Transformation with visibility: Building data-driven, adaptive enterprises

Transformation today isn’t about speed; it’s about seeing clearly and adapting fast. In this conversation with Dataquest, Yadi Narayana, Field CTO – APJ at Datadog, discusses how observability and AI-powered automation are reshaping enterprise strategy — turning data into decisions and complexity into resilience.

How has digital transformation strategy evolved amid changing business realities?

In the last few years, digital transformation has matured from being a broad, aspirational goal to a more disciplined, business-aligned process. Enterprises are no longer chasing transformation for the sake of it. The focus has shifted from “digital for scale” to “digital for resilience and adaptability”, according to a KPMG report. ( Source: India’s digital dividend: The strategic roadmap towards becoming a global digital leader)

Today’s transformation strategies are built around three pillars: efficiency, intelligence, and agility. Businesses are integrating AI-powered observability, security, and automation to enable real-time adaptability. The goal is to make technology ecosystems self-aware and self-optimising, capable of responding dynamically to changing customer demands or market shocks.

Another key change is the integration of business and IT roadmaps. Previously, CIOs and CTOs often worked in parallel to business leaders; now, technology strategy is business strategy. This means digital initiatives are being evaluated not just on technical performance but on how effectively they enable new revenue models, improve customer experiences, and enhance operational resilience.

What continues to be the hardest challenge for CIOs — aligning budgets, managing talent, or proving ROI?

All three are interlinked challenges, but proving ROI remains the most persistent priority for enterprises. As budgets tighten and boards demand measurable outcomes, CIOs are under pressure to demonstrate how every dollar spent on cloud, automation, or AI translates to tangible business impact.

This has pushed organisations toward value engineering — designing digital initiatives that are measurable from day one. Observability, analytics, and unified dashboards now play a crucial role in quantifying ROI by tying system performance directly to customer experience, conversion rates, and uptime.

The talent gap continues to complicate this equation. While the introduction of AI adds complexity to already hybrid environments, it also offers a powerful way to alleviate productivity challenges. By automating routine tasks and enhancing decision-making, AI enables teams to focus on higher-value innovation. The most successful CIOs are addressing this balance through a combination of upskilling, automation, and strategic hiring.

Are enterprises scaling automation, AI, and cloud initiatives, or recalibrating them for smarter efficiency?

It’s a strategic recalibration rather than a slowdown. Automation, AI, and cloud remain core investment areas, but the emphasis is shifting from expansion to optimisation. Enterprises are asking, “How do we make our cloud smarter, not just bigger?”, and evaluating the resilience of the foundations they already have in place.

For instance, enterprises adopting hybrid cloud solutions integrate on-premises setups with cloud elasticity, achieving significant cost reduction in disaster recovery and three times faster provisioning. Multi-cloud approaches let them balance workloads, optimise costs, and avoid vendor lock-in while embedding AI-powered cost-performance analytics and automated governance.

Further, AI is increasingly being embedded across operational layers, from predictive maintenance to anomaly detection and auto-remediation. Automation is evolving from workflow scripts to intelligent orchestration, where systems can self-adjust based on telemetry data.

What’s one guiding principle CIOs should follow to remain agile and value-focused?

If there’s one guiding principle, it’s data-driven adaptability. CIOs today must operate at the intersection of agility and accountability — making quick decisions, but always grounded in data.

This requires complete visibility across digital ecosystems. Without unified observability and data integration, even the most advanced digital programmes risk fragmentation. The ability to correlate metrics, from infrastructure health to business KPIs, enables CIOs to make informed trade-offs between cost, performance, and innovation.

Moreover, transformation is no longer about implementing technology; it’s about enabling continuous change. The most adaptive CIOs are treating transformation as an ongoing journey, embedding experimentation, automation, and learning into the organisation’s DNA.

How should technology partners evolve to meet CIO expectations in this new transformation era?

The role of technology partners has fundamentally changed. CIOs no longer want vendors; they want strategic collaborators who understand their business priorities as deeply as their technical pain points.

Partners must now bring domain expertise, co-innovation capabilities, and outcome-driven frameworks to the table. This means helping enterprises translate technical metrics into business outcomes — uptime into revenue protection, latency into customer satisfaction, and automation into workforce productivity.

In this environment, shared accountability is key. The best partnerships are those where success metrics are co-owned, whether it’s optimising cloud spend, improving reliability, or enhancing customer experience.

Finally, technology partners must also play a consultative role, guiding CIOs through new frontiers like AI ethics, data governance, and automation safety. The future of digital transformation will belong to ecosystems, not individual players — and partnerships built on trust, transparency, and measurable value will define that journey.

shrikanthg@cybermedia.co.in