Intelligent Automation (Cross-Industry) Agentic AI Use Cases
Challenge
Organizations find their enterprises plagued by a set of broken systems, redundancy and lagging speed due to human error. Most organizations do not experience true end to end automation, even after making investments in RPA and automation solutions, lack of commensurate, contextual decision-making and inter-system coordination remains an issue.
Deloitte findings show that 53% of automation initiatives are not allowed to scale past a single activity or bot. Cross-functional processes tend to involve manual processes in critical variable points, slowing down the pace, accuracy and efficiency.
How Agentic AI Helps
Context-aware automation has been realized by AI agents across systems, and enterprises. These smart agents are more than just conventional bots- they can do all these, such as authentication to a portal, scouring and evaluating data, editing CRM systems, and initiating responses based on results without involving humans. Optionally, using structured and unstructured data in real time, the Agentic systems can provide decision support in authorizations, selecting vendors or pricing decisions, and a lot of manual back and forth is eliminated.
In customer-related functions and back-office contexts, agents are able to independently summarise, reply to, and take action on communication in bulk. Such as in the case of email agents going as far as to route, respond, or action downstream dependencies based on contextual understanding. These autonomous processes orchestrate the flow of work across APIs, bots and human actors – dynamically adjusting that flow based on feedback in real-time.
When it comes to time reduction, Forrester estimates organizations implementing intelligent automation agents into the workflow reached as much as 40% savings in process time and 25% in errors, making them truly autonomous.