Webinar: How AI Is Reworking QA and DevOps
AI-powered automation is changing how teams test software and ship releases. At 4pm GMT on Wednesday, 28 January, a live session will break down what works, what doesn't, and how to put AI to work across QA and DevOps-without slowing your teams down.
Experts from OpenText and Cognizant will share practical strategies to reduce defects earlier, optimise test cycles, and tighten delivery pipelines. Expect concrete examples of AI helping teams cut risk, improve reliability, and keep velocity steady.
Beyond the tools, the discussion will cover methods, process changes, and team habits that make AI stick in day-to-day engineering work.
Why attend
- See how AI can predict defects, prioritise tests, and flag flaky suites before they waste your time.
- Learn how to build intelligent pipelines that auto-tune environments, gate risky releases, and speed up rollbacks.
- Pick up measurement frameworks: what to track (DORA metrics, defect escape rate, test ROI) and how to prove value fast.
- Hear real adoption patterns: pilot use cases, data needs, model feedback loops, and where teams usually get stuck.
- Get guidance on governance, security, and change management so AI supports-rather than overrides-engineering judgment.
Meet the speakers
Shantanu Sengupta, Senior Director - Projects, Cognizant
Shantanu leads the Technology Office for Cognizant's Quality Engineering & Assurance practice. With 25+ years in AI, data, and cloud-led quality engineering, he's driven large-scale automation and digital transformation programs that improve delivery speed and resilience.
Yaniv Sayers, Fellow, ADM Chief Architect at OpenText
Yaniv has a deep background in software architecture and AI integration. He helps organisations modernise application delivery for scalability, efficiency, and quicker release cycles-combining strategy with hands-on execution to align people, process, and technology.
Moderator: Tom Chapman, Senior Editor of AI Magazine
Tom will guide a focused discussion that links emerging AI practices with real QA and DevOps workflows.
Event details
- When: Wednesday, 28 January at 4:00pm GMT
- Format: Live webinar with Q&A
- Focus: Actionable tactics for AI in testing, reliability, and delivery pipelines
Who should join
- QA and QE leaders, SDETs, and automation engineers
- DevOps, Platform, and SRE teams
- Engineering managers and product leaders accountable for delivery speed and quality
What you'll take back to your team
- A short list of AI use cases you can trial in the next sprint (test selection, flaky test quarantine, release risk scoring)
- A plan to measure impact: baseline metrics, target deltas, and review cadences
- Change guidelines: how to introduce AI without adding friction or noise
Quick prep (optional)
- Bring last quarter's delivery metrics (failure rates, MTTR, test duration, deploy frequency)
- Identify one friction point to pilot (e.g., regression time or incident triage)
- List your top 5 flaky tests or high-churn areas-perfect candidates for AI assistance
Want structured upskilling for QA and DevOps roles? Explore curated options by role here: Complete AI Training - Courses by Job.
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