At SSC we were excited to see the AI Agent Studio get introduced at Oracle's Cloud World this year.  It is a significant shift in how business processes will be automated. We got a chance to review the partner training that was recently released.

Oracle’s approach is rooted in embedding intelligent agents into everyday workflows, helping teams get real work done faster and with less friction. This article outlines a few core ideas behind Oracle’s AI Agent approach, and examines the real-world use cases Oracle’s presentations went through to demonstrate Agent Studio working in real time. 

Human Capital Management:

Onboarding assistance: When a new employee is hired, an agent can immediately begin the process by collecting required personal information, sending digital forms, and scheduling any training or orientation sessions. It also automatically triggers equipment provisioning requests with IT and workspace setup with Facilities. The agent tracks task completion and sends reminders to relevant stakeholders HR doesn’t have to manually chase updates.

Compensation advice: Oracle demonstrated one of their agents performing a slew of tasks related to its ability to access information about worker’s current and past compensation in a variety of forms including their base pay,additional compensation,stock options and so forth, and using this information to compare and evaluate their compensation relative to others in order to deliver insights about how comparatively an employee is being compensated relative to peers and if there need to be any changes made

Leave and absence management:  Oracle demonstrated how their agent, integrated with several REST APIs can manage available leave, absence requests, various entitlements, leave donations, and cash disbursements throughout an entire team, tracking employee balances currently, and future projected as well as taking actions when absences may come into conflict,or notifying employees when leave is above or below certain thresholds. 

Talent Advice: By being able to draw on a large pool of data pertaining to any specific employee, Oracle demonstrated how their agent can pull together numerical data on things like KPIs, written evaluations, and all other feedback received to give a manager an accurate, and date bounded picture of how an employee has performed and been assessed by their peers,customers, or managers during a given period, massively simplifying their time and effort needed for such evaluations.

Supply Chain Management:

Return Assistance: Oracle demonstrated how one of their agents can pull from user input,session data, existing stock, and existing policies to provide information on and potentially facilitate return orders, and user queries regarding the same 

Regulatory and Compliance Assistance: Oracle demonstrated its product regulatory compliance assistant and its capabilities to extract item data, match that with characteristics that will indicate regulated or controlled items or information, and then to give feedback on the company's current compliance posture relative to the queried item, or set of items, speeding up and simplifying the compliance checks process.Such agents can also proactively check for any changes in the regulatory environment and flag updates pertinent to products or services the company deals with so that there is minimal lag time where the company may be noncompliant. 

Maintenance,repairs, work orders assistant: Oracle demonstrated their AI agent’s ability to pull in data on a specific work order, but also an items work history, and any additional available information from existing manuals and documentation regarding the item in question to provide the employee doing said maintenance with a full picture of the best course of action in maintaining or repairing the item they have been tasked with. 

ERP

Payment Optimization: Oracle demonstrated the workings of a payment optimization team which can understand a users intent in creating a payment plan, evaluate different options in terms of payment programs, calculate a rough ROI, and synthesize an optimal route forward for achieving the users intent in setting up that specific payment program. The presenter dived a bit deeper in this demonstration into how to inform agents to be pulling new information such as updates to payment terms and conditions, relevant dates, payment methods, into its analysis and final ROI calculations.

Customer Service/Customer Experience

Quote Generation: Oracle demonstrated an AI agent team centred around generating a quote for a potential sales pitch, this included agents tasked with data collection, pricing recommendations, presentation materials generation and recommendations, and a quote options and strategy adviser to put forward best courses of action with moving forward with a quote or pitch