Many enterprises are focusing on AI models, infrastructure, and prompt engineering while ignoring the real bottleneck—enterprise context. As a result, most agentic AI initiatives remain stuck in pilots or chatbot use cases, unable to scale into impactful business workflows.
In a Forbes article, Deepak Khosla, the Chief Growth Officer & Head of AI Business at Impetus Technologies, talks about how enterprises that invest in building a strong context foundation will be the ones to move from pilots to scalable, reliable, and cost-efficient agentic AI.
Key takeaways
- Models are not the differentiator—context is: Competitive advantage does not come from choosing the best model; it comes from grounding AI in enterprise-specific knowledge and meaning.
- Enterprise context has four distinct layers: Siloed data, lack of semantic understanding, execution loopholes, and inadequate guardrails prevent agents from delivering reliable outcomes.
- Agentic AI is more than a smarter chatbot: Intelligent agents can take actions, make decisions, and operate continuously—which requires deep contextual awareness.
- Context directly impacts cost and efficiency: Without a proper context layer, enterprises overspend on compute and tokens to achieve sub-optimal results.
- Scaling agents without governance creates enterprise risk: Deploying autonomous agents without the right controls can lead to operational risks.
Read the full article here: Agentic AI Won’t Scale Without Enterprise Context
