AiThority Interview With Krish Venkataraman, President of Dataiku

Krish Venkataraman, President of Dataiku, highlights more on Traditional AI and GenAI, the process of AI transforming decision-making, ethical AI implementation, and the latest innovations at Dataiku in this catchup:

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Hi Krish, welcome to the AiThority’s interview series. Your career has spanned financial services, cybersecurity, and big data. What inspired your transition to AI and your leadership at Dataiku?

Almost all industries are driven by data. I spent much of my career working in finance, where data is a vital asset used to make critical decisions every day. The progress that was made back then with Big Data and technologies like Hadoop paved the way for the AI revolution we’re experiencing today. It was a natural evolution for me to work at one of the companies that’s not just participating in the AI revolution – but actually shaping the future of the sector. 

Also Read: AiThority Interview with Louis Landry, CTO of Teradata

Dataiku promotes the idea of making AI accessible to everyone in an organization. What cultural and structural shifts are needed for true AI democratization?

AI democratization requires a fundamental shift in how we approach data and intelligence within an organization.  Instead of keeping this knowledge siloed in data engineering teams, you need to empower the “boots on the ground” – the frontline workers who know your business best. By extending data access and AI tools to everybody, from data scientists to those who create the data, we unlock the true potential of AI. This has become possible because of platforms like Dataiku, which provide the security, governance and ease of use to democratize access to AI with low- and no-code tools. And at the same time, we further enable developers and data scientists with sophisticated full-code tools. So we truly strive to offer universal access to AI for every type of user across the enterprise.

Traditional AI and GenAI have distinct enterprise applications. Talk about how Dataiku integrates both into its platform.

Dataiku is uniquely designed to power traditional AI applications as well as Agentic and GenAI capabilities, providing an intuitive experience for users. By connecting to a wide variety of data sources, we allow organizations to embark on a comprehensive data journey. This journey starts with foundational data analytics, progresses to data science and traditional AI, and culminates in the advanced capabilities of GenAI and agentic AI. Our platform provides the tools and  governance for each stage, meeting users where they’re at according to their needs. In fact, our customers have the flexibility to start use cases at the user, team, or full enterprise-level – so they are unrestricted to where they want to start and how far they want to scale, This user-centric approach allows employees at all levels to explore and leverage the full spectrum of AI, maximizing its value for their organization.

We’d love to hear what you think about the process of AI transforming decision-making in industries like finance, healthcare, and manufacturing.

Industries like finance, healthcare, and manufacturing have always been fundamentally data-driven, making them ripe for transformation by AI. Medicine, for instance, relies on data from clinical research. Finance thrives on the rapid movement and analysis of information.  This inherent data-centricity gives these sectors a significant advantage. They already have the infrastructure, processes, and culture for analyzing data. Even in highly regulated environments, their experience with governance and compliance allows a rapid adoption of AI tools.

AI bias is a major challenge. How should organizations ensure ethical AI implementation, and what role does Dataiku play in this space?

Addressing AI bias and ensuring ethical implementation is critical. To achieve this, organizations need to ensure they have rock-solid governance and compliance while still enabling rapid experimentation and development. Dataiku enables this with tools like LLM Mesh, which provides a secure gateway to a wide variety of AI models and tools. This level of optionality is rare among platforms, but ensures that enterprises can avoid vendor lock-in and always choose the technology that is best aligned with their use case and its performance. Not all LLMs are best for each type of use case, and that includes their relation to bias in outputs. Ultimately, with Dataiku, employees are able to access AI data and tools while the platform automatically ensures that your compliance and privacy policies are adhered to. 

What’s next for Dataiku? Any exciting developments or innovations in the pipeline that you would like to share with our readers? 

Our customers are excited to explore and advance their use of AI agents. Naturally, for the enterprise, this comes with some serious need for control and governance. We have the advantage of a robust, existing governance framework, so as we move forward, we are extending the capabilities of the platform to not only empower customers to build and deploy multi-agent solutions but also to predictably and confidently manage them. We have some exciting announcements in the coming months, and will showcase some new solutions and share some amazing customer stories at our Everyday AI Conference in April, which is our North American Summit, that we will also stream virtually for the first time. 

Also Read: From Time-Saving to Decision-Making: What’s Generative AI’s Next Leap for 2025?

Before we close, would you like to share any books or podcasts that have influenced your thinking on AI, leadership, or business strategy?

I’m a big fan of The MAD podcast from Matt Turck, which always has great advice for entrepreneurs and early-stage investors. I’ve also enjoyed the “Mastering AI” book by Fortune Magazine editor Jeremy Kahn, which takes a clear-eyed look at how AI will impact business and society in the years ahead.

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