On Demand: Closing the Confidence Gap: How AI-Assisted QA Keeps Pace with AI-Speed Development

AI is accelerating software development, but faster code creation does not automatically produce more reliable software. When traditional testing processes cannot keep pace, organizations can face growing gaps in coverage, quality, governance, and release confidence.
Join Experis technology and quality engineering leaders for a practical look at how AI-assisted QA can help organizations improve test coverage, accelerate release cycles, identify quality risks earlier, and increase release confidence, all while maintaining the human expertise and governance required for enterprise environments.
What You’ll Learn
In this session, you'll discover how leading organizations are:
Scaling quality engineering alongside AI-enabled software development
Expanding test coverage without increasing manual effort
Accelerating feedback loops between QA and engineering teams
Leveraging AI for test generation, automation, prioritization, and traceability
Improving release confidence while maintaining governance and oversight
Building a practical roadmap for AI-assisted QA adoption and transformation

See AI-Assisted QA in Action
The session will include a practical demonstration showing how AI-assisted QA can analyze a software change, identify potential risks, recommend or generate tests, run relevant regression testing, review coverage and traceability, and return actionable insights to engineering teams.

You will see how quality engineering can evolve from a downstream validation function into an engineering accelerator that supports faster, more confident software delivery.

Who Should Attend
This webinar is designed for technology, engineering, software delivery, and quality leaders seeking to improve software quality and development efficiency.

Ideal attendees include:

CIOs, CTOs, and Chief Digital or Product Officers
VPs and Directors of Engineering and Software Development
Quality Assurance and Quality Engineering leaders
DevOps, Platform Engineering, and Application Delivery Leaders
Enterprise and Solutions Architects
Digital Transformation Leaders
IT decision-makers evaluating AI-enabled testing, automation, or quality engineering