What change-freeze windows should we avoid when enabling new Copilot features this month?

Technical rollback plan

• Phase 1: Pre-deployment preparation
• Phase 2: Execution (upon regression)
• Phase 3: Post-rollback

Communications plan

• Phase 1: Pre-deployment
• Phase 2: Execution (upon regression)

To centralize AI usage logs from multiple suites for audits and cost control, you need a robust logging and observability platform that can ingest, normalize, and analyze data from various sources. This approach involves four key steps: establishing data pipelines, choosing a centralized logging solution, normalizing the data, and using the consolidated data for analysis and reporting. 

• Step 1: Establish data ingestion pipelines

Your chosen platform needs mechanisms to pull logs from every suite your organization uses, whether it's an internal application or a third-party service.

• Step 2: Choose a centralized logging solution

Select a platform that can aggregate and store AI logs at scale.

• Step 3: Normalize and structure the data

Logs from different sources often have different formats, which makes centralized analysis challenging.

• Step 4: Analyze and report on the centralized data

With your logs centralized and normalized, you can use built-in features for audits and cost control.

To prevent an AI summarization model from capturing confidential content like breakout-room or off-the-record discussions, quality assurance (QA) checks must validate both the technical implementation and the user experience. The checks must ensure that data capture is disabled or isolated during sensitive periods and that the AI model itself is not trained on or exposed to restricted data.

Here are some open-source AIOps tools that can help with IT operations automation, anomaly detection, and incident management: Prometheus, Grafana, Elastic Stack (ELK), Apache Kafka, OpenTelemetry, Seldon Core, Loglizer, AIOpsTools and Keep.

The tools used in AIOPS are Splunk IT Service Intelligence (ITSI), Dynatrace, IBM Watson AIOps, Moogsoft, BigPanda, AppDynamics and New Relic AI.