Predictions For 2025
Here are My Predictions forHere are My Predictions for Knowledge Graphs in 2025!
🔵 GraphRAG via Ontologies:
A range of GraphRAG frameworks and products will emerge, offering organisations ways to combine structured, reliable data with the generative capabilities of LLMs in 2025. However, there will be a growing realisation that this can only be done effectively by first establishing clear semantics. Unfortunately, many will probably attempt to reinvent the wheel rather than adopt existing ontological standards.
🔵 Knowledge Graphs as a Foundation for Data Fabric:
All major cloud platforms will introduce highly scalable Knowledge Graph offerings as part of their core services. Meanwhile, some large and complex organisations will begin positioning Knowledge Graphs as a central component of their data fabric strategies. The rise of semantic data products, powered by standards like DPROD, will start to transform data management practices among early adopters. A select few organisations will fully commit to achieving 'total data connectivity.'
🔵 Test-Time Compute Will 'Solve' Reasoning:
I predicate that by the end of 2025, it will be widely accepted that generative models can approximate reasoning so closely that distinguishing between them and 'genuine reasoning' will become nearly impossible. While not a direct Knowledge Graph prediction, this advancement will significantly impact the field, enhancing both ontology generation and graph-based retrieval.
🔵 The Data Crunch:
By the end of 2025, it will become 'accepted wisdom' that organisations must get their data in order to succeed in AI—and that almost everything else is secondary. Although we will not yet reach 'the panic phase,' there will be growing unease within the economic community about the scale of this challenge and the potential consequences for organisations that fail to address it.
These trends underscore the increasing strategic importance of Knowledge Graphs as a cornerstone for GenAI adoption in 2025. I’d love to hear your own predictions—feel free to share them in the comments or challenge mine!!
🔵 GraphRAG via Ontologies:
A range of GraphRAG frameworks and products will emerge, offering organisations ways to combine structured, reliable data with the generative capabilities of LLMs in 2025. However, there will be a growing realisation that this can only be done effectively by first establishing clear semantics. Unfortunately, many will probably attempt to reinvent the wheel rather than adopt existing ontological standards.
🔵 Knowledge Graphs as a Foundation for Data Fabric:
All major cloud platforms will introduce highly scalable Knowledge Graph offerings as part of their core services. Meanwhile, some large and complex organisations will begin positioning Knowledge Graphs as a central component of their data fabric strategies. The rise of semantic data products, powered by standards like DPROD, will start to transform data management practices among early adopters. A select few organisations will fully commit to achieving 'total data connectivity.'
🔵 Test-Time Compute Will 'Solve' Reasoning:
I predicate that by the end of 2025, it will be widely accepted that generative models can approximate reasoning so closely that distinguishing between them and 'genuine reasoning' will become nearly impossible. While not a direct Knowledge Graph prediction, this advancement will significantly impact the field, enhancing both ontology generation and graph-based retrieval.
🔵 The Data Crunch:
By the end of 2025, it will become 'accepted wisdom' that organisations must get their data in order to succeed in AI—and that almost everything else is secondary. Although we will not yet reach 'the panic phase,' there will be growing unease within the economic community about the scale of this challenge and the potential consequences for organisations that fail to address it.
These trends underscore the increasing strategic importance of Knowledge Graphs as a cornerstone for GenAI adoption in 2025.
