'The test isn’t whether AI can do something. It’s whether it can make the process measurably better': We hear why businesses need to be more selective about where they’re using AI (www.techradar.com)

As AI integrates deeper into business processes, organizations face the crucial question of whether to adopt AI broadly or apply it selectively to genuinely enhance efficiency. Gregg Aldana, Senior Vice President at Appian, emphasizes that the starting point shouldn’t be “Where can we use AI?” but rather, “What problem are we trying to solve?” This approach ensures businesses focus on addressing significant bottlenecks and inefficiencies before deciding if AI is the right solution, highlighting the importance of human oversight where high-stakes decisions are involved. Aldana warns against the misconception that AI is necessary in every process. For tasks with predictable outcomes, traditional rules or automation might be more efficient, whereas AI shines in scenarios requiring complex reasoning or adaptive context. Businesses must evaluate the operational infrastructure and potential hidden costs associated with AI adoption, such as data governance and exception handling. By prioritizing effective outcomes over sheer AI deployment, companies can build balanced processes that combine human expertise, conventional automation, and AI to achieve measurable improvements rather than adding unnecessary complexity and costs.