Innovation may start in the West. The proof that it scales is increasingly being written in India.
Watch the podcast to understand why enterprise AI’s next proof points are coming from India, and what it takes to move from controlled pilots to measurable outcomes.
From pilot to production
Most enterprises have already proven that AI works in a controlled environment. The harder test is what happens next, when a pilot meets real organizational data, decades of legacy systems, security guardrails and people who need a reason to change how they work.
That is where most AI programs stall. Usually, the platform isn’t the problem. The business context is: the latent processes and judgment calls that live in people’s heads and never made it into the data estate. Without that context, and without governance designed in from the start, even the most capable platform struggles to deliver results the business can measure.
Featured Speakers
Sandeep Srinivasan, Corporate Vice President & Head of APAC, Persistent
Sandeep brings the view from the delivery side. He sees how enterprises across APAC turn platform capability into industry outcomes, and why Persistent frames AI around context, coordination and control.
Anand Kalidoss, Senior Director – Enterprise Business, Databricks
Anand brings the view from the platform side. He works with Databricks’ enterprise customers across a fast-growing market, from regulated financial institutions to digital natives, and sees which ones are scaling AI and why.
Scale is a context problem, not a model problem
The conversation keeps returning to one idea: enterprise AI scales when industry context, platform capability and governance come together. India is an ideal proving ground because it combines enterprise scale, industries ready to adopt and a deep talent ecosystem. That makes it a place where projects are tested hard and the lessons feed back into the platforms. The enterprises pulling ahead hold every initiative to measurable outcomes, such as new revenue, better profitability and faster turnaround, and they work with partners who understand their business as well as the technology.
Six Shifts Explored:
- From experimentation to execution. The inflection point has passed. The work now is adoption, guardrails and scale.
- From AI for developers to AI for leadership. Business leaders are asking their data directly what changed and why, without waiting on MIS teams.
- From “regulated means slow” to “regulated means first.” India’s financial institutions are using AI for fraud, risk and revenue growth, including local-language customer engagement.
- From model-first to context-first design. The hardest part of scaling is capturing the business knowledge that lives in people’s heads.
- From governance as an afterthought to governance by design. Lineage, access control and traceability for autonomous decisions are becoming the basis of scale adoption.
- From platform to ecosystem. Analytical, application and AI layers are converging, and partners with vertical depth are what make the platform real for the enterprise.
Join the conversation. Contact us at podcasts@persistent.com.
Speakers
Anand Kalidoss, Senior Director, Enterprise Business, Databricks
Sandeep Srinivasan, Corporate Vice President & Head of APAC, Persistent
