Analysts working for GlobalData have highlighted what they believe to be the greatest limit on the success of agentic AI in the enterprise sector.
They go on to explain that the problem may lie with the human element rather than the capabilities of the technology itself.
The company identified there is a growing marketplace for agentic AI systems, explaining in a statement this is opening the door for operations spanning various sectors and enabling even smaller organisations to access the technology for digital transformation.
Principal analyst Isabel Al-Dhahir pointed to rapid growth in the agentic AI sector, but cautioned uptake by enterprises largely remains rooted in whether people are convinced the technology can “add demonstrable business value”.
GlobalData identified potential to employ agentic AI in consumer, enterprise, scientific and industrial situations, highlighting some of the most complex environments may rely on multiple agents to handle specific tasks.
It predicts the technology to “play a central role in the digital transformation of enterprise systems to AI-native stacks”, a shift benefitting software companies, systems integrators, start-ups and big-name technology players.
Al-Dhahir said there is “ongoing scepticism” over the business value, but argued the “greater autonomy and methodical approach to reasoning, problem-solving and decision making” would enable agentic AI to deliver more than “previous iterations of generative” tools.
“The next step is crafting these agents for practical high-value use cases”.
DevOps
GlobalData outlined hopes agentic AI could boost software development and IT operations (DevOps), building on prior automation advances to augment continuous integration and delivery processes “and infrastructure as code pipelines”.
Research director William Rojas cautioned not every agentic AI project would succeed: “Many will fail as developers cultivate best practices for designing, building, testing and validating” the systems.
He sees the task of integrating agentic AI into existing processes as a “critical challenge”, predicting it will take time for organisations to fully embrace the technology.
GlobalData recommends a cautious approach about how much autonomy is given to agentic AI in the early days, noting in DevOps there are obstacles including foundation model hallucinations and the ease with which current software stacks can be shifted to native set-ups based on the technology.
Source: Mobile World Live
Image Credit: Stock Image