According to the latest Strategic Intelligence report from data analytics and consulting company GlobalData, agentic AI promises efficiency improvements for automation processes including enterprise workflows, reducing costs, and improving customer experience.
Agentic AI is defined as advanced artificial intelligence systems that act autonomously, making decisions and taking actions with limited or no human supervision. An AI agent is a software program that interacts with its environment and collects data, which it uses to perform specific tasks, answer questions, and automate processes for users.
Able to mimic human decision making to communicate and collaborate, AI agents are being developed for a range of consumer, enterprise, scientific, and industrial purposes. Complex environments, such as industrial plants, might be served by multiple AI agents, each tasked with a specific subtask to reach their overall goal.
GlobalData says in its report ‘Agentic AI’, that Agentic AI is expected to play a central role in the digital transformation of enterprise systems to AI-native stacks. It adds that, for enterprises that do not have the resources to create their own AI agents, the industry has already developed pre-packaged AI agents for a range of applications such as earnings analysers, video script generators, and customer profile builders.
“The agentic AI ecosystem is growing rapidly,” said Isabel Al-Dhahir, Principal Analyst, Strategic Intelligence at GlobalData, referencing the burgeoning number of companies already providing industry-specific agentic AI solutions. “However, enterprise adoption will require confidence that these tools can add demonstrable business value, a detail that remains subject to ongoing scepticism.
“The greater autonomy and methodical approach to reasoning, problem-solving, and decision-making should see agentic AI capable of far more than previous iterations of generative AI tools. The next step is crafting these agents for practical high-value use cases.”
Industry also expects agentic DevOps to improve on the past successes of robotic process automation to enhance continuous integration/continuous delivery processes and infrastructure as code pipelines. Agentic DevOps refers to the integration of autonomous AI agents into DevOps practices, such as code assistance, to realise systems that enhance automation, decision-making, and operational resilience.
GlobalData recommends that organisations proceed cautiously regarding how much initial autonomy is given to AI agents in DevOps. It warns that obstacles to agentic DevOps progress include hallucinations in the foundational models and how readily the existing software stack can be migrated or transformed into an AI-native design.
“Not all agentic AI projects will succeed. Many will fail as developers cultivate best practices for designing, building, testing, and validating agentic AI systems,” Added William Rojas, Research Director, Strategic Intelligence at GlobalData: “Over time, enterprises will seek to transform their software stack into an AI-native architecture. AI agents will play a critical role in facilitating this journey.”
“Integrating agentic AI into existing processes is going to be the critical challenge; clearly, it will take time for organisations to fully embrace agentic AI. Nevertheless, agentic AI will play a front-and-centre role in transforming AI-native architecture.”
