Docusign Names Graham Sheldon Chief Product Officer

Jun 2, 2026
Docusign has appointed Graham Sheldon as Chief Product Officer, effective July 6. Sheldon will lead product, design, and user research for the company's Intelligent Agreement Management platform.

Docusign announced in a press release the appointment of Graham Sheldon as Chief Product Officer, effective July 6. Sheldon will oversee product, design, and user research, guiding the company's Intelligent Agreement Management platform as it expands its capabilities in AI and automation.

Sheldon previously served as Chief Product Officer at UiPath, where he led the company's transition into a platform for agentic automation and business orchestration. Before that, he spent over twenty years at Microsoft, where he helped build Microsoft Teams and held leadership roles across Dynamics, Bing, and Office.

According to Docusign, Sheldon’s experience in AI and large-scale enterprise software will help advance its Intelligent Agreement Management offering, which is used by approximately 40,000 customers. The company recently introduced MCP server connectors for Anthropic Claude, Gemini, and OpenAI ChatGPT to strengthen its integration ecosystem.

Docusign CEO Allan Thygesen thanked outgoing Chief Product Officer Dmitri Krakovsky for his contributions, noting that the foundation he established will continue to support customers as the company moves forward.

We hope you enjoyed this article

Consider subscribing to one of our newsletters like Daily AI Brief.

Also, consider following us on social media:

Free newsletter

Daily AI Brief

Daily report covering major AI developments and industry news, with both top stories and complete market updates

Whitepaper

Tensordyne Napier: What If One Rack Could Do the Work of Nine?

Tensordyne

This Tensordyne whitepaper presents Napier, an inference-focused AI processor and rack-scale system based on the company’s TDN Math logarithmic number system. It examines infrastructure requirements for large mixture-of-experts and agentic models, compares major inference architecture approaches, and details the TDN AIP processor, TDN72 pod, TDN Link fabric, and Napier Ultra configuration. The paper reports simulation-based performance, cost, and accuracy-validation results, including Tensordyne’s projected comparison of one Napier rack with a nine-rack Nvidia Rubin plus Groq deployment; the chip is reported as taped out and in fabrication.

Read more
Free, six days a week

Daily AI Brief: the AI news that matters, in your inbox.