Embracing the shift from traditional AI to autonomous, goal-driven AI systems
Agentic AI is reshaping enterprise intelligence. Unlike traditional AI, agentic AI systems perceive context, make autonomous decisions, and execute tasks independently transforming how businesses operate, scale, and innovate.
By 2028, over 33% of enterprise applications will embed agentic AI, enabling 15% of daily decisions to be made autonomously.[1] Yet, most businesses remain unprepared for this shift. This paper explores the strategic adoption of agentic AI, its integration challenges, and how to overcome legacy barriers.
This whitepaper highlights the evolution from reactive AI to proactive, goal-driven systems through LTIMindtree BlueVerse. It outlines the benefits of agentic AI across industries—from customer service and ITSM to marketing and healthcare—and presents a practical roadmap for implementation. It also examines key trends in agentic AI, including explainable AI (XAI), federated learning, responsible governance, and building trustworthy systems.
References: Intelligent Agents in AI Really Can Work Alone. Here’s How. https://www.gartner.com/en/articles/intelligent-agent-in-ai#:~:text=By%202028%2C%2033%25%20of%20enterprise,complete%20tasks%20and%20achieve%20goals
Key takeaways
-
Agentic AI is the next evolution beyond generative AI, enabling autonomous decision-making and action.
-
Core principles include autonomy, adaptability, context awareness, and multi-agent collaboration.
-
Adoption requires strategic planning and infrastructure readiness. How organizations can build an effective agentic AI adoption strategy.
-
Emerging trends include XAI, federated learning, responsible AI governance, and trustworthy AI systems.
-
Real-world use cases span customer service, ITSM, marketing, and healthcare.
Read the whitepaper to explore how agentic AI can future-proof your enterprise and unlock scalable, intelligent automation.
