s strategy

For institutions looking to drive in adopting artificial intelligence, Gartner’s prediction challenges many common assumptions about Gen Ai Marketplace. The focus indicates devices spending, supply aspect operating programs and compact functions that a more evolutionary approach may result in better results than revolutionary initiatives.

Technical decision makers should focus on combining Gen AI’s commercial potential in the current workflow instead of building custom solutions. This approach is in line with Loverock noting that CiOS reduces self -development efforts in favor of features of current software providers.

For organizations that plan to accredit more conservative, the inevitability of devices that support artificial intelligence provides challenges and opportunities. While these capabilities may reach through regular update sessions regardless of strategic intention, organizations that are preparing to benefit from effectively will gain competitive advantages.

With the acceleration of the Gen AI spending about $ 644 billion in 2025, success will not be determined by spending alone. Organizations that correspond to their investments with organizational readiness, focus on overcoming the three main failure factors and developing strategies to benefit from the increasingly compact Geen AI capabilities on extracting the greatest value from this advanced technological scene quickly.