In 2021, I led the research and design of Ariba Canvas—SAP’s first generative AI tool for procurement—to accelerate category research and strategy development. This 0→1 initiative addressed the inefficiencies of manual data analysis and empowered category managers to make faster, more informed decisions.

CONTEXT

How might we empower advanced planners to develop better category strategies through deeper research and flexible workflows?

As we learned, seasoned category managers need to synthesize insights from massive volumes of procurement data—spend patterns, supplier performance, market trends, and risk factors—to develop impactful strategies.

But existing tools required switching between systems and manually aggregating information, slowing decision-making and reducing confidence in strategic planning.

OPPORTUNITY

Empowering advanced category planners with an intelligent research & scenario planning tool

Category Managers lacked a centralized, intuitive way to query and analyze internal and external data. The opportunity was to reimagine research workflows using generative AI to reduce cognitive load, surface insights faster, and enable real-time decision-making.

Our strategic goal was to transform SAP Ariba from a transactional tool into an intelligent, strategic planning platform powered by AI.

TEAMS

Hong Xu, Product Manager (Category Management)
Hui Dong, Data Scientist (Supplier Management)
Vijay C, Engineer Lead
SAP Business AI Lab

MY ROLE

Led discovery research
Concept development & prototyping
Defined core workflows & AI interaction Patterns
Aligned vision across stakeholders

SOLUTION

Ariba Canvas, category manager’s intelligent research companion

I conceptualized “Ariba Canvas”—an intelligent research tool designed to enable a new way to explore, visualize, and interact with procurement data.

From expert strategists to newer category managers, ensuring both flexibility and structure in AI-powered planning, there are two workflows that made Ariba Canvas adaptable to diverse user needs:

01 The exploratory workflow

As we learned, seasoned category managers need a more exploratory approach to research and data analysis to develop impactful strategies.

Enabling prompt-as-interface & user data upload

Ask open-ended questions about suppliers, spend categories, market trends, and risk.
AI synthesizes insights from both structured procurement data and unstructured documents.

Visual canvas for organizing findings and tracking research progress

Users can organize, compare, and annotate insights in a flexible research canvas to inform strategy development.

02 The guided workflow

For users seeking a faster path to output.

Ariba Canvas generates a draft category strategy plan based on key inputs (e.g., category objectives, supply risk).
Users can review and edit each section (e.g., goals, supplier strategy, KPIs) and track revisions in context.
Designed to help junior or time-constrained users take confident first steps, while still supporting strategic iteration.

THE IMPACT

Laid the foundation for SAP’s GenAI roadmap in procurement

Product Vision (Procurement Intelligence)

Helped teams envision a strategic, insight-led future for category management tools.
Inspired buy-in across leadership and product orgs, leading to roadmap prioritization.

SAP Design

Introduced new UX patterns for GenAI interactions in enterprise tools.

SAP Business AI

Helped shape cross-functional alignment on AI governance, data security, and trust.

Ariba Canvas