Strategy: Why enterprises can’t afford to ignore agentic AI
Artificial intelligence (AI) technologies like generative AI (Gen AI) and predictive AI have already revolutionised business operations, but agentic AI takes innovation further by enabling enterprises to work smarter and more efficiently.
As we move through 2025, agentic AI is redefining how enterprises innovate, operate and compete. According to Gartner’s 2025 Strategic Technology Trends, agentic AI is poised to be one of the most significant developments in the enterprise tech landscape, offering a critical advantage for businesses looking to stay ahead in a competitive, fast-moving world.
What is Agentic AI and why does it matter?
Agentic AI is the next step in the evolution of AI. While traditional AI relies on pre-programmed tasks or predictions, agentic AI does not just forecast or generate content, it acts as….
Frequently asked questions (FAQ)
What is Agentic AI for enterprises?
Agentic AI refers to AI systems that can plan, coordinate and execute multiple steps towards a defined business objective. In enterprise settings, this can include gathering information, using different tools, making recommendations and triggering approved workflow actions.
How is Agentic AI different from Generative AI?
Generative AI mainly creates or interprets content, while Agentic AI can coordinate actions around that information. For example, Generative AI may draft a customer response, while an Agentic AI system can decide when to use it, update the CRM and trigger the next workflow step.
What enterprise processes can Agentic AI automate?
Agentic AI can support document processing, customer service, compliance checks, fraud investigation, workflow routing, scheduling, information gathering and other multi-step operational processes. The best use cases usually involve repetitive coordination across several systems or teams.
Does Agentic AI remove the need for human oversight?
No. Human oversight remains important for exceptions, high-impact decisions, regulated activities and situations requiring judgement or accountability. Organisations should define clear limits on what AI agents can access, decide and execute.
How can Agentic AI improve enterprise productivity?
Agentic AI can reduce the manual work involved in searching for information, moving data between systems, coordinating approvals and completing repetitive workflow steps. This can allow employees to spend more time on complex decisions, customer relationships and higher-value work.
What should enterprises consider before adopting Agentic AI?
Enterprises should consider data quality, system integration, permissions, security, auditability, human approval points and measurable business outcomes. Agentic AI creates more value when it is designed around a clear workflow problem rather than deployed simply because the technology is available.
