Knowledge Graph adoption in 2025: Success stories, roadblocks, and the way forward
A Talk by Timm Amstein , Dr Ben Gardner and Afraz Jaffri
About this Talk
Even though knowledge graphs are a mature technology with more than 20 years of history, they are yet to reach their full potential in terms of adoption.
Knowledge Graphs can bring a range of benefits, and represent significant value for a wide array of organizations and use cases.
Knowledge graphs support collaboration and sharing, exploration and discovery, and the extraction of insights through analysis.
Knowledge graphs capture information about the world in a visually intuitive format yet are still able to represent explicit semantics and complex relationships.
Knowledge graphs act as the backbone of a number of products, including search, smart assistants and recommendation engines.
Generative AI models can be combined with knowledge graphs to provide context for more accurate outputs in a technique becoming known as GraphRAG or G-RAG.
However, knowledge graph adoption requires both solid technical tooling and significant implementation skills that span both technical and domain knowledge.
Join us as we explore success stories, roadblocks, and the way forward.
Key Topics
- What are the benefits driving Knowledge Graph adoption?
- What does Knowledge Graph adoption look like today?
- What types of organizations are using Knowledge Graphs?
- What are the roadblocks hindering Knowledge Graph adoption?
- What can be done to facilitate adoption?
Target Audience
- CxOs
- Technical Managers
- Product Managers
- Line of Business Stakeholders
Goals
- Explore the benefits knowledge graphs can bring to organizations, and what is needed to make that happen
- Answer questions that matter
- What organizations are using Knowledge Graphs, and what are the drivers for adoption?
- What is the current state of the art, and how does Knowledge Graphs adoption work?
- What are the next milestones / roadblocks?
Session outline:
- Introduction
- Meet and Greet
- Setting the stage
- Why Knowledge Graphs?
- What is a Knowledge Graph?
- What is the relationship between Knowledge Graphs and Ontologies?
- What kind of problems can we solve by using knowledge graphs?
- Adoption drivers
- Manage increasing number of data silos
- Make better use of unstructured data held using standardized metadata
- Awareness of KGs use in consumer products & services
- Complement AI & ML with explicit knowledge, rules & semantics
- How does Generative AI relate and contribute to Knowledge Graph adoption?
- Increased usage of KG & LLMs to provide enhanced contextual understanding
- Use of graph algorithms & machine learning in complex networks
- Emerging landscape of Web3 applications; need for data access across trust networks
- What kind of problems are not best solved with knowledge graphs?
- What are some real world examples of knowledge graphs in the enterprise?
- Putting a Knowledge Graph in Your Organization
- What are the profiles of organizations using Knowledge Graphs?
- Corporates
- Mid-market
- Others
- How does adoption differ across those?
- What is a typical adoption path?
- Where does the data come from to populate knowledge graphs?
- Who are the major vendors for knowledge graph technology?
- What are some common technology stacks used in knowledge graph deployments?
- What skills are required to deploy a knowledge graph application?
- Are the skills readily available in the workforce?
- What is the breadth and depth of tooling for knowledge graphs?
- How good are knowledge graph visualization tools?
- How well do knowledge graphs scale?
- Removing roadblocks and the way forward
- What are the major obstacles organizations need to remove to reap the benefits of Knowledge Graphs?
- Difficult to capture business value/relevance in early implementation stages
- Moving KG models from prototype to production requires expertise
- Graph DBMS market is fragmented
- Making internal data interoperable with external knowledge graphs is a challenge
- In-house expertise is lacking, and identifying third-party providers is difficult
- What can be done to remove or mitigate those roadblocks?
- How do you see Knowledge Graph adoption evolving?
Format
- Extended panel
- Expert discussion, coordinated by moderator
- 1,5 - 2 hours running time
- Running time includes modules of expert discussion, interspersed with modules of audience Q&A / interaction
Level
- Beginner - Intermediate
Prerequisite Knowledge
- Basic understanding of Knowledge Graphs & Databases will be helpful
About The Speakers
Senior Solution Architect and Graph Expert, Capgemini
Timm has the strong desire to link people, solutions and data together. He is working as a Senior Solution Architect and Graph Expert for Capgemini Insights & Data Germany on projects in the automotive, life science sector and retail sector.
R&D Lead for Data Mesh and Semantic Infrastructure, AstraZeneca
Ben is responsible for the application of graph technology in support of Information Discovery. He is focused on delivering FAIR Data-centric architecture to create multimodal integrated data sets to enable exploration and reuse of pre-clinical, clinical and Real World Evidence data.
Moderators
Connected Data London
Got tech, data, AI and media, and not afraid to use them I help people: * Map and understand complex domains to make better decisions * Design, implement and monitor models, processes & systems to achieve goals * Craft communication strategies and outreach initiatives to grow awareness & market
We’re a cloud tech company that provides organisations around the world with computing infrastructure and software to help them innovate, unlock efficiencies and become more effective. We also created the world’s first – and only – autonomous database to help organise and secure our customers’ data.
