Agentic AI and business efficiency

- Most situations and transactions in business are repeatable. How customer buys products, how customer service responds to incoming requests, and how finance closes the books, they all follow well-defined steps in a business process that ensure the same outcomes, time and again. Most situations are also a little more complex than you initially envision them to be like, for example, customers requesting custom discounts and different payment terms, vendor deliveries being delayed due to natural disasters or strikes, facilitating product recalls and exchanges on a global scale and many other unforeseen circumstances. There are always exceptions, but it's just not feasible to conceive of every possible situation or exception, let alone trying to describe these situations in software code. So that's where analyzing, evaluating, reasoning and decision-making are important, which differs from traditional software. AI agents are the latest technology to help businesses do that. End users are used to telling software what to do. If this happens, then do that, but that's not how you would onboard a new team member. Agents change their paradigm. Instead of defining instructions on how to accomplish a task, the user gives it a goal and the agent identifies the steps to reach it. This is also helpful for tasks that spend multiple systems in where each has its own complexity. For example, in the future, the procurement team could use AI agents to discover delivery delays and automatically source materials from alternative suppliers. That way your production stays on schedule without the procurement team having to intervene manually. The agent monitors delivery dates for open purchase orders, and if it notices a delay, it gathers the availability of other suppliers and creates a proposal. It sends the new sourcing proposal to a procurement professional who reviews it, and if no adjustments are needed, the agent can make the purchase right away. Otherwise, the purchaser can ask the agent to refine the proposal or make edits themselves. This just one example of how AI agents will help business teams. What are common tasks in your role that AI agents might be able to help you with? Take a moment to pause and think about three tasks that are repetitive, but often have exceptions, require you to consider multiple data sources and systems and involve some level of uncertainty before you can make a decision. (upbeat music) When tasks become more complex, analysis, reasoning, and decision making take precedence over inflexible roles. AI agents can address the uncertainty in these situations and increase overall efficiency.