Infosys Launches AI Agent To Streamline Energy Operations
Nov. 6, 2025 - Infosys introduced an AI Agent for energy operations built with Infosys Topaz, Infosys Cobalt, Microsoft Copilot Studio, Azure OpenAI (Foundry Models), and ChatGPT4o. It turns real-time data into clear recommendations, automates reporting, and helps teams act faster with fewer errors.
For operations leaders, the promise is straightforward: better safety, higher reliability, tighter control over well performance, and less non-productive time (NPT).
What the AI Agent actually does
- Processes well logs, images, plots, and tables to answer questions, summarize findings, and draft reports.
- Converts streaming and historical data into alerts, root-cause hints, and next-best actions.
- Surfaces early warnings for drilling and production challenges so teams can adjust before issues escalate.
- Delivers conversational access to field knowledge, engineering notes, and playbooks.
Why operations teams should care
- Shorter reporting cycles and fewer manual handoffs.
- Improved wellbore quality through quicker detection of anomalies.
- Lower NPT via predictive insights and faster coordination across rigs and assets.
- Clearer decision-making on safety and reliability, backed by auditable data trails.
Where it fits in your stack
The agent sits on top of your existing data sources and tools, pulling from historians, SCADA, drilling data platforms, EAM/CMMS, and document repositories. It can draft daily ops reports, assist during morning meetings, and support frontline teams with context-aware guidance.
- Data sources: well logs, MWD/LWD, pressure and flow sensors, maintenance logs, and incident records.
- Workflows: morning report prep, shift handover notes, work order prioritization, and deviation management.
- Tech foundation: Infosys Topaz and Cobalt combined with Microsoft Copilot Studio and the Azure OpenAI Service.
Fast rollout playbook
- Pick one high-friction workflow: daily drilling reports, production variance analysis, or incident triage.
- Map data access and permissions; define what the agent can read, write, and suggest.
- Set guardrails: versioned prompts, source citation, and human-in-the-loop approval for critical actions.
- Pilot with a single asset or rig for 4-6 weeks; collect operator feedback weekly.
- Measure results, refine prompts and connectors, then expand to more assets.
Metrics that prove it's working
- NPT reduction (%) and avoided downtime hours.
- Time to generate morning reports and post-job summaries.
- Mean time to detect anomalies (MTTD) and mean time to respond (MTTR).
- Incident rate and severity trends.
- First-response accuracy of recommendations and user adoption by role.
Safety, security, and governance
- Role-based access with least privilege and clear data residency rules.
- Audit logs for prompts, sources, and decisions taken based on recommendations.
- PII/PHI filtering where needed; protect contractor data and service-provider IP.
- Model lifecycle management: validation on real field scenarios, shift-left testing, and drift checks.
What the partners say
Microsoft notes that the collaboration pairs deep industry expertise with AI and cloud to deliver measurable results across safety, reliability, and operations.
Infosys states the solution addresses high-volume operational data and real-time decision needs by turning raw inputs into practical insights through conversational AI-moving teams toward intelligent automation and predictive analytics at scale.
About Infosys
Infosys is a global digital services and consulting company with over 320,000 employees serving clients in 59+ countries. The company focuses on cloud and AI-led transformation, agile delivery at scale, and continuous learning supported by an innovation ecosystem.
Forward-looking statements
This update includes forward-looking statements subject to risks and uncertainties, including strategy execution, talent, regulatory changes, technology shifts (such as AI), and cybersecurity. More details are available in the company's filings with the U.S. Securities and Exchange Commission.
Next steps for operations leaders
- Identify one reporting or monitoring workflow to automate and assign a cross-functional pilot team.
- Set success criteria (NPT, report cycle time, MTTD/MTTR) and track weekly.
- Upskill your team on practical AI use in operations with job-focused learning. See AI courses by job function.
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