Organisations behave like dissipative systems — optimising locally while exporting entropy to the whole. To become AI-native, we must redraw our boundaries, dissolving silos and integrating intelligence at the organisational level. Knowledge Graphs provide the connective tissue for this transformation, turning chaos into coherence.

If software is eating the world and AI is eating software, what eats AI? The answer is philosophy—expressed through a clear, machine-readable ontology. By surfacing your enterprise’s core semantics and linking them to real data, you give AI a lens to reason over what truly matters: how your business creates value.

DeepMind’s AlphaEvolve blends LLM creativity with automated evaluation, unlocking breakthroughs from new matrix multiplication algorithms to global compute optimisation. Its success signals a new era for verifiable AI — and shows why enterprises need semantic frameworks like ontologies and knowledge graphs to bring similar rigour to complex business domains.

After years of rapid breakthroughs, AI’s exponential curve seems to be catching its breath. But this isn’t a slowdown — it’s a strategic pause. With generative AI reaching a 'good enough' baseline, now is the moment to focus on structure, meaning, and human-guided scaffolding through knowledge graphs.