Large technology companies such as Amazon, Oracle, and Salesforce have long been rushing to adopt AI agent solutions, which are systems characterized by their ability to accomplish goals and take action independently without direct human intervention, and these companies have invested billions of dollars in this technology, driven by hopes of boosting profit margins and optimizing costs.
But with the great momentum surrounding this technology, the Gartner report warns that the market is witnessing a phenomenon known as (Agent washing) Agent Washing, which is that many companies are rebranding their existing products, such as virtual assistants and chatbots, as artificial intelligence agents) without having the actual capabilities that characterize this type of system.
Gartner estimates that only 130 of the thousands of companies with AI agent solutions are real companies offering real value, and this indicates that there is a lot of noise in the market that does not necessarily reflect real innovation or added value.
Reality versus hype.. Challenges of large-scale implementation:
The report revealed that most of the AI agent projects at the moment are nothing more than early experiments or proof-of-concept models. driven largely by media hype and market trends rather than actual needs, and are often applied incorrectly.
Anushree Verma, director of analysts at Gartner, explained that this makes it difficult for organizations to realize the real cost and complexity associated with the large-scale deployment of AI agents, which leads to the stoppage of such projects before they reach the production stage. Verma stressed the need to move beyond the hype to make strategic and careful decisions about where and how to apply this emerging technology.
Enterprise Investment in artificial intelligence agents and market trends:
The Gartner report notes that the technology of artificial intelligence agents is still at the stage of experimentation and formation, and faces real challenges related to technical maturity and commercial yield. With expectations of increased business dependence, many companies may be at a critical crossroads between further investment or reevaluation. Organizations seeking to adopt this technology should adopt thoughtful approaches, investigating the actual value rather than being driven by catchy headlines.
A survey conducted by Gartner in January 2025, which included more than 3,400 participants of a webinar, revealed insights on the levels of investment in AI agents, with 19% of respondents reporting that their organizations had invested cautiously in AI agents.
42% of respondents stated that their organizations ' investments in these systems were conservative, while 8% of respondents reported that their organizations did not make any investments in this area, and 31% of them confirmed that their organizations took a wait-and-see approach because they were unsure of their investment plans in this area.
These results indicate that a large segment of organizations is still in the early stages of exploring or adopting AI agent solutions, with a large percentage preferring caution or having not yet made a decision, reflecting uncertainty and hesitation in the market towards this technology.
Prospects for artificial intelligence agents.. Commercial value and future transformations:
In light of these initial challenges, the trend towards agents still represents a quantum leap in artificial intelligence capabilities and market opportunities, as this technology is expected to contribute to enhancing resource efficiency, automating complex tasks, and introducing new business innovations beyond the capabilities of programmed automation robots and virtual assistants.
Gartner forecasts significant shifts in the near future: by 2028, at least 15% of daily business decisions will be made independently through artificial intelligence agents, compared to 0% in 2024.
33% of enterprise software applications will include AI agent technologies by 2028, compared to less than 1% in 2024, and these forecasts indicate that the market still sees great potential in this technology, but success will largely depend on the ability of developers and companies to overcome current cost challenges, provide clear business value, and develop more mature models capable of handling complex tasks.
To get the most out of AI proxies, Gartner experts recommend adopting this technology only when it achieves a clear value or a tangible return on investment (ROI), taking into account the technical complexity of integrating proxies into legacy systems, which may disrupt the workflow and require expensive adjustments, as well as rethinking the workflow from the ground up using AI proxies as an ideal path for successful implementation.
Verma emphasizes that achieving real value from AI agents requires organizations to focus on the productivity of the whole enterprise, rather than just enhancing individual tasks, and suggests starting to use AI agents when independent decision-making is needed, automating routine workflows to free employees from repetitive tasks and enable them to concentrate on high-value work. The overarching goal, she explained, is to achieve commercial value by improving key factors such as cost, quality, speed, and scope.