95% of enterprise GenAI pilots fail—but it’s not the models’ fault. The winners connect data, enforce clear semantics, and wrap LLMs in formal ontologies for trustworthy, validated AI.

From SAP and Netflix to ServiceNow and Samsung, leading organisations are embracing knowledge graphs and ontologies as foundational infrastructure for AI and analytics. The reason is clear: AI needs context, businesses need unified meaning, and users need semantic access to insights. The knowledge graph is becoming the new enterprise standard.

Forward-thinking organisations are realising that their AI strategy is their data strategy. The next frontier isn’t extracting intelligence from data — it’s embedding intelligence back into it. By using AI to shape, connect, and structure data through ontologies and knowledge graphs, we create systems that truly reflect how the business thinks.

What does DeepSeek mean for enterprises? The release of DeepSeek’s R1 model has caused shockwaves. This feels like a pivotal moment - demonstrating how constraints can drive innovation while also hinting at the economic and geopolitical 'mega-event' looming on the horizon. Beyond its clever efficiency gains, R1 underscores two critical trends that enterprises should heed: the rise of open-source AI and the irreplaceable value of high-quality data.