The Ravit Show

Everyone wants better AI models. A few days back at Data Citizens on the Road by Collibra, I sat down with Reece Griffiths, Field CTO at Collibra on The Ravit Show, to discuss one of the biggest challenges facing enterprise AI today: unstructured data.

For years, data governance focused primarily on structured data.

But AI is changing the game.

Today, enterprise knowledge lives across PDFs, presentations, images, documents, emails, and shared drives. If that content isn't properly governed, AI systems can quickly run into problems:

* Generating answers from outdated or draft documents

* Exposing sensitive information due to missing confidentiality labels

* Missing relevant content because of poor metadata and classification

One concept from our discussion really stood out:

Knowledge decay.

Even the most advanced AI models will struggle if the underlying knowledge base is stale, incomplete, or poorly maintained.

We also discussed why enterprises are moving toward unified semantic models that connect structured and unstructured data, allowing AI systems to understand business context consistently across the organization.

The takeaway?

The future of enterprise AI won't be determined solely by model performance.

It will be determined by the quality, freshness, and governance of the data behind it.

#Data #DataCitizens #Collibra #AI #GenerativeAI #DataGovernance #AIGovernance #EnterpriseAI #Metadata #DataManagement #TheRavitShow

What if the biggest obstacle to AI success isn't the technology? It's the way organizations are structured. At Data Citizens on the Road by Collibra, I sat down with Joyce Snelders Senior Manager at Deloitte on The Ravit Show to discuss what organizations are experiencing as they move from AI experimentation to enterprise-wide adoption.

A few key takeaways from our conversation:

* Data governance has gone from a "nice to have" to a business priority because AI is only as good as the data behind it.

* Many organizations are building AI agents without common standards, creating duplicate efforts and inconsistent outcomes across teams.

* Chief Data Officers are increasingly becoming AI leaders, taking responsibility for both data and AI strategies.

* The next phase of enterprise AI is not just about technology. It is about governance, operating models, and change management.

* Leaders should start preparing for a future where digital FTEs work alongside human employees.

One statement from Joyce stood out:

Organizations don't have an AI problem. They have a governance and operating model problem.

The companies that solve that challenge first will be the ones that scale AI successfully.

#DataCitizens #Collibra #AI #DataGovernance #AIGovernance #EnterpriseAI #DataLeadership #TheRavitShow

Everyone is talking about AI governance. Almost nobody is talking about the part that actually decides whether it works. I had a blast chatting with Gaurav Bhandari, AVP and Head of Data and Analytics consulting at Infosys, on The Ravit Show at Data Citizens on the Road by Collibra. One line stuck with me. Roughly 80% of AI governance is just governing the data that feeds your models. We have been here before. Data governance started as a compliance and privacy problem in regulated industries. Then data became the asset everyone wanted to mine for value. Now AI has raised the stakes again, because a model is only as good as the context behind it.

Gaurav broke that context down into five things every enterprise has to get right:

- Trust. Can you rely on the output.

- Ethics. Even when you trust it, is it the right answer to put in front of people.

- Regulations. Are you staying compliant as the rules keep shifting.

- Privacy. Do people still control their own data.

- Security. Is everything safe once it sits inside your workflow.

Miss one of these and your AI agents are running on shaky ground.

What stood out to me was how the Infosys and Collibra partnership fits this moment. Ten plus years working together, and not just in finance. Retail, manufacturing, life sciences too. Collibra brings the platform. Infosys weaves the policies, controls, and structure into one governance story instead of a pile of disconnected tools.

His advice for the next 12 months was refreshingly simple. Stop thinking about data governance. Start building data plus AI governance.

The companies that treat these as one problem will move faster than the ones still treating them as two.

Full interview is live now.

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#data #ai #collibra #governance #infosys #api #datacitizen #theravitshow

Most enterprise conversations around AI start with models, copilots, and agents. This conversation started somewhere else: the data foundation. Last week at Informatica World, I had the opportunity to sit down with Martí Ganduxé Pregona from Schneider Electric and Emilio Valdés from Informatica to discuss what it really takes for enterprises to move from AI experimentation to AI at scale on The Ravit Show!!!!

One theme came up repeatedly throughout our discussion:

AI is only as good as the data behind it.

We explored how the combination of Informatica and Salesforce is expanding the role of data management beyond traditional integration and governance into areas such as agent governance, workflows, and APIs.

We also talked about one of the most talked-about announcements from the event: Informatica Headless.

The idea is simple but powerful. As enterprises deploy more AI agents, they need a trusted layer that ensures those agents are working with accurate, governed, and compliant data.

A few insights from the conversation:

* Why trusted data is becoming the foundation of every AI strategy

* How enterprises are preparing for an agent-driven future

* Why data governance is becoming more important, not less, in the age of AI

* The growing need to balance innovation speed with compliance and security requirements

* What enterprise leaders are learning from one another as they navigate AI transformation

One thing was clear: the future isn't just about building smarter AI.

It's about building an organization that can trust the outputs AI produces.

The full interview is below.

#data #ai #InformaticaWorld #theravitshow

One of the most interesting conversations I had at Informatica World was with Theodora Bakker, Vice President of Data at Hearst, and Gaurav Pathak, SVP & GM Product Management, DGP and AI at Informatica/Salesforce on The Ravit Show.What stood out to me was how practical this discussion was.We talked about why enterprise leaders continue to bring Informatica IDMC into multiple organizations across industries, what actually makes a company “AI-ready” versus truly “AI-leading,” and how the new Headless announcements could change the way teams think about modern data architectures.Theodora shared a strong perspective from the customer side, especially around scaling data foundations across very different environments. Gaurav also broke down how Informatica is thinking about the next phase of AI and enterprise data management.A few key themes from the conversation:* Why strong data foundations still decide whether AI initiatives succeed or fail* The difference between experimenting with AI and operationalizing it at scale* How enterprises are thinking about flexibility, governance, and modernization with Headless capabilities* What enterprise leaders should prioritize right now to move from AI-ready to AI-leadingIf you’re working in data, AI, analytics, governance, or enterprise architecture, this is a conversation worth watching.#data #ai #InformaticaWorld #theravitshow

Breaking right from Informatica World 2026!!!! Rahul Auradkar, President & GM, Data & Context | AI Foundations,, Salesforce just came off the keynote stage and joined me on The Ravit Show to break down everything that was announced today around:

- Headless Data Management

- Trusted enterprise context for AI

- Agentic AI workflows

- Multi-cloud interoperability

- The future of enterprise data architecture

One thing that stood out from our conversation:

Enterprise AI is no longer just about building models.

It is now about building trusted systems that AI agents can actually operate on.

We also discussed why metadata, governance, and interoperability are becoming the foundation for the next generation of AI systems across enterprises.

A lot of important insights in this one.

#data #ai #InformaticaWorld #theravitshow

Are dashboards becoming irrelevant in the age of Agentic AI? I recently sat down with Clarence Rozario from Zoho on The Ravit Show for an in-depth conversation on one of the biggest shifts happening in Data & AI right now: Agentic Analytics!!!!For years, business intelligence has focused on helping people understand what happened. Now we're entering a new era where analytics can help recommend actions, support decisions, and even automate parts of business workflows.In this conversation, we explored:* How BI has evolved from reporting and dashboards to Agentic Analytics* Why enterprises are shifting from insights to outcomes* Whether dashboards still have a role in the AI era* How Agentic AI is changing decision-making inside organizations* Why Context Engineering may become one of the most important capabilities for enterprise AI* The growing importance of semantic layers, business context, and trusted data foundations* Why Data & Analytics platforms must evolve to support agentic systemsOne theme stood out throughout our discussion:AI is only as good as the context and data foundation behind it. Without the trusted business context, even the smartest agents will struggle to deliver reliable decisions.What role do you think dashboards will play in a world increasingly driven by AI agents?#data #ai #agentic #ai #dashboards #api #semanticlayer #theravitshow

Some conversations stay with you because there is no hype in them, just real answers. That is how my interview on The Ravit Show with Thomas Benjamin, SVP of Product Development and Engineering at Boomi, felt at Boomi World 2026.

Thomas was clear about why most companies cannot get past their first pilot. They treat scaling as a model problem, when the real issue is everything underneath. The data. The context. The way agents are governed. That is where pilots quietly fall apart.

We also talked about what agentic context actually means inside a real enterprise. Thomas explained it in a way that made it obvious why putting AI on top of messy data will keep giving you unreliable answers, no matter how strong the model is.

The part I keep thinking about was on partnerships. No single company owns the full stack today. Thomas was honest about what makes a partnership real versus what makes it just a logo on a slide. That difference matters more than most people admit.

My takeaway. The winners in this next phase will not be the ones with the flashiest agents. They will be the ones who took the time to get the boring layers right.

#data #ai #BoomiWorld #theravitshow #BoomiAmbassador

I learn the most from people who can explain hard things simply, and my conversation on The Ravit Show with Patricia Moore, AI Field CTO at Boomi, was one of those at Boomi World 2026.

Patricia was direct about why so many AI agent pilots stall. Most teams rush to deployment before doing the work on context, data readiness, and governance. That is the gap between the enterprises getting real value and the ones still running experiments.

We spent real time on context engineering. Everyone uses the phrase, but very few can explain it. Patricia made it obvious why context is not just another feature. It is what decides whether an agent can be trusted inside a real business. The same thinking applies to hallucinations. The fix is not bigger models. It is better grounding, cleaner data, and tighter checks around the agent.

The part I enjoyed most was her view on the shift happening inside enterprises moving from experiments to real outcomes. The leaders getting it right are not chasing AI for the sake of AI. They are tying every initiative to outcomes that actually matter.

My takeaway. The companies winning with agents are treating context, governance, and outcomes as the real product. The model is just one part of the story.

#data #ai #BoomiWorld #theravitshow #BoomiAmbassador

At Boomi World 2026, I spoke with the amazing Nicole Bradley from Amazon Web Services (AWS) for a conversation on The Ravit Show, and it kept coming back to one idea. Most enterprises are not failing at agentic AI because of the models. They are failing because they are trying to stand up data management and agents without the right partnership underneath!!!!

Nicole walked me through the patterns AWS is seeing across customers right now, why Boomi became the partner that made sense, and the use cases where this combination is genuinely hard to beat. We also talked about the roadmap for the next 12 months, and there is a lot coming that customers should be paying attention to.

The line that stuck with me. Customers do not need more tools. They need fewer broken seams between them.

#data #ai #BoomiWorld #theravitshow #BoomiAmbassador