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Modern data collaboration promises to help organisations work together without repeatedly copying, moving or exposing sensitive information. But while the technology has advanced quickly, trust, commercial incentives and internal processes have not always kept pace.

In Episode 6 of The First Mile, Dom Burch speaks with Adrian Bolosan, Head of ISV GTM Strategy for Enterprise and Emerging Business in the Americas at Databricks.

Adrian explains how Databricks is expanding its focus beyond the core platform to the wider ecosystem of data providers, connected technologies and software companies building on Databricks. The ambition is to make “Databricks plus partner” a force multiplier for customers, helping them solve specific business problems without assembling everything themselves.

The conversation explores how OpenSharing and clean rooms allow organisations to collaborate without surrendering control of their underlying data. Adrian shares examples from identity resolution, supply-chain data and retail media, including one retailer and CPG collaboration that took almost a year to complete. The technology worked, but lengthy approvals, misaligned incentives and excessive aggregation left the resulting insights too diluted to be useful.

Dom and Adrian also discuss the less glamorous middle of data collaboration: legal agreements, procurement, security reviews, data engineering and seller incentives. In many cases, the biggest obstacle is no longer technical. It is persuading people and commercial models to move away from established ways of working.

The final part of the episode turns to AI. Adrian argues that organisations cannot jump straight to sophisticated agents without first addressing the quality, identity, consent and governance of their underlying data. They also discuss real agentic media-buying pilots between publishers and agency holding companies, where agents are already buying media, receiving signals and deciding what to do next.

In this episode

• What data collaboration means in practical terms
• Why zero-copy sharing is replacing legacy files, APIs and duplicated pipelines
• How clean rooms support identity resolution without exposing raw customer data
• Why a technically successful retail-media collaboration still failed to create value
• Where Databricks chooses to build and where it relies on specialist partners
• What Databricks looks for in a Built-On partner
• How commercial incentives can slow adoption of better technology
• Whether clean rooms reduce costs or create another cost centre
• Why AI adoption depends on reliable and governed source data
• How MCP servers are connecting agents to external data and tools
• What is already happening in agentic media buying
• How businesses should identify the right place to begin

Chapters

00:00 Introduction
02:01 Adrian’s expanded role and the Databricks partner ecosystem
03:16 What has changed in data collaboration
04:47 Identity resolution and zero-copy sharing
06:37 A retail-media collaboration that underdelivered
09:28 Why trust still comes first
10:09 Where Databricks stops building and partners begin
12:35 The Partner Well-Architected Framework
15:44 Legal, procurement and the boring middle
18:22 Who pays for data collaboration?
20:21 Why poor data undermines AI
23:13 MCP adoption and AI-ready data
24:03 Agentic media buying across company boundaries
26:18 Governing what agents can access and do
27:50 Adrian’s advice for getting started

About Adrian Bolosan

Adrian Bolosan leads ISV go-to-market strategy for Databricks’ Enterprise and Emerging Business across the Americas. His work spans data collaboration, partner adoption and the ecosystem of specialist companies that connect to or build their products on Databricks.

Before taking on his expanded role, Adrian helped develop Databricks’ go-to-market approach around data collaboration, including OpenSharing and clean rooms.

Find out more

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AI doesn’t start with algorithms. It starts with data flow.

In this episode of the First-Mile Podcast, we sit down with Patrick Harrington, Head of AI & Machine Learning at MetaRouter, to cut through the noise and talk about where real AI capability is actually being built.

Patrick explains why most AI systems today still operate like archaeology—analyzing the past instead of shaping outcomes in the moment—and why the real breakthrough happens in the first mile, where data is created, identity is resolved, and intent is revealed in real time.

We explore what it means to hold a privileged position in the data flow, why bot detection is fundamentally a data quality and behavior problem, and how AI becomes powerful only when learning compounds across use cases—not when it’s treated as a feature.

If you’re tired of AI hype and want a grounded conversation about real-time intelligence, server-side infrastructure, and how AI actually drives commercial outcomes, this episode is for yo

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Retail media is no longer a nice-to-have, it’s a core growth system. In this episode, Second-Gen Retail Media: It’s No Longer Just a Nice to Have, we sit down with Neerav Vyas, VP of Data & AI at Capgemini, to unpack how retail media is evolving from outsourced ad placements into owned, composable platforms that power real differentiation.

We start with outcomes. Retail media inventory only works when it serves the shopper—think native sponsored listings, contextual placements that reduce friction, and in-store screens that align with store flow and inventory reality. From there, we dive into identity as the backbone of second-gen retail media: privacy-first data collection, consent orchestration, and unknown-to-known stitching that keeps customer journeys intact as cookies disappear. Neerav shares practical tactics, from email-to-web continuity and cross-device linkage to why authentic personalization is the value exchange customers actually accept.

Measurement is what turns promise into belief. We break down how leading retailers connect exposure to sales lift, incrementality, and lifetime value across on-site, off-site, and in-store environments. We also explore how clean rooms and collaboration frameworks enable retailers and CPGs to prove performance without exposing raw data, plus emerging partnership models with streamers and publishers that unlock full-funnel visibility, smarter audience building, and higher CPMs.

Finally, we talk operating models and speed. Composable architectures allow teams to assemble best-of-breed identity, ad serving, and measurement in weeks—not years—while partners handle the undifferentiated heavy lifting. Alignment across ecommerce and store operations ensures retail media supports both the brand and the basket. If you’re heading to NRF, consider this your field guide to the conversations that matter now: own your data, choose your ambition, and prove value without breaking the customer experience.

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