COGNIWARE INSIGHTS
Latest thinking
INSIGHT
What every CIO needs to know about frontier labs' retention of sensitive enterprise data
There's a critical AI risk most CIOs are overlooking, and may not even know about – leakage of sensitive or proprietary data through use of frontier models.
Ambarish Desai
INSIGHT
6 Reasons Why You Should Own Your Inference
If your AI strategy depends entirely on hosted frontier models, then you do not fully control your AI strategy.
Ambarish Desai
INSIGHT
Will the Frontier Model Boom Last?
The enterprise AI stack will not be one model. It will be a portfolio: frontier models for the work that needs frontier intelligence, smaller proprietary models for lower-cost production use cases, open-weight models where control, cost, latency, or data posture matter, specialized models for narrow tasks, and local or private inference where economics and governance justify it.
Ambarish Desai
INSIGHT
Token Shock: Why Enterprise AI Economics Are About to Change Forever
Margin is the new battleground for enterprise AI. As AI moves from pilot to production, economics will start to have a major impact on AI strategy and usage. Enterprises that act strategically to embrace open source models and smart prompt routing will avoid token shock before it starts to erode margins – and ultimately will be the winners in the AI race.
Ambarish Desai
INSIGHT
As AI Scales, Are We Headed for Blackouts?
As the founder of CogniwareAI, a software firm dedicated to optimizing AI infrastructure costs and power consumption needs, I’ve been diving deep into the latest projections on AI’s energy demands. The numbers are staggering — and they beg a crucial question: If GenAI scales as projected, are we headed for blackouts?
Ambarish Desai
