The test isn’t whether AI can do something. It’s whether it can make the process measurably better

Gregg Aldana, Head of Global Solutions Consulting at Appian, argues that businesses must move beyond the assumption that AI should be applied to every process. Instead, companies should prioritize solving specific business problems and addressing inefficiencies. Aldana emphasizes that the true test for AI adoption is whether it makes a process measurably better, rather than simply adding complexity. He suggests a balanced approach: using traditional automation and rules for predictable, high-volume tasks, and reserving AI agents for scenarios requiring adaptive reasoning or unstructured data analysis. Furthermore, businesses must account for the hidden costs of AI implementation, including data integration, security, governance, and the operational infrastructure needed to manage exceptions. Ultimately, organizations should focus on the business problem first, ensuring that AI provides genuine value rather than replacing effective, established workflows for the sake of novelty.