From Strategy to Pipeline: Architecting AI-First QA Workflows
AI has shifted from tool to foundation in QA, reshaping testing workflows and team structures. AI X QA Leadership Summit 2026 is built for teams ready to formalize an AI‑First QA operating model instead of “adding AI on the side.” It brings QA heads, engineering leaders, and senior quality engineers into one room to define AI‑driven workflows that deliver speed, coverage, and clearer quality signals across the delivery lifecycle.
This edition is a tightly curated mix of a keynote, leadership sessions, unscripted panels, live case studies, and high‑impact workshops, compressed into a compact, sub‑three‑hour format. Across dedicated streams for QA leaders and quality engineers, you’ll explore how to make AI‑First QA real: aligning strategy and metrics, reshaping roles and governance, and evolving everyday testing practices with clear, immediately usable frameworks.
Anchoring the summit is the BrowserStack AI Test Platform built for a world where AI is only as strong as the data, context, and systems behind it. Instead of another isolated AI tool, BrowserStack has created a privacy‑first, agentic platform that unifies trusted global infrastructure, 20+ connected AI agents, and a single data model for results and signals. You integrate once, and AI‑driven planning, authoring, execution, and failure analysis run on one coherent QA operating model reducing fragmentation and turning AI‑First testing into tangible outcomes.
SPEAKERS
Erika Chestnut
Founder & Executive Coach- Powerhouse Professionals
Sireesha Machiraju
Director – AI Assurance & QE, KPMG
Shashank Chaturvedi
QE Analytics & AI Solutions, S&P Global
Mark Nicholas Angeles
Quality Engineering Director – Sun Life
Ahmed El-Deeb
QA Manager – Amazon
Prajakt Deshpande
Head of Engineering, Atlassian
Dhimil Gosalia
Vice President, Browserstack
Snehal Thakkar
Sr. Director – Automate, Browserstack
David Burns
Head of Developer Relations, Browserstack
Sreenivas Karthikeyan
Principal Product Manager – A11Y, BrowserStack
Akhil Gundawar
Director of Product – Test Automation, BrowserStack
Rajesh Chilka
Product Manager – Low Code Automation, BrowserStack
AGENDA
AI, Speed, and Trust: AI, Speed, and Trust: Transforming QA from Execution to Orchestration
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Prajakt DeshpandeHead of EngineeringAtlassian
Crack Executive AI Strategy: Hard ROI, Outcome Metrics & Scale
- Shashank ChaturvediQE Analytics & AI SolutionsS&P Global Solutions
- Sireesha MachirajuDirector - AI Assurance & QEKPMG
Join enterprise leaders as they move past AI experimentation to focus on hard ROI, team alignment, and measurable business impact. This panel addresses how AI reshapes the delivery lifecycle – from leveraging production usage data to continuous post-release monitoring. Learn how to redefine developer-QA accountabilities, establish executive-ready outcome metrics, and scale your quality strategy through 2030.
Redefining QA Efficiency: An Amazon Deep Dive into Lean Workflows
- Ahmed El-DeebQA Manager - AmazonBrowserStack
Discover Amazon’s approach to optimizing QA operating models, shortening release cycles, and elevating executive metrics. Combining risk-based strategies with AI-assisted workflows targets critical quality risks while improving resource allocation. Aligning AI adoption directly with key business KPIs turns quality engineering into a primary driver of organizational velocity.
Leading AI Adoption in QA: Strategy, Frameworks, and ROI
- Mark Nicholas AngelesQuality Engineering DirectorSun Life
Unpack how enterprise QA leaders deploy AI in software testing to drive measurable operational efficiency. This session details high-impact testing use cases, specific metrics for measuring executive ROI, and strategies to maintain production quality at higher release speeds. Get a step-by-step framework for scaling AI from pilots to enterprise adoption, along with practical implementation do’s and don’ts.
WHY YOU SHOULD ATTEND?
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