Podcast: Tech Transformed

Guest: Mihir Nanavati, GM and Product Executive in MarTech and AdTech

Host: Doug Laney, Research & Advisory Fellow at BARC and Author of Infonomics & Data Juice

AI might have overtaken the industry with processing data, automating workflows, and creating content. The next big thing could be a major one, says Mihir Nanavati, GM and Product Executive in MarTech and AdTech, “AI is moving from managing data to making decisions with it.”

In the recent episode of the Tech Transformed podcast, host Doug Laney, Research & Advisory Fellow at BARC and Author of Infonomics & Data Juice, sat down with Nanavati to talk about a larger transformation in data and decision-making systems driven by AI.

They particularly focus on the integration of agentic AI in marketing and customer data platforms. They explore the challenges of fragmentation in ad tech, the importance of connecting customer data to revenue outcomes, and the transformative role of AI in decision-making processes. Mihir shares insights on how companies can leverage AI to enhance their marketing strategies and the future of first-party data.

"This is not a cost exercise, it’s about how much more you can get done and how many more ideas you can execute," said Nanavati.

For years, enterprises went through waves of technological change, including cloud infrastructure, mobile platforms, and customer data platforms (CDPs). Each development helped enterprises collect, store, and manage larger amounts of data. However, Nanavati asserts that humans making most decisions will never change. Now, AI agents are introducing a new model.

How AI has Moved from Data Navigation to Making Decisions

In the past, customer data initiatives aimed to create a unified view of customers. Enterprises built warehouses, ETL pipelines, and data platforms that were designed to be reliable. 

However, Nanavati suggests that AI agents are changing these expectations. "Machines can reason, and that is fundamentally different."

Rather than simply serving as another analytical feature in existing systems, AI agents are increasingly acting as decision-makers. They weigh trade-offs, learn from results, and execute plans based on specific goals.

This change has significant implications for customer data platforms. CDPs are not just repositories for customer information now. Instead, they are becoming layers that enable intelligent actions.

"The role of customer data platforms is evolving into ‘how do you make meaning of this?’" While, decisions about which customer segment to target, which message to send, or which offer to present may increasingly be guided by AI-driven systems.

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What’s the Fragmentation Problem in Modern AdTech

While AI agents create new opportunities, Nanavati pointed out a persistent issue in the AdTech and MarTech ecosystem – fragmentation. Brands today tend to lean towards deploying multiple advertising and customer engagement platforms. These include social platforms, retail media networks, email tools, and specialised ad technologies. Each system may optimise effectively within its own space, but often fails to connect at the customer level.

Nanavati calls it a "paradox of choice." "Each system is optimising locally for its own clicks and conversions, but none of that is coordinated at the consumer level."

The result is a customer experience that many consumers notice, alluding to repeated retargeting for products they have already bought, irrelevant recommendations, or disconnected interactions across channels.

As enterprises adopt AI agents, fragmented data environments may become an even bigger problem. AI systems can process information quickly, but they still rely heavily on context. "AI doesn't need perfect data in many cases, but it needs context."

What’s Next for Enterprise Tech?

As AI adoption continues, Nanavati believes that successful enterprises will be recognised not by how many experiments they run, but by how fast they learn and use the results.

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"Learn very rapidly. Then scale what you've learned." For leaders, this may require a stronger commitment than just isolated pilot programs or limited rollouts. It may also need organisational changes that place AI decision-making and customer context at the centre of growth strategies.

For companies navigating the intersection of AI agents, CDPs, and customer data, the question may no longer be whether AI can automate processes. The ultimate question is about who is calling the shots.

Key Takeaways

  • AI is fundamentally changing how decisions are made in marketing.
  • The shift from third-party to first-party data is crucial for businesses.
  • Fragmentation in ad tech leads to a paradox of choice for brands.
  • Connecting customer data to revenue outcomes is essential for success.
  • AI can help marketers make better decisions without needing perfect data.
  • Customer data platforms are evolving to support real-time decision-making.
  • Companies can run significantly more marketing experiments with AI.
  • Leaders must personally drive change in their Enterprises.
  • Successful AI implementation requires a focus on revenue outcomes.
  • First-party data collection is becoming more sophisticated and essential.

Chapters

00:00 Navigating the Shift in Data and AI

03:03 The Evolution of Decision-Making in Marketing

05:55 Challenges of Fragmentation in Ad Tech

09:00 Connecting Customer Data to Revenue Outcomes

11:56 The Role of AI in Customer Data Platforms

14:55 Real-World Applications of Agentic AI

18:05 Blueconic's Approach to Customer Growth

21:14 The Future of First-Party Data

24:02 Building Habits for Successful AI Implementation

Listen to the full episode of Tech Transformed for a deeper discussion on AI agents, customer data platforms (CDPs), first-party data strategies and the future of AdTech. Subscribe for upcoming episodes and join the conversation across our social channels.

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