AI adoption in software engineering is accelerating, but the real story lies in how top-performing teams are turning it into measurable impact. While many organisations remain stuck in experimentation, leading teams are successfully translating AI-driven productivity gains into improved delivery performance. The difference isn’t the tools, it’s how they’re applied within the system.
Most QA teams are stuck measuring how many tests they ran. But in a tightened economy, leadership wants to know one thing: What is the ROI?
On May 7th, join SD Times for Supercast 2: The ROI of Intelligent Quality. We’re shifting the conversation from simple test automation to real business outcomes.
Engineering leaders are under more pressure than ever. AI coding tools are being rolled out across teams at breakneck speed. Executives want to see measurable impact. DORA metrics and throughput numbers tell part of the story, but they can’t tell you why deployment frequency dipped last quarter, or whether your developers actually trust the AI-generated code they’re shipping.
Join us to learn the keys to your next breakthrough.
Building Context Aware Systems Developers Can Rely On
AI is rapidly becoming embedded in the software development lifecycle. Yet many organizations are discovering a hard truth: intelligence without context is unreliable. Models generate plausible output, but they lack awareness of system architecture, internal policies, API contracts, ownership structures, and downstream impact. In enterprise environments, that gap is where risk lives.
Trusted AI is not simply about model quality. It is about grounding AI in the real, structured context of your organization.
The next phase of enterprise AI is not bigger models. It is smarter systems that understand the environment they operate in. Join us to explore how context-driven AI enables software teams to move faster with confidence.
Join the premier event series to uncover the latest in AI in Test trends related to MCP, Agents, and AI driven automation. Speakers will present solutions you to learn how to deliver value for your organizations.
Your engineering team is using AI coding tools, but when the CEO, CFO, or board asks, “What’s the actual ROI?”, you’re stuck between “It feels faster” and “I can’t actually prove it.” License counts are useless, and velocity metrics can’t isolate the AI variable. Join GitKraken’s VP of Engineering, Stasia Zamyshlyaeva, as she shares her real-world struggle and the data-driven framework built to overcome it. Learn the exact metrics that silence the skeptics and demonstrate undeniable financial impact.
When tests scale to thousands, who’s in charge?
In this session, we’ll explore six breakthrough areas where artificial intelligence now leads in QA—where AI doesn’t just assist, it performs. These advances represent not incremental improvement but a paradigm shift. QA has entered the generative era, where AI models can reason about user flows, infer data relationships, and produce complete test suites autonomously. Come see the six tasks where AI is already leading the charge, and learn how to make them part of your team’s QA strategy now.
Not sure how QA survives the AI wave? This session gives you a practical playbook. AI platforms that generate, execute, and heal tests are already running thousands of tests in hours – and that means the old tester-as-scripter playbook is obsolete. This webinar shows QA leaders and senior testers how to move from being automated-out to running the automation.
Through real-world examples from enterprises already using AI-first QA (including autonomous test generation and digital-twin workflows), we’ll map the new QA operating model and the roles that matter: QA architects, strategy owners, and governance leads. You’ll see how teams shift effort away from fragile scripting toward risk-based coverage, CI/CD integration, and AI oversight that delivers measurable velocity and reliability gains.
Join Kevin Surace in this SD Times Live! Microwebinar series with Appvance. Learn how plain-language requirements can be turned into test cases, automatically converted into executable scripts, and more.
Corporate legal departments rely on workflow automation to enhance efficiency, but integrating and accessing critical legal data for enterprise reporting remains a challenge. Progress DataDirect Hybrid Data Pipeline provides simple and secure access to a broad range of data sources.
In this webinar, you’ll see how Onit, SaaS leader, powers seamless enterprise reporting by embedding Hybrid Data Pipeline into their platform.
You’ll learn:
• How Onit’s SaaS legal platform enables customers to use their own enterprise reporting tools
• How Progress DataDirect OData connectivity simplifies integration
• Best practices for connecting SaaS workflow applications to enterprise reporting tools
• How legal teams can gain deeper insights with seamless data connectivity
Watch now to discover how Progress DataDirect solutions can optimize your enterprise reporting strategy!
AI technology is disrupting industries at unprecedented speed, yet Gartner research reveals 47% of AI initiatives fail to reach production. This session examines how enterprise-grade AI capabilities, now accessible to businesses of all sizes, are fundamentally transforming operations, while organizational readiness lags critically behind.
Our four-phase methodology—Assessment, Planning, Implementation, and Evaluation—provides a clear path to quantifiable business results across industries. The session follows a compelling narrative arc from AI disruption to practical implementation, concluding with a blueprint for success. Attendees will leave with immediate next steps to begin their journey to AI-driven success.
