MongoDB Partners in the AI Era: driving enterprise AI execution

As enterprises across the world race tooperationalise artificial intelligence, the gap between experimentation and real-world impact is becoming increasingly visible. While AI pilots and proofs of concept continue to multiply, scaling them into production remains a challenge. At the centre of this shift lies enterprise data, how it is stored, modernised, governed, and ultimately made AI-ready. For MongoDB, this evolution has fundamentally reshaped not only its modern data platform strategy, but also the role of its global and APAC partner ecosystem.

In an in-depth conversation with Olivier Zieleniecki, Global VP Worldwide Partners, MongoDB, and Bidhan Roy, VP of Partners, APAC, a clear narrative emerges: partners are no longer execution arms or transactional resellers. They are now central to helping enterprises move AI from proof-of-concept to production, driving measurable outcomes through data modernisation and AI execution at scale.

A decade of evolution: MongoDB’s partner strategy comes of age

Having spent nearly a decade at MongoDB, Olivier Zieleniecki has witnessed the company’s journey from a developer-friendly document database to what he describes as an AI-driven modern data platform purpose-built for enterprise workloads.

“We started as a document data model because relational databases had clear limitations,” he said. “Today, we’ve evolved into a platform that consolidates multiple workloads, removes complexity, and helps customers innovate faster than ever.”

That platform evolution has directly influenced MongoDB’s partner strategy. With thousands of partners globally, ranging from boutique specialists and regional system integrators to global SIs and hyperscalers, the focus has shifted from scale alone to precision, specialisation, and relevance.

“Our focus now is to sit at the table with the right partners for the right use cases, in the right industries, and in the right geographies,” Zieleniecki said.

Why AI projects are stalling and where partners step in

Across regions, a recurring pattern is emerging: AI initiatives struggle to move beyond pilots. According to Bidhan Roy, the issue is not the AI models themselves, but data readiness and execution complexity.

“There is a sense of fatigue around AI POCs not moving fast enough,” Roy said. “What’s holding customers back is data stuck in legacy systems and the inability to reduce technical debt quickly.”

Rather than forcing enterprises to wait for full-scale modernisation, MongoDB is enabling partners to help customers run legacy modernisation and AI initiatives in parallel. This approach allows organisations to unlock value from existing data while gradually transitioning away from decades-old relational architectures.

“We cannot expect all customers to be at the same maturity level,” Roy explained. “So we are moving from partner ecosystem expansion to partner specialisation.”

From certifications to centres of excellence

A consistent theme throughout the discussion was the shift from surface-level enablement to deep capability building. MongoDB has invested heavily in empowering partners beyond certifications, with a strong focus on delivery readiness and operational scale.

“We have tens of thousands of developers, architects, and delivery professionals trained on MongoDB,” Zieleniecki said. “But more importantly, we are helping partners build real centres of excellence that can deliver AI and modernisation outcomes at enterprise scale.”

This includes close collaboration with boutique system integrators that bring niche expertise, as well as long-term investments in partner-led delivery capabilities across industries and regions.

India: Complexity at scale, innovation at speed

Both leaders emphasised that India represents one of the most complex and high-potential markets for AI-driven enterprise transformation. The challenge is not just technical depth—but depth at scale.

“In India, it’s not about solving for 20 customers,” Roy said. “It’s about solving for 20,000 customers, while innovation is happening at the same pace.”

Indian partners are increasingly choosing depth over breadth, focusing on specialised AI and data use cases in sectors such as banking, fintech, and public sector modernisation. MongoDB’s role, Roy noted, is to provide a unified data platform that removes infrastructure complexity, enabling partners to focus on customisation and business outcomes.

Sustainability through focused partnerships

Rather than spreading resources thin, MongoDB is taking a deliberately focused approach to partner engagement, particularly across APAC and India. The strategy centres on deep co-investment, aligned go-to-market execution, and long-term customer success.

“We’re moving away from deal-by-deal knife fights,” Zieleniecki said. “Instead, we’re building repeatable processes that scale over time and drive customer loyalty.”

This model is designed to be mutually reinforcing. Partners invest in MongoDB expertise and delivery depth, while MongoDB commits dedicated teams, enablement, and strategic alignment to ensure sustainable growth.

What will define high-impact MongoDB partners in the AI era

Looking ahead to the next 18–24 months, MongoDB believes the most successful partners will differentiate themselves through mindset as much as skillset. According to Zieleniecki, the priorities are clear: AI-ready architecture design, governance, performance at scale, and repeatable industry solutions.

Roy reinforced this from an India-specific lens. “The partners who will succeed are the ones willing to go deep, not wide,” he said. “This is not a commodity market. The depth of technology required is extremely high.”

Conclusion: Partners as force multipliers in enterprise AI transformation

As MongoDB positions itself at the intersection of data modernisation and AI execution, its partner ecosystem has become a strategic force multiplier rather than a support function. In markets like India, where scale, speed, and complexity converge, the company’s success will increasingly depend on how effectively partners translate platform capabilities into real-world, production-grade AI outcomes.

“India is a central pillar of MongoDB’s growth strategy,” Zieleniecki said. “And partners will be the catalyst that helps customers move from legacy constraints to AI-driven innovation.”

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