As AI moves deeper into the enterprise, questions around data, governance, infrastructure and sovereignty are becoming increasingly important. For companies, the challenge is not just deploying AI, but doing so securely and responsibly across complex technology environments. Charles Sansbury, CEO of Santa Clara, California-based enterprise data analytics firm Cloudera, discusses the next phase of AI adoption, the rise of agentic AI and India’s growing role as a market and R&D hub, in an interview with Sudhir Chowdhary. Excerpts:
The spotlight globally is on AI models, but enterprises often say their biggest challenge is getting their data in order. Has data become the real differentiator in enterprise AI?
There’s a lot of spotlight on AI models today, and rightly so. But in the longer term, I believe the real differentiator in enterprise AI will be data quality. What remains a key differentiator is how organisations deploy and use trusted data to power their AI applications and use proprietary data in a way that helps train and deliver output of AI workloads. The focus is extracting value without compromising control, particularly in regulated industries such as financial services, telecom, pharmaceuticals, and government. Enterprises need consistent governance and security across on-premises, private and public cloud environments. At Cloudera, we have invested approximately $1 billion in R&D over three years to build these capabilities, enabling private and sovereign AI while helping enterprises derive greater value from their data securely.
How does India fit into Cloudera’s global growth strategy over the next five years?
India is one of the most dynamic markets for data, analytics and AI, with digital-native companies such as PhonePe scaling rapidly and at the same time established enterprises modernising their data estates. This coupled with the market’s exceptional depth of technology talent and strong momentum around AI adoption, makes it strategically important.
For Cloudera, India is already one of our two or three fastest-growing geographies globally by revenue, and its strategic importance will continue to grow. We have four offices across Delhi, Mumbai, Bengaluru and Chennai, and our workforce has expanded from roughly 600 to nearly 1,000 in a year. We see India as both a strategic growth market and a critical R&D hub, with teams spanning product management, development and architecture.
What separates organisations that successfully scale AI from those stuck in pilots?
The companies achieving the greatest success with AI today are those that were thoughtful from the outset and invested in building a strong technology foundation. While speed to market is important, solutions that are not designed for the long term are unlikely to withstand changing business demands and evolving market dynamics. What sets AI leaders apart is their relentless focus on business outcomes. They invested early in trusted data, strong governance, and scalable foundations, enabling them to move AI from experimentation to enterprise-wide impact. Financial services is a good example. Automating initial reviews in areas such as know your customer (KYC) and anti-money laundering (AML) can significantly reduce operational workloads, allowing employees to focus on higher-value activities that require judgment and expertise.
How does Cloudera differentiate itself from hyperscalers and fast-moving AI enterprises?
We provide hugely scalable data and AI platforms with tools to help manage and deploy AI-based applications. We have strong credentials in building big data and analytics from the past 15 years and within the Cloudera framework we manage almost 30 exabytes of data for our global customer base, which is arguably one of the biggest, if not the biggest data repository stores. That gives us deep expertise in operating at scale, with the security and performance that enterprise customers demand. Our focus is on the world’s largest organisations, where hybrid architecture is increasingly becoming a strategic requirement.
Building AI software on an enterprise scale requires substantial investment, which is why many start-ups struggle despite the pace of innovation in the market. Our innovation is fundamentally forward-looking and customer-driven in providing enterprises with the flexibility, security, and scale they need today, with a data platform they can continue to use over the next five to 10 years as AI evolves.
What data infrastructure changes do financial services organisations need for agentic AI while maintaining trust, sovereignty, and compliance?
AI agents are becoming more autonomous, bringing trust, governance, and security into sharper focus alongside the pace of innovation. The challenge is ensuring these areas advance together.
That is especially true in sectors like financial services and healthcare companies, where data sovereignty, compliance, and risk management are non-negotiable. While the potential of agentic AI is significant, organisations need the right guardrails, observability, and governance frameworks before deploying autonomous systems at scale.
The leaders in this next phase of AI will be those that strike the right balance between innovation and control, giving businesses the ability to move faster while maintaining trust.
Will stricter AI, privacy, and data sovereignty regulations slow adoption or boost customer confidence?
The growing focus on AI governance reflects both the importance and increasing maturity of the technology. AI is evolving at an extraordinary pace, and regulatory frameworks are working to keep pace with its development. The opportunity now is to establish governance models that foster innovation while building trust.
AI cannot be governed by model providers alone, which is why industry-led collaboration has an important role to play in developing standards tailored to sectors such as financial services, telecommunications, and the public sector. Greater government involvement is inevitable and, when approached thoughtfully, can strengthen confidence, accountability, and adoption. The key is to strike the right balance by creating safeguards that build trust without constraining innovation or slowing the pace of progress.
What will distinguish the leaders in enterprise AI over the next three to five years?
Organisations that are creating real business value from AI are those that combine strong governance of their enterprise data with high-quality data management and operational excellence across the business. Our customer base in India closely reflects our global customer profile. For example, around three-quarters of India’s leading banks rely on Cloudera as their enterprise data platform and are extending its capabilities to support their AI initiatives. We also work with more than half of the country’s major telecommunications providers, as well as organisations such as PhonePe, leading trading exchanges, and government agencies.
Our role is to provide a trusted data foundation that enables these organisations to deploy AI securely, responsibly, and at scale.