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CASE STUDY Google Cloud

Google Cloud modernizes lead enrichment with AI

A new agentic AI workforce—built and proven inside Google Cloud’s own go-to-market engine—is delivering faster, high-quality leads at the right time

As one of the fastest-growing major hyperscalers, Google Cloud operates one of the world’s largest demand engines. With that growth came a surge in the volume, variety, and complexity of leads that enter the system.

To convert demand into revenue, sales teams need trusted context as leads move from marketing to sales—everything from the right buyer contacts and roles to account context and relevant market signals—to assess fit and prioritize opportunity.

Until recently, this preparation relied heavily on manual, batch-based effort. As demand grew, this approach strained the process—making it harder to enrich leads fast enough to support timely sales engagement.

Google Cloud partnered with Accenture to redesign lead enrichment as an always-on agentic AI engine that prepares, validates, and routes leads in real time. By bringing the right context forward earlier, the multi-agentic solution removes manual bottlenecks and eliminates lead volume limits, enabling sellers to focus on engaging qualified opportunities with confidence.

30x

faster lead processing

4

hours to process 25,000 inbound records — reduced from nearly a week

Built for real-world scale

The team designed a multi-agent model to orchestrate enrichment, validation, and routing as a single, adaptive system that delivers decision-ready leads and continuously improves as markets and priorities shift.

The model

Built on Google Cloud’s stack (Vertex AI, BigQuery, Gemini) and embedded in core go to market workflows, the model has run at production scale.

The agents

A multi agent environment draws from internal data, 3rd party sources, and enriched datasets that can be refreshed as new information emerges.

The impact

The new model brings the right context forward earlier.  Now, sellers spend less time filling gaps and more time acting on qualified opportunities.

Ready, not just routed

Quality was engineered into the system from the start—so increased speed never comes at the expense of trust.

Humans where it matters most

This shift redesigned how work gets done—using agentic AI to absorb the high-volume, repetitive preparation work so human judgment is applied where it matters most. With routine enrichment handled automatically, people focus on oversight and governance, resolving exceptions, sharpening quality standards, and developing new, higher value signals that help sales engage the right prospects at the right moment—continuously improving decision quality and performance over time.

A capability that evolves with demand

By embedding agentic AI into core demand generation operations, Google Cloud is increasing sales productivity, accelerating conversion and reducing cost-to-serve by up to 80%—while compressing work that once took days into a matter of hours.

What we built together goes beyond improving a single function. By redesigning lead enrichment as an agent-enabled system, the company has created a repeatable way to move intelligence into the flow of work—at speed, at scale, and with human judgment embedded by design.

This approach provides a blueprint for how Google Cloud can apply agentic AI across the business—modernizing core operations, expanding growth capacity, and adapting as markets and buying behaviors evolve.

MEET THE TEAM

Emma Webley

Associate Director – Digital Marketing Strategy, Accenture Song

Peter Sprugel

Senior Manager – Functional AI Strategy, Accenture Song

Abhimanyu Shetty

Senior Manager – Data Architecture, Technology