Big Data ATL

Agentic browsers and AI bots are quietly reshaping how traffic flows across the web—and breaking your analytics in the process. According to HUMAN Security, agentic browsing traffic surged 6,900% between 2024 and 2025, fueled by tools like Perplexity Comet and ChatGPT Atlas. The result? A growing share of pageviews, clicks, and conversions that aren’t coming from people—and aren’t being flagged by traditional analytics tools.

In this session, we’ll unpack how AI agents distort metrics like bounce rate, CTR, and conversion funnels, and why legacy bot detection methods fall short. We’ll also show how Snowplow is tackling this challenge with a dual-layered approach: combining CDN-level server-side signals with client-side fingerprinting and behavioral pattern analysis.

You’ll walk away with a framework to distinguish human from synthetic sessions, normalize inconsistent AI attribution, and uncover where agentic traffic is helping—or hurting—your site’s performance. It's about regaining visibility, restoring trust in your data, and adapting your web strategy to an AI-browsing future.

What You'll Learn:

1️⃣ Understand agentic traffic distortion: Learn how AI browsers and bots impact core engagement metrics—and why you likely aren’t seeing it.

2️⃣ Detect invisible AI traffic: See how behavioral analysis and hybrid event collection expose agent takeovers without false positives.

3️⃣ Normalize attribution across sessions: Identify where AI platforms are routing users and distinguish between synthetic influence and genuine engagement.

4️⃣ Plan for an agent-first future: Learn how to adapt optimization and content strategies for hybrid audiences: humans, bots, and everything in between.

Many enterprises believe they’re ready for AI once models are selected, platforms are deployed, and pilots are underway. But in practice, AI initiatives often stall before reaching production—or they underperform once they do. The root cause? The data isn’t actually ready.

In this thought-leadership session, Naveen Punjabi from Google Cloud and Jake Bengtson from Striim unpack four critical signs that your data foundation can actually support AI at scale. Drawing from real-world customer patterns, we’ll explore why centralized data isn’t enough, how invisible data errors derail AI outcomes, and why stale data threatens use cases like RAG and AI agents.

What we'll cover:

• What Google Cloud is seeing across enterprise AI adoption—and where data readiness tends to break down
• Four practical indicators your data is ready for trustworthy, production-grade AI
• Why validation and accuracy matter before any models get involved
• How real-time pipelines give AI access to operational truth
• How Google Cloud and Striim help enterprises move from AI experimentation to enterprise impact

This session is built for data, analytics, and AI leaders ready to move beyond AI experimentation—and build foundations that truly support scale.

What You'll Learn:

1️⃣ Spot the Warning Signs: Know when your data might silently sabotage your AI initiatives.

2️⃣ Go Beyond Centralization: Why a data lake isn’t the same as a data strategy.

3️⃣ Enable Live AI: How real-time pipelines can unlock true operational intelligence.

4️⃣ Validate Early, Scale Confidently: Why data quality must be addressed before model deployment.

5️⃣Learn from the Field: What Google Cloud and Striim have seen across real enterprise AI journeys.

As AI evolves from passive tools to active collaborators, enterprises face a pivotal shift: embracing systems that can not only respond but also take initiative. This webinar unpacks what it means to build and deploy agentic AI—models that possess goal-directed reasoning, dynamic planning capabilities, and the ability to autonomously execute tasks across complex workflows.

We’ll explore architectural and governance considerations for enterprise adoption, including how to integrate agentic systems into existing data ecosystems, ensure transparency and control, and maintain human-in-the-loop oversight. Join us for a practical, forward-looking discussion on how to prepare your organization for AI that doesn’t just assist—but acts.

What You'll Learn:

1️⃣ What Agentic AI Really Means: Understand the core components—reasoning, planning, and autonomous action—and how they differ from traditional AI assistants.

2️⃣ Enterprise Readiness: Learn what technical and organizational infrastructure you need to safely and effectively deploy agentic systems.

3️⃣ Designing for Oversight and Control: Explore observability, guardrails, and human-in-the-loop strategies for managing proactive AI in production environments.

Panelists to be announced soon.

Explore the real-world impact of Agentic AI in our fast-paced, insight-packed virtual showcase. Each 10-minute session features a live demo from a leading innovator in the Agentic AI space—highlighting practical applications, dynamic workflows, and tangible business outcomes.

This isn't just another pitch session. It’s a curated look at how agent-based systems are driving intelligent automation, adaptive planning, and cross-functional orchestration across industries. You’ll meet the minds behind these technologies and see firsthand how they’re redefining what's possible in enterprise AI.

What You'll Learn:

1️⃣ Autonomous Workflows: See how agentic systems plan, coordinate, and execute complex tasks across tools and teams.

2️⃣ Dynamic Decisioning: Explore examples of contextual reasoning, goal alignment, and memory-enhanced agents in action.

3️⃣Practical Integration: Understand what it takes to embed agentic AI into your stack—without overhauling everything.

Engage live with founders and builders shaping the future of autonomous enterprise solutions.

You’re short on time but deep on curiosity. This format respects both—cutting straight to the tech and the teams behind it. No filler, no fluff. Just signal.