Ep 17 - 2026 Predictions: What's Next for Data Streaming and AI

Failed to add items

Sorry, we are unable to add the item because your shopping cart is already at capacity.

Add to basket failed.

Please try again later

Add to wishlist failed.

Please try again later

Remove from wishlist failed.

Please try again later

Adding to library failed

Please try again

Follow podcast failed

Unfollow podcast failed

Ep 17 - 2026 Predictions: What's Next for Data Streaming and AI

Listen for free

View show details

AI isn’t just evolving—it’s reshaping who your customers are, how systems operate, and what real time really means. From machines making purchase decisions to agents increasing query volume across databases, the realities of 2026 are forcing leaders to rethink data architecture and governance strategies at a fundamental level. In this episode, Joseph is joined by Will LaForest (Field CTO, Confluent), Adi Polak (Director of Developer Advocacy & Experience, Confluent), and independent analyst, Sanjeev Mohan, to break down critical insights from Confluent’s 2026 Predictions Report. Together, they explore how agentic AI will transform digital commerce, why Model Context Protocol is quickly becoming table stakes, and how context engineering is emerging as the next major unlock for AI systems. The conversation also dives into the acceleration of AI-enabled cybercrime, why enterprises can no longer dismiss data governance, how Apache Iceberg™ is quickly becoming the standard in cold data management, and much more.If you’re navigating AI and data streaming, this episode offers a grounded, opinionated take on what’s coming next—and how technologies like Apache Kafka® and Apache Flink® will shape what you need to do now. About the Guests:Will LaForestWill is Field CTO for Confluent. Will works with customers across a broad spectrum of industries and government, enabling them to realize the benefits of a data in motion architecture with event streaming. He is passionate about data technology innovation and has spent 26 years helping customers wrangle data at massive scale. His technical career spans diverse areas from software engineering, NoSQL, data science, cloud computing, machine learning, and building statistical visualization software but began with code slinging at DARPA as a teenager. Will holds degrees in mathematics and physics from the University of Virginia. Adi PolakAdi is the Director of Advocacy and Developer Experience Engineering at Confluent. For most of her professional life, she has worked with data and machine learning for operations and analytics. As a data practitioner, she developed algorithms to solve real-world problems using machine learning techniques and expertise in Apache Spark, Kafka, HDFS, and distributed large-scale systems.Adi has taught how to scale machine learning systems to thousands of practitioners, and is the author of successful books: Scaling Machine Learning with Spark and High Performance Spark 2nd Edition.Sanjeev MohanSanjeev is a recognized thought leader in cloud technologies, modern data architectures, analytics, and artificial intelligence. With a keen focus on emerging trends and technologies, Sanjeev hosts It Depends podcast and authors regular Medium blogs. He is also the author of Data Product for Dummies.Formerly a Vice President at Gartner, Sanjeev was renowned for his in-depth research and strategic insights, shaping the research agenda for data and analytics globally. Over the past three years, he has led SanjMo, a consultancy specializing in technical advisory services that elevate category and brand awareness for clients.Guest Highlights:“There was already an asymmetric relationship between attackers and defenders. This just increases that, because it’s easier to use AI to attack than it is to use it to defend.” — Will LaForest“We’re about to accidentally DDoS our software and databases, because we’re giving a tool to automate things without thinking if our systems are actually ready for it.” — Adi Polak“Your proprietary data is your only moat. Everything else—models, performance, tooling—will keep changing.” — Sanjeev MohanEpisode Timestamps: 03:40 – Predictions Report Overview05:05 – Prediction 1: The Rise of Agentic Commerce: Machines Are Your New Customers12:45 – Prediction 2: Leading Platforms Will Offer Model Context Protocol18:00 – Prediction 3: Context Engineering Is the Next AI Unlock24:15 – Prediction 4: AI Will Apply Increased Pressure to Existing Databases30:10 – Prediction 5: AI Will Drive Cyber Crime to Unprecedented Levels36:15 – Prediction 6: AI Will Accelerate Enterprise Investment in Data Governance43:25 – Prediction 7: Apache Iceberg™ Will Become the Standard for Cost-Effective Cold Data Management49:20 – Prediction 8: Your AI Strategy Will Need an Independent Data Plane to Avoid Overcommitting55:00 – Prediction 9: Early Adopters of Durable Execution Engines Will Gain a Competitive AI Edge1:00:01 – Prediction 10: Improvements in Generative AI Will Help Businesses Finally Address Legacy Tech DebtDive Deeper into Data Streaming:EP1—Stream On: Unleashing Innovation With Data Streaming | Life Is But A StreamEP2—Processing Without Pause: Continuous Stream Processing and Apache Flink® | Life Is But A StreamEP3—The Connective Tissue: Shift Left to Turn Data Chaos to Clarity | Life Is But A StreamLinks & Resources:Confluent’s 2026 Predictions Report...

No reviews yet