{"slug": "the-agentic-marketing-stack-starts-with-the-data-layer", "title": "The agentic marketing stack starts with the data layer", "summary": "Acxiom Chief Cloud and Data Modernization Officer Ankur Jain argues that organizations must modernize their data infrastructure before building agentic AI, warning that legacy systems create immediate scalability and performance ceilings. Acxiom's migration from on-premises Hadoop to Databricks improved workload run times by 80-90%, freeing engineering teams to focus on product development rather than infrastructure management.", "body_md": "Why modernizing the data foundation is a critical first step in any AI strategy\n\nby [Aly McGue](/blog/author/aly-mcgue)\n\nThere's a version of the AI modernization story that goes: build the platform, then figure out the use cases. Ankur Jain would tell you that's backwards — and that most organizations are learning that the hard way.\n\nAnkur is Chief Cloud and Data Modernization Officer at Acxiom, the connected data and technology foundation that helps global brands resolve customer identity across channels, enrich customer profiles with more than 10,000 attributes, and deliver outcomes across customer acquisition, retention and personalization.\n\nAnkur leads both product engineering and client-facing solutions engineering — meaning he is responsible not just for what Acxiom builds, but for how those capabilities get embedded inside the environments where clients actually operate.\n\nAfter joining the company less than two years ago, Ankur led the modernization of Acxiom’s core infrastructure, data pipelines, legacy architecture and underlying tech-stack. Today, Acxiom is actively building agentic workflows that automate the full marketing value chain.\n\n**Aly McGue:** A lot of organizations want to move to agentic AI but are still running core workloads on legacy infrastructure. What is the risk of trying to build intelligence on top of a foundation that wasn't designed for it?\n\n**Ankur Jain:** The risk is that you hit a ceiling almost immediately. When I joined Acxiom, both products and client solutions were hosted mostly on-premises. When your products and solutions are constrained to a data center, they have limited scalability. Performance was not up to par for the real-time use cases clients were asking for. And then there was a lot of legacy tech — the stack needed a refresh, a reimagining of what cloud-native architecture could look like.\n\nWhat we also saw was a lot of manual pipelines, a lot of data redundancy, copies of the same data in multiple places. The process itself was not very efficient. Any organization trying to build agentic capabilities on a fragmented or legacy foundation is going to spend more time managing infrastructure than building products.\n\nFor us, the strategic vision comes down to two north stars: data modernization and agentic marketing. They are sequential, not parallel. You cannot build an agentic marketing ecosystem on a legacy foundation.\n\n**Aly:** You moved from on-premises Hadoop to Databricks. What did that shift make possible that wasn't possible before?\n\n**Ankur:** In terms of performance, we have seen improvement across the board, across different types of workloads and different types of pipelines, almost 80 to 90 percent faster run times. Workloads that used to take 50+ hours, sometimes 90+ hours — and I'm talking hours, so literally days, sometimes up to a week — are now getting done within 2-3 hours. Those same workloads, in 2-3 hours.\n\nIt has also freed up our people. In some cases we have been able to free up multiple full-time roles to focus more on value-added outcomes rather than managing infrastructure. The number one thing it enabled was for the engineering team to focus more on business outcomes rather than worrying about the infrastructure underneath. That might sound like a soft win, but when your engineers are spending their time building products and delivering client solutions rather than keeping the lights on, it changes what you can even attempt.\n\n**Aly:** Where are you seeing agentic AI reshape actual marketing workflows today, and where does that vision extend?\n\n**Ankur:** Acxiom's core operation is very data-centric. We bring in marketing data from multiple platforms — CRM, e-commerce, Adobe Analytics, Google Analytics — and help brands build a holistic customer view, enrich it, and deliver outcomes. Traditionally, that required a team of data engineers and data architects who would model everything and build pipelines manually. ETL is always the longest pole in the tent, and it would take months.\n\nThrough AI, that entire cycle compresses. Code generation through prompts, automated testing of outputs, accelerated CI/CD pipelines. On the marketing side, producing different variations of an ad used to take creative agencies months. Now you can analyze ads at scale through machine learning, feed those results into an AI engine and generate highly customized variations in minutes.\n\nWhere we have seen the biggest real shift is on execution. Take audience planning — a marketer passes a prompt describing a campaign objective and target profile, and the agent builds the audience segments with sample personas using Acxiom data, surfaces different demographic and behavioral dimensions and lets the marketer refine from there. What used to take effort from multiple people with varied skill sets and a lot of lead time is now done agentically in minutes. We have demonstrated the same pattern for media buying: an agent queries available inventory, evaluates it, makes a buying decision and activates the audiences across channels.\n\nThe goal is to connect the entire pipeline — from audience design through media buying, activation and performance analytics — into an agentic framework. That whole AI for BI capability that Databricks is building through the Genie and agentic ecosystem is exactly where marketing workloads like ours are heading. It can all be put to work end-to-end.\n\n**Aly:** Acxiom operates in highly regulated industries, and deploying agents requires a high level of trust. How does that shape the way you design governance into agentic workflows?\n\n**Ankur:** The data we handle spans PII, so every agentic workflow we build starts with privacy as an architectural principle.\n\nIn practice, that means AI-generated content never goes directly into a live campaign. It routes through an approval workflow where legal reviews creative and messaging before anything reaches a customer. The agents operate within defined boundaries, with security and privacy controls baked into the pipeline, and humans stay in the loop at every decision point that carries regulatory or brand risk. The goal is not to slow things down. It is to make sure speed does not come at the cost of trust — for the customer, the brand or Acxiom.\n\n**Aly:** What does it mean for Acxiom's products to be AI-native, and how does that change what clients actually experience?\n\n**Ankur:** AI-native means intelligence is embedded across the entire marketing value chain: ingesting first-party data, resolving customer identity, enriching profiles with Acxiom's data assets, building audience segments, planning media buys, activating campaigns across channels and feeding performance analytics back into the next cycle. Each of those steps can now be AI-driven rather than manually orchestrated.\n\nFor clients, the biggest change is transparency. Traditionally, a lot of what we provided operated as a black box. Brands sent data in, outcomes came back, and the logic in between was opaque. Now those same capabilities can be delivered collaboratively, inside the platforms clients already use, with full visibility into how decisions are being made. That is what clients are asking for: meet them where they are, operate in their environment and make the process transparent.\n\nAnd it is a forcing function that comes not only from within the organization, but from our clients directly. They are asking us: how can you make it more cost-effective? How can you make it more performant? How can you make it faster? If you want to answer those questions honestly, you have to bring in AI.\n\n**Aly:** Your data assets are core to what Acxiom sells. How is the way you deliver that data to clients evolving, and what does that unlock?\n\n**Ankur:** Acxiom helps clients make the most of their customer data. We help them put it to work and monetize it. We provide data assets that brands otherwise would not have, across automotive, retail, healthcare and pharmaceutical. Historically, delivering that data was through traditional means — through SFTP. A brand would request enrichment, we would enter into a contract and send the files. That was the old way.\n\nNow we are embedding our data in an agentic fashion, either in our own platforms or directly in the client's environment. We partner with leading martech platforms where our data assets are natively available. If a client is building their own AI platform, we can integrate agentically so they can make a call to our assets and serve them up directly. We are also developing clean room solutions in partnership with Databricks, where clients can integrate with Acxiom data in a privacy-safe manner within their own ecosystem.\n\nThe brands we work with understand that first-party data is their most valuable asset. Data privacy plays a very important role while handling and processing this data. Brands want to exercise greater control and are constantly in-housing the marketing capabilities. The expectation is shifting for agencies to work inside brands’ platforms and governance frameworks. The agencies that can operate and deliver outcomes natively into that environment will be indispensable.\n\n**Aly:** If you were speaking to a C-suite peer just beginning to scale their AI efforts, what's the one thing you'd want them to hear?\n\n**Ankur:** Make sure the foundation is solid. There is a lot of AI buzz, which isn't a buzz anymore; it's reality. But what makes or breaks the whole AI initiative is the foundation that it needs to sit on. In our case, moving from on-premises to the cloud was not only an ambition. Keeping the future in mind made it a necessity so that we could be a real player in the AI journey. Solid data foundation, cloud-native architecture, data governance and security — those are the key ingredients. Any organization that skips that step is going to find out eventually that it wasn't optional.\n\nThe pattern at Acxiom is a useful frame for any executive evaluating where to put their energy. Modernizing the foundation and pursuing agentic AI aren't two separate programs competing for budget and attention. They are the same bet, made in sequence. Get the data layer right, prove value through focused pilots, then embed your differentiated capabilities where clients actually need them.\n\nThe shift Ankur describes — from delivering data through file transfers to embedding intelligence natively inside client environments — isn't just an architectural upgrade. It changes what kind of company Acxiom is. That kind of repositioning doesn't happen by bolting AI onto an on-premises stack. It requires the foundation to come first.\n\nExplore how over 25 industry experts and 1,200+ leadership-level survey respondents are paving the way for successful AI deployment by[ ](https://www.databricks.com/resources/analyst-research/making-ai-deliver)[accessing the \"Making AI Deliver\" report](https://www.databricks.com/resources/analyst-research/making-ai-deliver) from Economist Enterprise, created in partnership with Databricks.\n\nSubscribe to our blog and get the latest posts delivered to your inbox.", "url": "https://wpnews.pro/news/the-agentic-marketing-stack-starts-with-the-data-layer", "canonical_source": "https://www.databricks.com/blog/agentic-marketing-stack-starts-data-layer", "published_at": "2026-07-10 19:00:00+00:00", "updated_at": "2026-07-10 19:11:04.391754+00:00", "lang": "en", "topics": ["ai-infrastructure", "ai-agents"], "entities": ["Acxiom", "Ankur Jain", "Databricks", "Aly McGue"], "alternates": {"html": "https://wpnews.pro/news/the-agentic-marketing-stack-starts-with-the-data-layer", "markdown": "https://wpnews.pro/news/the-agentic-marketing-stack-starts-with-the-data-layer.md", "text": "https://wpnews.pro/news/the-agentic-marketing-stack-starts-with-the-data-layer.txt", "jsonld": "https://wpnews.pro/news/the-agentic-marketing-stack-starts-with-the-data-layer.jsonld"}}