AWS AI Strategy: Praveen Sridhar on Partner Growth

The Indian IT partner ecosystem has seen many technology transitions. Each wave has created new winners and exposed slow runners. Hardware partners had to adapt to software. Software partners had to embrace services. System integrators had to evolve to the Cloud. And Cloud partners must now nail generative AI, data readiness, agentic workflows, governance and business outcomes.

For Praveen Sridhar, Head, Partner & ISV Business, AWS India and South Asia, the next phase is clear: partners must not stop at putting together the tarmac but also help enterprises take off to the outcomes that they want, moving AI from pilots to production. In a conversation with Thomas George, Sridhar explains how AWS is doing just that, enabling partners through AI Competency, marketplace-led commerce, industry specialisation and skilling.

How are AWS partners being enabled to address these imperatives before selling AI use cases?

We are in one of the most exciting phases of technology. In one generation, we have seen mobility, Cloud and now AI as transformative waves. AI holds tremendous promise, but how do enterprises move from experimentation to real value? According to McKinsey’s 2025 State of AI report, almost 88% of enterprises have already tried AI in some form, but only 39% see value and ROI.

We recognised this early. There are four broad challenges: data readiness, talent gap, integration complexity and scaling (technical and commercial) to production. This is where partners become very important. AWS was the first to launch an AI Competency. Partners here have demonstrated the ability to take projects from pilot to production through their technology depth, change-management capability, production-grade delivery and business-outcome orientation.

We are also assisting partners through the Generative AI Innovation Centre, where AWS has invested about USD 100 million.

Is data readiness a bigger challenge in India than in mature markets? Why?

The good part about India is that customers have access to a tremendous volume of data. Cloud gives customers different storage layers. On AWS, active data can sit in Amazon RDS, data can be stored on Amazon S3, and archival data can be stored on Glacier, allowing optimisation of data storage costs.

Are partners evolving from implementers to co-owners of business outcomes?

Partners themselves are transforming. Earlier, many partners saw themselves as migration, modernisation or analytics specialists. Successful partners get AI Competency, work on customer projects, experiment through pilots and take selected use cases into production. They are also moving away from purely man-hour-based billing towards outcome-based models.

Is AWS making AI adoption easier, or creating new complexity for partners?

Earlier, the tech stack comprised hardware, an operating system, a database layer and an application layer. In AI, hardware is still important. That is where GPUs, AWS Trainium, Inferentia and our close partnership with NVIDIA come in.

The models are becoming the operating systems of the future. Customers can access and orchestrate models through Amazon Bedrock. They can use publicly available large models, AWS Nova models or SageMaker to build their own custom models.

On top of this comes the part of agents: they make AI real. We have AgentCore to build agents for enterprises. We also have an agent marketplace with over 3,000 agents listed. So, the architecture is changing: now it is hardware, models and agents.

Is AI becoming simpler for decision-makers, or are partners playing a bigger role?

We will always have different kinds of customers: start-ups and digital natives will adopt technology differently compared to banks, public sector organisations and healthcare companies.

Partners help customers think through pilot-to-production journeys, ROI metrics, when to revisit a project, whether token costs are becoming high and whether a particular model is the right one. Technology brings complexity, and that is where AWS and partners help.

How does AWS define an AI Competency partner? What are the criteria?

It is a publicly available programme. For AI Competency, a partner needs to have a certain number of people certified on AWS AI. They need to have executed customer projects, and customers must validate their ability to execute. If they are a technology partner with an ISV or SaaS solution, they should also have a programme to list their solutions on AWS Marketplace. These requirements are open; any partner who believes it can meet them can apply.

How important is marketplace-led commerce for partners in India?

AWS Marketplace is an umbrella platform that brings together technology consumers and sellers. The India marketplace capability ensures that an Indian customer and an Indian partner can transact in Indian currency and within Indian taxation laws, simplifying commerce.

What must partners do differently to succeed in the AI era?

Partners must continuously learn. At AWS, we have roles such as partner solution architects and partner training consultants who work specifically with partners, help them understand technology roadmaps and prepare for what is coming.

AI is a transformative technology, and partners must keep evolving. AWS is investing significantly in the GenAI Innovation Centre and AI Competency, enabling expertise in strategic partner offerings and technologies from Anthropic and OpenAI.

Who owns accountability in agentic AI: the customer, the partner or AWS?

Cloud has always operated on a shared responsibility model, and AI follows the same principle. Whenever customers are moving to the Cloud or AI for the first time, we ask them to clearly understand this.

AWS provides tools. The partner can bring everything together, but customers must weigh in on security and governance.

What is your priority for the next year?

My priority is to ensure that partners are ready for the upcoming transformation. Once partners are ready, hundreds of thousands of customers also become ready. It is the multiplier effect.