Make AI Useful with Knowledge Graphs

Many organizations have invested in AI—but still struggle to see real business impact because AI lacks the context of how work actually gets done. In this live Forrester + Atlassian webinar, learn how knowledge graphs, like Atlassian’s Teamwork Graph, can make AI truly useful at work.

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  • Many organizations have poured time and budget into AI and AI agents, yet still don’t see the returns they expected. Building on a new Forrester Consulting Thought Leadership Paper, commissioned by Atlassian and based on a survey of 275 AI decision-makers, this webinar explores why AI initiatives stall—and how knowledge graphs, like Atlassian’s Teamwork Graph, can transform AI’s usefulness by connecting it to unified, AI‑ready organizational knowledge.
  • Join Forrester Senior Analyst Will White and Atlassian Senior Principal PM Hersh Iyer as they share key findings from Forrester’s research on enterprise AI performance; explain what knowledge graphs are and why they’re critical for trustworthy, high‑impact AI; show how connecting AI to the right knowledge improves relevance, adoption, and ROI; and discuss the modern data platform foundations needed to scale AI across your organization.

발표자

Will White

Senior Analyst at Forrester

Will works as a senior analyst on Forrester’s technology architecture and delivery (TAD) team, focusing on modern service delivery. His research helps enterprises understand and capitalize on advancements in processes and technologies, including unified communications as a service (UCaaS), the proactive help desk, chatbots for employee support, enterprise service management (ESM), virtual desktop infrastructure (VDI), and more.

Hersh Iyer

Senior Principal Product Manager at Atlassian

Hersh Iyer는 Atlassian의 수석 제품 매니저로, 플랫폼 및 데이터 전략을 이끌고 있습니다. 현재 그는 AI 지원 데이터 플랫폼을 구성하는 요소를 정의하고 해당 전략을 AI 경험을 지원하는 기본 기능으로 전환하는 데 집중하고 있습니다. 그는 Rovo와 같은 제품의 기반이 되는 Atlassian의 Teamwork Graph를 포함하여 주요 이니셔티브를 구상하고 시작하는 데 기여했습니다.

Atlassian에 합류하기 전에 Hersh는 Amazon에서 제품 리더십 역할을 맡아 Alexa 관련 업무를 담당하며 머신러닝, 자동화 및 멀티모달 UI 분야에서 경험을 쌓았습니다. Hersh는 NYU Stern에서 MBA를, Georgia Tech에서 컴퓨터 과학 석사 학위를 취득했습니다.