Understanding When a Business Process is Ready for Agentic AI

Agentic AI is slowly becoming a staple in the business world, but deciding where to apply it can be tricky. The key is to pinpoint which processes will truly benefit from this technology. With many companies exploring how agentic AI can add value, it's crucial to ask: which business workflows are the best candidates?

The Rise of Agentic AI in Business

According to Deloitte, by 2025, a quarter of businesses using generative AI will experiment with agentic AI, expanding to half by 2027. Some industries might even start integrating agentic AI into their workflows this year. However, not every business process is a good fit for agentic AI, and for some, traditional deterministic automation might still hold sway.

Aligning AI with Business Goals

How can a business tell if a process is ready for agentic AI? Like any tech investment, it's important to consider whether AI will genuinely enhance the process. Prashant Kelker from ISG emphasizes the importance of aligning AI's goals with the broader business objectives. Without a clear mission, agentic AI can feel directionless.

Reiko Feaver from CM Law suggests that deciding to switch to agentic AI should follow the same decision-making process as any new tech adoption. If a cost-benefit analysis shows a positive ROI, then it's worth investing resources. However, the complexity and the required resources for agentic AI can pose challenges. Companies need to assess if they have the infrastructure and compliance measures to support and monitor AI effectively.

The Importance of Quality Data

For agentic AI to be effective, high-quality data is crucial. Saket Srivastava from Asana points out that outdated or irrelevant data won't yield valuable results. AI agents need a clear framework of tasks, objectives, and timelines to function effectively. Asana has leveraged agentic AI to streamline work management, using AI to handle repetitive tasks and free up time for more strategic work.

Customer Service: A Prime Candidate for Agentic AI

Customer service is one area where agentic AI can shine. Traditional systems like IVRs and chatbots often fall short, as they are rule-based and struggle with unexpected queries. Sheldon Monteiro from Publicis Sapient explains that agentic AI can provide a more adaptive and personalized customer experience by understanding context and learning over time.

Ideal Scenarios for Agentic AI

Experts identify several scenarios where agentic AI can be most beneficial:

1. Hybrid Processes: AI can enhance processes that involve both automated and manual tasks, like insurance claims that require both data validation and human judgment.

2. Cross-Department Workflows: When processes span multiple teams, AI can unify data and streamline coordination, as seen in order-to-cash processes.

3. Repetitive Tasks: Routine actions like data entry and report generation are perfect for AI, freeing employees for more strategic work.

4. Costly Manual Tasks: In growing businesses, AI can handle routine customer interactions, reducing costs and improving efficiency.

Agentic AI is not just about automating tasks; it's about solving problems and enhancing business processes. By carefully selecting where to apply this technology, businesses can unlock new efficiencies and improve customer experiences.