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As cyber threats become more sophisticated and AI reshapes both attack and defence strategies, enterprises are moving beyond standalone security tools towards integrated resilience platforms. For US-based cybersecurity firm N-able, that shift is being driven by AI-native architectures and globally distributed engineering talent. In conversation with The GCC Hub, Mike Adler, Chief Technology and Chief Product Officer at N-able, discusses how India’s GCCs are emerging as key centres for AI, cybersecurity and cloud engineering, helping accelerate innovation while strengthening cyber resilience. 

Edited excerpts 

With changing business dynamics globally and evolving cyberthreats, what is most critical has moved from describing itself as a UEM/RMM vendor to an AI-native cyber resilience platform. From a product architecture standpoint, what did that transition actually require and where does ResilienceAI sit in the stack today versus where you want it in 18 months?

Instead of treating endpoint management, security operations and data protection as separate layers, we unified them into one AI-native platform. ResilienceAI is the intelligence layer across it: not a standalone product, but the connective tissue that analyses events, prioritises what matters and drives automated response and recovery in real time.

That required a data-centric model where signals from endpoints, identities and backups are continuously correlated and acted on through one workflow, rather than handed between tools. Looking ahead, we’ll continue deepening that integration, moving from AI-assisted workflows toward more autonomous, agentic capabilities across the full lifecycle – with humans still firmly in control.

The combined Chief Technology and Chief Product Officer role remains relatively uncommon. How do you balance the demands of the product roadmap with technology architecture, shaped by engineering requirements? What challenges arise when these functions operate separately?

A combined CTPO model aligns product strategy, architecture and engineering around one goal: resilient security capabilities that work at scale. In cybersecurity, especially with AI, architecture defines what’s possible, while product direction ensures it solves real customer problems. Separating these functions can lead to fragmented tools, disconnected workflows and limited impact.

That’s why we design the platform and roadmap together, compounding capabilities across endpoint, security and data protection to deliver resilience as a system, not just a set of tools.

With the recent appointments of a Chief Innovation Officer and a Chief AI Officer, how do you expect innovation and AI to enhance N-able’s business resilience strategy and differentiate the company in an increasingly competitive cybersecurity market?

These roles help accelerate responsible AI adoption and disciplined innovation as AI reshapes both cyberattacks and defence. At N-able, AI is embedded into everyday customer workflows as a force multiplier for speed, accuracy and confidence. Nicole Reineke ensures those capabilities are trusted and continuously improving, while Robert Johnston identifies ways to simplify complexity, expand integrations and deliver new partner outcomes, helping make AI practical, integrated and aligned to real business resilience.

As AI becomes increasingly central to cybersecurity, where do you see the biggest opportunities for N-able to create value for its partners and customers?

The biggest opportunity is narrowing the gap between attack speed and response. AI helps teams analyse telemetry, spot anomalies and prioritize risk at machine speed.

We see the greatest impact in three areas: Reducing noise by surfacing what matters, automating response to contain threats faster and strengthening recovery confidence by validating clean, reliable restoration. Together, these capabilities deliver value across the full lifecycle, improving detection, reducing disruption and helping customers return to normal operations faster.

GCCs are becoming key centers for global engineering and cybersecurity R&D. For N-able which capabilities should remain close to product leadership and which can be effectively distributed to centers of excellence in India?

Global capability centres like Bengaluru are key to scaling innovation, bringing deep expertise in AI, cybersecurity and cloud engineering. Core platform architecture and product direction should stay close to leadership because those choices define how the stack fits together.

Distributed teams add the most value by accelerating execution, building and extending AI-driven capabilities, advancing automation and integrations and scaling data, cloud and security engineering. The goal isn’t centralisation versus distribution, it’s about coordination and working together. By aligning global teams around shared platform priorities and goals, security innovation can happen everywhere, while still supporting one business resilience strategy.