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