Has your organization already bought the platform and still not felt it in the business? In this conversation, Persistent and Databricks explore why the distance between platform capability and business value is widening and what actually closes it.

When the Platform Is No Longer the Problem

For most enterprises, the platform decision has been made. The data estate is consolidating, the tooling is in place and the pilots came back interesting. What has not arrived at the same pace is the outcome. Leaders have stopped asking whether AI works and started asking why it is not scaling faster and the honest answer has little to do with model capability. The gap sits between what a platform can do and what the business actually receives and in many organizations that gap is widening rather than closing.

Featured Speakers

Josh Meyer, Global Head of Ecosystem, GTM Programs at Databricks, explains why the data foundation and the context built on top of it determine whether AI delivers enterprise value and why partners who invest in domain depth and delivery capability will be disproportionately rewarded as the market matures.

Devashish Mishra, Vice President, Solutions Consulting at Persistent, brings the practitioner’s lens to the conversation, centering his perspective on where value is actually landing across banking, life sciences, healthcare and retail: the document-heavy processes, regulatory workflows and reconciliation cycles where AI changes the economics of work.

A Platform Is Only as Valuable as the Business It Understands

The discussion challenges a comfortable assumption that enterprise AI maturity is a function of platform sophistication. The sharper truth is that intelligence stopped being a constraint a while ago. AI is already capable to handle most enterprise tasks. What it lacks is the institutional knowledge: the rules, the history, the processes and the relationships that make a generic answer into a usable one. Without that, a platform delivers capability. With it, a platform delivers decisions.

Six Shifts Explored:

  1. Context as the condition for value: Intelligence is plentiful and getting cheaper. What determines enterprise value is whether the data foundation organizes institutional knowledge in a form AI can actually use.
  2. Production discipline over prototype velocity: The fundamentals that decide whether anything reaches production have not changed in decades: organizational alignment from the top down, honest change management and use cases chosen to match the readiness of both the organization and its technology foundation. What has changed is the speed at which those decisions must be made.
  3. Governance as engineered trust: Trust is built, not declared. Alongside it sits the concern every enterprise leader now raises: retaining control of proprietary data and IP rather than prompting it away into third-party tools.
  4. Effectiveness as the ROI story: Value is landing in the document-heavy middle of the business. It is not primarily about reducing the number of people doing the work. It is about removing the manual overhead that slows them down.
  5. Fit-for-purpose intelligence as the cost moat: Organizations are balancing frontier models against open-source options and matching the model to the job rather than to the benchmark. The less-discussed piece is the database layer beneath agents, which need rapid access to data to act and which is becoming a significant and largely unplanned cost.
  6. Delivery depth as the partnership moat: The final shift is execution. Databricks brings the platform. Persistent brings the layer built around it, across migrate, modernize and transform. The value is not in replacing enterprise investments. It is in building the capability that makes them produce an outcome.

Join the conversation. Contact us at podcasts@persistent.com.

Speakers

Josh Meyer, Global Head of Ecosystem, GTM Programs at Databricks

Devashish Mishra, Vice President, Solutions Consulting at Persistent

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