Agentic AI set to reshape enterprise and industrial automation
Aaron Blutstein 1 September 2025 
Agentic artificial intelligence (AI) is emerging as a key driver of business and industrial automation, with the potential to improve efficiency, cut costs, and enhance customer experiences, according to a new report from data and analytics company GlobalData.
Agentic AI systems are designed to act autonomously, making decisions and taking actions with limited or no human supervision. These AI agents interact with their environment, gather data, and perform tasks ranging from process automation to customer support, making them suitable for consumer, enterprise, scientific, and industrial applications.
GlobalData’s Strategic Intelligence report, Agentic AI, highlights that the ecosystem is expanding rapidly, with software companies, system integrators, start-ups, and major technology firms developing frameworks, platforms, and tools. For businesses without in-house expertise, a growing number of pre-packaged agents are available for applications such as earnings analysis, video script generation, and customer profile building.
Isabel Al-Dhahir, Principal Analyst, Strategic Intelligence at GlobalData, comments: “The agentic AI ecosystem is growing rapidly. 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.”
The report also notes growing interest in agentic DevOps, where autonomous AI agents are integrated into development and operations workflows. This could enhance processes such as continuous integration/continuous delivery (CI/CD) and infrastructure as code (IaC) pipelines, potentially increasing automation, decision-making, and operational resilience.
GlobalData advises that organisations proceed cautiously, particularly when determining the level of autonomy given to agents in critical systems. Challenges include “hallucinations” in foundational models and the complexity of migrating existing software stacks to AI-native architectures.
William Rojas, Research Director, Strategic Intelligence at GlobalData, adds: “Not all agentic AI projects will succeed. Many will fail as developers cultivate best practices for designing, building, testing, and validating agentic AI systems. 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.”
Rojas concludes: “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.”
