2 min read

AI Automation Market Map

In a previous post, we mentioned that the next wave in enterprise automation will be all about AI agents. AI agents are vastly superior to their predecessors (i.e. RPA bots) with their human-like capabilities, including to plan, do, check, and act. This enables them to handle both unstructured processes and unstructured data, a major limitation with the current RPA bots.

For businesses who are just getting started with AI agents, here are four steps to consider in your journey from automation to AI:

Get management buy-in: It is important for the C-Suite to understand the potential of AI agents, and the idea that every business in future will be a AI-powered business. As with any strategic initiatives, management support in the form of budget and resources is absolutely critical to success.
Identify initial use cases: The recommended approach is to start small, then scale fast. For the initial use cases, it may be helpful to review your existing automation pipelines, particularly those processes or workflows which cannot be automated in a straight-through manner with RPA. The key objective of these Proof-of-Concepts is to acquaint the entire organization with AI agents, and expose them to this future of work where humans collaborate with agents to get work done.
Understand the risk: Before deploying AI agents widely across the organization, it pays to be cognizant of the risks associated with the use of AI. Such risks include data confidentiality, privacy and security, accuracy and authentication issues, copyright infringement, ethical concerns and explainability. It is therefore important to establish proper AI governance and security guidelines before you starting to scale any deployments.
Be flexible and stay nimble: Finally, a word of caution. Given the rapid pace of developments and advancements in the AI industry, it would be wise to explore different technologies and solution providers. Also, avoid being locked in to a particular technology or vendor, and to consider open source where feasible.