By Lyndsey James |
The pressure to become AI-ready is mounting across every boardroom in 2026. But Hitesh Bhardwaj, chief technology officer and head of business for Asia Pacific APAC at Cloud4C, believes most organisations are asking the wrong question.
“Business leaders must realise that AI amplifies existing operational maturity,” he says. “If the data estate is fragmented, AI will expose it. If identity controls are inconsistent, data leaks widen. If operations are over-reliant on manual interventions, AI-led workloads make that fragility more visible.”
For Bhardwaj, the real question is not about which AI use case to build first. “The number one question is: ‘Can our organisation continuously and sustainably operate at scale while ensuring intelligence, safety, reliability and regulatory compliance?’,” he says. “Enterprises that move fastest are those that treat AI readiness as an operating model transformation – cloud, data, security, compliance, automation and managed services working together from the start.”
That transformation starts in the cloud. For Bhardwaj, being cloud-first isn’t a technical preference – it’s a business imperative. “Being cloud-first is all about agility and adaptability; continuously modernise, innovate and expand leveraging the latest technologies,” he says. “An AI-powered operating model is a business criticality, and enterprise AI use cases are best delivered and responsibly operated via robust cloud platforms like Microsoft Azure.”
Cloud4C’s approach combines Azure’s hyperscale infrastructure with what Bhardwaj describes as a connected, fully managed ecosystem – bringing modern applications, data, AI, security and identity together under one roof. Azure Services, in his words, “when integrated reliably, help modernise every layer of the legacy core, adopt the newest IT and operating stacks and set the foundation for a secure AI-led future.”
Cloud4C’s own role in this ecosystem is what Bhardwaj calls a unique platform-people-process approach to managed services. At the centre is SHOP, the company’s agentic AI-infused unified operations platform. “SHOP renders customers single control across all operational landscapes, IT and cloud platforms, installed cloud-native services, applications and data stacks, augmented with multi-layer security and proactive predictive maintenance,” says Bhardwaj.
Underpinning this is a network of 25 Centres of Excellence, tagged directly into SHOP and governing clients’ mission-critical functions around the clock, alongside what Bhardwaj describes as “encoded standard operating procedure (SOP)-driven and automated processes” that ensure the operating model runs without failure. The numbers are impressive: “Today we resolve 85 per cent of alerts automatically, reducing time-to-resolve by over 80 per cent,” says Bhardwaj. “The entire model is available in a single service level agreement, and is secured and compliant by design, irrespective of the landscape size and complexity.”
Cloud4C's AI solution features built-in security controls, which means it can be used by organisations in heavily regulated industries like healthcare (Photo: Adobe Stock/Svitlana)
In regulated industries, that last phrase carries particular weight. Bhardwaj is emphatic that multi-layer security and compliance should be built into the architecture from the outset – not bolted on later. “AI-led operating models must ensure continuous risk vigilance, from workload assessments to implementation and run,” he says.
Crucially, the requirements vary by geography. “A Middle East financial services institution, Australian public sector organisation, or ASEAN hospital will have different regulatory mandates,” says Bhardwaj. “Cloud4C aligns security controls at each layer of the IT stack to a broad spectrum of national and international standards. Done well, security and compliance-first operations don’t slow transformation – they build the trust needed to accelerate it.”
Cloud4C operates across 25 countries in APAC, EMEA, and Americas, and Bhardwaj points to a range of high-stakes deployments as evidence of the model’s real-world impact. An APAC federal agency moved a more than 12-terabyte HANA landscape to sovereign-hosted Azure. An American wellness leader personalised care delivery with generative AI, streamlining decision-making for thousands of patients. A Gulf-based government housing organisation modernised its flagship citizen application with Oracle on Azure. One of the world’s largest aviation companies fortified its global operations with AI MXDR. And Manila Water, a large water and wastewater service utility, secured business continuity with disaster recovery on Azure to reduce recovery point and recovery time objectives.
“Over a million households or 7.9 million citizens depend on our services,” said Melissa Egasani, chief information officer at Manila Water. “Cloud4C’s platform-ready services, backed by deep Azure competency and localised support, ensured an infrastructure of national importance operates risk-free, always.”
Looking to the future, Bhardwaj draws a sharp distinction between organisations that are AI-ready and those that are merely AI-enabled. “The difference will come down to trust, resilience and repeatability,” he says. “Can the organisation govern its data? Maintain compliance across jurisdictions? Detect, respond, and recover before disruption becomes visible? Constantly innovate without disrupting foundations? These are the areas that will differentiate a quick fixer versus a business aiming for an intelligent future with an AI-ready operating model.”
The message, ultimately, is clear: AI transformation is an infrastructure problem before it is an innovation one.
Discover more about enterprise solutions from Microsoft Partner businesses in the Summer 2026 issue of Technology Record. To get content like this on a regular basis, subscribe to the print edition or free digital edition of the quarterly Technology Record magazine.