AI Cost vs AI Value: How to Use Claude Efficiently
Key Speaker
AI/ML Lead, Ksolves India Limited
He is an AI/ML specialist with hands-on experience in large language model workflows, prompt engineering, enterprise AI adoption, and building cost-efficient AI systems at scale.
In this session, Sumit Tyagi, AI/ML Lead at Ksolves India Limited, tackles one of the most pressing challenges facing enterprise AI teams today: AI adoption is accelerating, but rising token costs, inefficient workflows, and uncontrolled usage are quietly eating into the business value that AI is supposed to deliver.
Most organizations investing in AI focus heavily on capability – which model to use, which use case to tackle first – but very few have a clear strategy for managing what it actually costs to run AI at scale. The result is ballooning budgets, underperforming workflows, and leadership questioning whether the investment is worth it.
This webinar breaks down exactly how enterprises can use Claude more efficiently – from understanding how token usage impacts your AI budget, to choosing the right model for the right task, to building smarter prompt workflows that reduce unnecessary spend without compromising output quality. Every strategy covered is practical and immediately applicable, designed for teams that are already using AI and want to do it better.
If your organization is exploring AI at scale, this session will help you strike the right balance between innovation and cost efficiency.
Key Takeaways
- How token usage directly impacts your AI budget and where costs silently accumulate.
- Prompt optimization strategies that reduce spend without sacrificing output quality.
- How to choose the right Claude model for the right task and avoid over-engineering.
- Practical ways to improve productivity through smarter AI workflows.
- Real strategies businesses can apply immediately to maximize AI ROI.
- Scalable frameworks for enterprise AI adoption that keep costs under control.
