Control the chaos: An enterprise framework for safe, productive LLMs

Enterprise CTOs face a constant barrage of new large language models (LLMs) that are inevitably accompanied by fanfare and industry noise for their performance on industry benchmarks. But enterprise success depends on how that model is delivered, governed, and integrated inside the business, not just its benchmark performance. The real decision isn’t simply which model to use, but rather which model and provider, together, can deliver the stability, control, and enterprise guarantees the business needs. Failing to make the right choices leads to endless LLM experiments. This paper introduces the eight HFS pillars of enterprise-grade success, offering a framework on which to build real AI success.

WRITER CTO Waseem AlShikh believes making the right choices is becoming harder as foundation model capabilities converge, choices expand, and domain-specific small language models (SLMs) become increasingly popular alternatives.

A quick-fire survey of AI and data-savvy HFS OneCouncil members (enterprise leaders from across industries) found the majority (65%+) were aware of just one to four LLMs 12 months ago. Today, most are aware of more than three times as many, between 10 and 19. Some report awareness of more than 20. The challenge of choice is real.

Amid that proliferation, line-of-business leaders are demanding outcomes while CTO and central IT teams are looking for integration, governance, and risk controls. Add to this the arrival of agentic AI, and now firms must also supervise the tools, context, and autonomy of decisions, not just model outputs.

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