PepsiCo
Workforce collaboration
Disparate tools slowed 320,000 employees. Unifying on Teams and Copilot connected the workforce and embedded AI into daily habits.
- 90-95% daily active use of Copilot
Manual order entry caused pricing errors and billing disputes. Now, an AI agent flags discrepancies and drafts client emails for staff.
A global consumer goods enterprise with 90,000 employees across 120 countries, processing thousands of daily customer orders through various channels including email, PDF, and electronic data interchange.
Manual workflows and complex order processing led to frequent data entry errors and pricing inconsistencies across internal systems. These...
“AI doesn’t sit still. It is challenging and reshaping our strategy.”
Global dairy, plant-based food, bottled water, and specialized nutrition company.
Enterprise software, cloud infrastructure, and consumer electronics platform.
Danone's Order processing is part of this use case:
Related implementations across industries and use cases
Disparate tools slowed 320,000 employees. Unifying on Teams and Copilot connected the workforce and embedded AI into daily habits.
Manual coordination across systems bottlenecked teams. Now, employees build custom AI agents to automate tasks like purchase analysis.
Sales reps manually interpreted unstructured email orders. Now, AI extracts product codes and validates data to trigger ERP workflows.
Disparate tools slowed 320,000 employees. Unifying on Teams and Copilot connected the workforce and embedded AI into daily habits.
Manual coordination across systems bottlenecked teams. Now, employees build custom AI agents to automate tasks like purchase analysis.
Every new meeting question triggered days of data prep. Finance teams now ask the data lake directly and test hypotheses in minutes.
Every 'why is this number moving?' queued behind the domain team. Now leaders ask Genie directly and get the answer on the spot.
Hundreds of keys, one invoice line, no owners. Giving each key a name and purpose surfaced a ghost workload and a caching fix within weeks.
Creditworthy but credit-invisible: millions of Colombians locked out. Graph ML mapped their behavior instead, making them legible to lending.
Manual order entry caused pricing errors and billing disputes. Now, an AI agent flags discrepancies and drafts client emails for staff.
A global consumer goods enterprise with 90,000 employees across 120 countries, processing thousands of daily customer orders through various channels including email, PDF, and electronic data interchange.
Manual workflows and complex order processing led to frequent data entry errors and pricing inconsistencies across internal systems. These...
“AI doesn’t sit still. It is challenging and reshaping our strategy.”
Global dairy, plant-based food, bottled water, and specialized nutrition company.
Enterprise software, cloud infrastructure, and consumer electronics platform.
Danone's Order processing is part of this use case:
Related implementations across industries and use cases
Disparate tools slowed 320,000 employees. Unifying on Teams and Copilot connected the workforce and embedded AI into daily habits.
Manual coordination across systems bottlenecked teams. Now, employees build custom AI agents to automate tasks like purchase analysis.
Sales reps manually interpreted unstructured email orders. Now, AI extracts product codes and validates data to trigger ERP workflows.
Disparate tools slowed 320,000 employees. Unifying on Teams and Copilot connected the workforce and embedded AI into daily habits.
Manual coordination across systems bottlenecked teams. Now, employees build custom AI agents to automate tasks like purchase analysis.
Every new meeting question triggered days of data prep. Finance teams now ask the data lake directly and test hypotheses in minutes.
Every 'why is this number moving?' queued behind the domain team. Now leaders ask Genie directly and get the answer on the spot.
Hundreds of keys, one invoice line, no owners. Giving each key a name and purpose surfaced a ghost workload and a caching fix within weeks.
Creditworthy but credit-invisible: millions of Colombians locked out. Graph ML mapped their behavior instead, making them legible to lending.