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Leon Taiman, Global Practice Lead at Dell Technologies, discusses the strategic partnership between Dell, Cloudera, and NVIDIA to accelerate the adoption of Private AI on-premises for customers.
The AI Forecast welcomes back John Santaferraro, host of The Digital Analyst Podcast and CEO of Ferraro Consulting, for a candid look at what’s really coming next for AI in 2026.
The AI ecosystem is exploding with tools that promise to accelerate delivery, improve quality, and transform the way we work. Yet for many teams, evaluating these tools is overwhelming - flashy demos and marketing claims rarely answer the real questions: Will this work in our context? Can it scale? Is it sustainable?
AI is reshaping software testing, but real quality does not come from hype alone. This session explores where AI truly adds value in automation and where human testers remain essential. It focuses on building a practical partnership between AI and testers, where speed and scale are balanced with judgment, context, and responsibility.
AI is leveling the field across organizations. Everyone, from leaders to individual contributors, is approaching work with a beginner’s mindset, questioning what AI can do, what it cannot, and how it affects business, customers, and roles. This shared uncertainty challenges traditional leadership models and raises a fundamental question. How does leadership evolve when no one has all the answers?
The SDLC, or software development lifecycle, is undergoing a radical change. Engineering teams have been using conventional, frequently reactive procedures for decades. We construct, test, correct, and implement. However, in today's fiercely competitive digital world, this traditional strategy is insufficient. It can't keep up with the complexity of contemporary applications and is too sluggish and prone to human mistakes.
AI is fundamentally reshaping software quality, and the organizations leading this shift aren’t waiting to adapt. In October 2025, we brought together over 1,000 quality engineering leaders, practitioners, and innovators for Transform, our annual conference exploring what’s next in software delivery.
Retrieval-Augmented Generation can sound convincing while still being wrong. This session focuses on moving beyond surface-level metrics and turning stochastic AI outputs into evidence-backed, verifiable results. It explores how to test the entire RAG pipeline, from ingestion and indexing to retrieval, grounding, and answerability, ensuring every response is traceable to the right source, policy, and user context.
What if you could ask ChatGPT "which customers haven't ordered in 90 days?" and get an instant answer from your actual database? I set this up live in under 5 minutes. No code. No SQL. Just questions and answers.