Chris Leone, Executive Vice President, Applications Development at Oracle.
Enterprise software has always been good at keeping records. Orders, invoices, approvals, expenses, forecasts and service tickets are all captured in software, usually with a report waiting at the end. This has proven to be extremely valuable, but the harder part has always been everything that happens after the data shows up.
A supplier misses a shipment. Inventory drops below plan. A forecast changes. A customer issue sits too long in the queue. The system can show the problem, but the outcome still depends on someone noticing it, finding the right context, pulling in the right people and pushing the process forward.
That gap is where agentic applications are having an impact. This new class of application plays a more active role in execution. Instead of waiting for a user to interpret a dashboard or chase a workflow, agentic applications can monitor business conditions, understand process context, recommend next steps and help coordinate the work needed to complete an outcome.
From Activity To Progress
A conventional application waits for a user to search, review, approve, escalate or decide. An agentic application can keep watching the process while work is underway. It can see when a forecast changes, when an approval is stuck, when a supplier misses a commitment or when a customer issue is likely to affect renewal risk. Then it can recommend a path, start the right workflow and bring in the people and agents best positioned to solve the problem.
For example, a low inventory alert is useful, but often not enough. The system needs to know demand patterns, open orders, supplier reliability, fulfillment priorities, margin impact and any approval rules that govern the response to ensure successful automation.
With the right context, the application can help evaluate options. It may suggest moving inventory from another location, initiating a sourcing workflow, flagging a customer commitment at risk or escalating an approval because the delay has financial impact. A human can still make a decision, if human judgment is required, but in many workflows, agents within the agentic application can make decisions based on established policies.
Beyond The Co-Pilot Model
Co-pilots have been useful because they help people complete individual tasks. They can summarize meetings, draft notes, answer questions and make routine work less tedious.
Agentic applications go further because the unit of work changes. Instead of asking software to complete a task, employees can assign a broader business outcome: reduce supply chain delays, shorten the financial close, resolve service issues before they affect customer retention or improve collections without damaging customer relationships.
Those outcomes require judgment, trade-offs and coordination across functions.
Take an inventory shortage. A basic assistant might tell a manager that stock is running low. An agentic application can look at available inventory, supplier commitments, purchase orders, demand signals and fulfillment rules. It can identify likely fixes, start the sourcing process, coordinate approvals and address the issue before it becomes a larger disruption. This means the manager does not have to manually stitch together every step.
A Practical Path Forward
When it comes to implementing agentic applications, organizations first need the right foundation. Agents need trusted enterprise data and business context, clear process rules and governance that defines what agents can access, what decisions and actions they can take on their own, when human approval is required, and how their actions are monitored and audited. The closer agents are to the systems where business processes, data, security and approvals already live, the more context they have to reason where reasoning adds value, execute deterministically at enterprise scale and learn from every outcome.
With that foundation in place, a good place to start is where the most friction exists today. Look for high-volume, repetitive processes where people spend significant time gathering context, making decisions based on established policies, coordinating across systems or teams, and following up to keep work moving. Recruiting, collections, procurement, supply chain exceptions and service resolution are all good examples. These are areas where agentic applications can shift from doing tasks to achieving outcomes, taking on more of the execution and coordination that people have had to stitch together themselves.
Importantly, you do not need to hand over an entire process on day one. Start by having agents monitor conditions, reason over business context and recommend actions, then allow them to execute lower-risk steps within clearly defined policies and thresholds. As agents demonstrate that they can reliably deliver the intended outcomes, you can expand their scope of autonomy while keeping people close to higher-risk or consequential decisions.
The goal is not autonomy for its own sake. It is to move more of the execution and coordination to agents while people remain responsible for defining the desired outcomes, policies and boundaries, and for stepping in when judgment or accountability requires it.
Human Judgment Moves Upstream
A common mistake in enterprise AI discussions is assuming that more capable software means less need for people. In practice, the opposite is more likely. As systems take on more routine coordination, people have to be clearer about the outcomes they want, the risks they will accept and the boundaries the system must respect.
That changes the work. Employees can spend less time clicking through screens and spend more time setting priorities, handling exceptions, weighing trade-offs and deciding when the standard path is not good enough.
The system can monitor, recommend, coordinate and execute within approved limits, but people still define the limits.
Organizations will need systems that understand enterprise data, process rules, security, approvals and accountability. They will also need leaders who know where automation should act and where human judgment must stay close. This is particularly important in the current economy, with labor shortages, supply chain volatility and rising customer expectations forcing many organizations to rethink how work gets done.
Agentic applications can help organizations respond to these pressures by changing what they expect from business software, from systems that primarily record and surface information to systems that can help move work forward within defined goals, policies and boundaries.
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