Why Data Readiness for AI Is Becoming the Biggest Opportunity for Channel Partners
Artificial intelligence has become the dominant technology conversation across enterprises, yet many organisations continue to struggle with AI adoption despite significant investments. According to Andrew Fisher, AVP, Partners & Alliances, Asia Pacific & Japan, Everpure, the problem often has less to do with AI models and more to do with the readiness of the underlying data.
In a conversation with DQ Channels, Fisher outlined how Everpure's evolving Enterprise Data Cloud (EDC) vision is focused on helping organisations understand, manage and govern data more effectively. More importantly, he believes this shift is creating a substantial opportunity for channel partners to move beyond traditional infrastructure discussions and establish themselves as strategic advisors.
Data intelligence is becoming the foundation of AI readiness
Everpure's latest strategy revolves around three core pillars: Universal Data Intelligence, Unified Data Plane and Intelligent Control Plane. Together, these capabilities are designed to help organisations understand where their data resides, how it is classified, and how it should be governed across increasingly complex environments.
According to Fisher, enterprises today are dealing with fragmented data spread across multiple locations, making it difficult to assess whether that data is suitable for AI workloads.
"Universal Data Intelligence moves organisations from simply having data knowledge to achieving true data awareness. Before organisations can effectively deploy AI, they must understand whether their data is ready for AI workloads."
He explained that many organisations continue to approach AI implementation in the wrong sequence by focusing first on models and platforms instead of understanding the quality and governance of their data assets.
Why AI projects often fail before they begin
One of the strongest messages from Fisher was that data management and AI should not be viewed as separate challenges. Instead, he sees them as two parts of the same transformation journey.
He noted that enterprises frequently select AI technologies before establishing data governance frameworks, resulting in poor outcomes and delayed returns on investment.
"The challenge isn't whether AI or data management is more important. Both matter. The real question is sequence, and I believe data readiness must come first."
Fisher argued that organisations should begin with business strategy, data classification, governance policies and data location assessments before selecting AI platforms. Once those foundations are established, AI implementation becomes significantly easier and more predictable.
This approach also creates a natural advisory opportunity for channel partners who are willing to engage customers at the business level rather than beginning with infrastructure discussions.
Channel partners can build recurring revenue through AI readiness services
While many partners continue to view AI consulting as the primary monetisation opportunity, Fisher believes the market is much broader than that.
He sees growing demand for data-readiness assessments, governance consulting, compliance reviews and strategic advisory services. These engagements can help partners elevate conversations from technology procurement to long-term business outcomes.
"Consulting is certainly an important starting point, but the opportunity extends much further."
Once partners help customers assess data readiness, they can also advise on deployment architectures, storage strategies, security frameworks and operating models. This creates opportunities that extend well beyond initial implementation projects.
Because Everpure operates exclusively through channel partners, Fisher noted that long-term services, support engagements and customer relationships remain in the hands of partners.
He also suggested that future additions to the Universal Data Intelligence portfolio could create additional software, intelligence and consulting opportunities over time.
AI governance and cyber resilience are emerging growth areas
As enterprises move beyond experimentation and begin deploying AI at scale, governance and security concerns are becoming more prominent.
Fisher believes organisations increasingly require visibility into where their data resides, how it moves across environments and whether it remains compliant with evolving regulations.
The company's Intelligent Control Plane strategy addresses these concerns through automation, compliance monitoring, security oversight and governance capabilities that can operate across large-scale data environments.
"As agentic AI workflows become more prevalent, organisations will need greater visibility and control over where data resides, how it moves, and whether it remains secure and compliant."
For channel partners, this creates opportunities to extend existing security practices into AI governance, cyber resilience and compliance-focused services.
Rather than treating AI deployment as a standalone project, partners can position themselves as long-term advisors responsible for securing and governing AI environments.
The shift from reseller to trusted advisor is accelerating
Fisher believes the transition from product reseller to trusted advisor has been underway for years, but the emergence of data intelligence and AI governance presents a unique opportunity to accelerate that evolution.
The current market is characterised by strong customer demand and a limited pool of expertise, creating favourable conditions for partners that invest in specialised capabilities.
"Rather than beginning with infrastructure conversations, partners can start with business-level discussions around data governance, AI readiness, compliance and operational risk."
He stressed that partners do not need to abandon existing business models. Instead, they should gradually develop specialist teams capable of leading strategic engagements around data governance and AI preparedness.
This approach enables partners to create stronger differentiation while building deeper customer relationships based on business outcomes rather than product transactions.
Conclusion
The AI market may be moving rapidly, but Andrew Fisher's perspective suggests that successful AI adoption will depend less on choosing the right model and more on preparing the right data foundation. For channel partners, this shift represents a significant opportunity to move beyond infrastructure resale and build higher-value practices around data intelligence, governance, AI readiness and cyber resilience. As organisations continue to struggle with fragmented data environments, the partners that can help customers establish trust in their data may be best positioned to capture the next phase of AI-driven growth.
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