As global cloud spending rockets toward $679 billion in 2024 (Gartner) and hybrid infrastructure expands at 15.1% CAGR (MarketsandMarkets), CIOs face a critical crossroads: chase flashy customer-facing AI or build foundations for sustainable growth.
In conversation with Nisha Sharma, Senior Tech Correspondent at Tech Disruptor Media, Rahul S Kurkure. Founder and Director of Cloud.in, discusses comprehensive approach to modern cloud challenges, emphasizing practical, actionable solutions using AWS services to help CIOs navigate GenAI investments, hybrid cloud complexity, edge computing, AI/ML integration, ESG goals, and robust cloud security, while addressing the human element in security.
In essence, it showcases Cloud.in as a strategic partner that empowers CIOs to leverage cloud technologies effectively, securely, and compliantly, moving beyond mere technical implementation to holistic business value.
Founder and Director
Cloud.in
TDM: Gartner predicts global public cloud end-user spending will reach $679B in 2024, with AI driving much of this growth. How should CIOs prioritize GenAI investments—start with low-hanging fruit like IT ops automation, or aim for customer-facing use cases first?
Rahul S Kurkure: CIOs should start GenAI investments with the easiest use cases to implement and show results quickly. These are often internal tasks like automating repetitive IT operations, sorting support tickets, generating technical documentation, or helping teams with smart code suggestions. These use cases help teams get comfortable using GenAI as they begin to trust it.
Then GenAI can be taken to the next level by improving customer experience through AI-powered chatbots, smart recommendations on travel or shopping platforms, or even generating marketing content. These external use cases drive more business impact, but they also require more testing, thorough privacy checks, and careful implementation to ensure success.
So advice is: don’t rush. Start with low-hanging fruit, prove the value, and then scale GenAI step by step with confidence.
TDM: According to MarketsandMarkets, the hybrid cloud market will grow at 15.1% CAGR through 2028. Yet, many CIOs struggle with interoperability. How do you help clients navigate tool sprawl and inconsistent security policies across AWS, Azure, and on-prem systems?
Rahul S Kurkure: Most companies start with one cloud provider, maybe AWS. But as different teams or departments grow, they start using other clouds like Azure or keep some systems running on their own servers (on-prem). Over time, things get messy and you end up with too many tools doing similar things, security settings that don’t match, and a lack of visibility into what’s going on.
At Cloud.in, we help clean that up. We aim to bring everything under one roof, so teams aren’t jumping between different systems or confused about which tool to use. We help clients set up a central control panel using AWS tools like Control Tower, IAM Identity Center, and Security Hub to help manage users, apply consistent security rules, and monitor what’s happening across AWS, other clouds, and even on-prem environments.
We also take the time to map out where each workload should live. For example, some applications might run better on AWS, while others need to stay in the data center for compliance or performance reasons. We then help unify the tools and policies so security is the same everywhere, and teams can work without second-guessing.
TDM: With 5G accelerating IoT adoption, how should CIOs redesign their cloud-edge architectures to handle data from sensors/devices while ensuring compliance?
Rahul S Kurkure: Today, everything is always generating data, whether it’s a smart car, factory machine, medical device, or fitness wearable. This data can be huge in volume and needs to be processed quickly. But sending all of it to the cloud for processing can slow things down, increase costs, and even create compliance issues if the data has to stay within a certain region.
At Cloud.in, we help CIOs rethink how their cloud and edge systems work together. Instead of sending everything to the cloud, we redesign the architecture so that the data is first processed closer to where it’s created, right at the edge.
Only the most important or refined data is sent to the cloud for long-term storage, deeper analysis, or visualization. This approach reduces the bandwidth needed, speeds up response times, and helps organizations meet data privacy and regulatory requirements by controlling where data goes and how it’s handled.
TDM: You’ve spoken about AI-as-a-Service for SMBs. For larger enterprises, how can CIOs integrate AI/ML workflows with existing data lakes?
Rahul S Kurkure: In large organizations, data flows through many systems and is stored in data lakes like Amazon S3, Redshift, or sometimes even third-party platforms. The challenge isn’t collecting the data; it’s using it smartly without breaking what’s already working.
At Cloud.in, we help integrate AI and machine learning into these existing systems smoothly and non-disruptively. There’s no need to start from scratch or move everything to a new setup. Instead, we use powerful AWS tools like Amazon SageMaker and Amazon Bedrock to build and deploy AI models that work with the data right where it lives.
This means businesses can start using AI to make predictions, automate decisions, or find patterns in their data without lifting and shifting the entire data infrastructure. We also focus on what happens after the model is built. AI can’t just be a one-time project or a side experiment. It needs proper management, including tracking model versions, monitoring performance, and ensuring it stays secure and compliant. That’s where MLOps comes in, and we help teams get that right so their AI projects actually deliver value at scale.
In short, we help enterprises unlock the value of their data with AI, while keeping things running smoothly and securely.
TDM: You’ve highlighted cloud’s role in reducing energy costs. Beyond carbon footprint, what metrics should CIOs track to align cloud strategies with ESG goals?
Rahul S Kurkure: Saving energy is important, but it’s only part of the bigger picture when building a cloud strategy that supports ESG (Environmental, Social, and Governance) goals. At Cloud.in, we encourage CIOs to go beyond just looking at power consumption. There are other meaningful metrics to track, like how often hardware is reused instead of replaced, how much water data centers use for cooling, and the carbon footprint of the specific cloud regions their workloads run in.
We help our clients use AWS tools like AWS Cost Explorer, highlighting opportunities to improve resource efficiency.
We also help teams take action, like right-sizing workloads, which means adjusting cloud resources so you’re not using more computing power than you need. We also identify and decommission unused resources, such as idle servers or forgotten storage that quietly add to cost and environmental impact.
These steps help with ESG goals and sustainability reporting and lead to real financial savings.
TDM: 96% of teams claim they’re ‘cloud-secure,’ yet 37% fail audits. Where’s the biggest disconnect?
Rahul S Kurkure: Many teams think they’re secure because they’ve set up firewalls, encryption, and access controls but fall short during audits. The truth is, there’s often a gap between feeling secure and actually proving it with evidence. Security today needs to be continuous, not something you set up once and forget.
We help close that gap by making security something you can measure and monitor in real time. We use AWS tools like AWS Config (to track how resources are set up and if they meet security standards), GuardDuty (to detect unusual or suspicious activity), and Security Hub (to bring all the security alerts and findings into one place).
But we don’t stop setting up these tools; We also ensure they work together. For example, if GuardDuty detects a threat, Security Hub can flag it, and AWS Config can tell you whether your current setup is leaving you exposed. This kind of integration helps teams spot problems quickly and take action before they become major issues.
In simple terms, it’s not just about having the right locks on the doors. It’s about having cameras, alerts, and a smart system that tells you what to do next if something goes wrong. That’s how we help businesses stay secure, pass audits, and sleep better at night.
TDM: 79% trust SaaS security, yet 56% can’t enforce access controls. Is SaaS the new shadow IT?
Rahul S Kurkure: Absolutely, and this is something we hear from many CIOs and IT leaders. SaaS tools (like file-sharing apps, CRM platforms, or marketing tools) are incredibly easy for teams to start using. Anyone with a credit card can sign up and get going. That flexibility is great for productivity, but it also means that tools can start popping up all over the company without proper oversight. This is where things get risky because if IT doesn’t know which apps are being used, they can’t manage access, enforce security, or ensure compliance.
At Cloud.in, we help organizations regain control without slowing their teams down. We set up systems like single sign-on (SSO) and conditional access policies using AWS IAM Identity Center and trusted third-party integrations. This means employees can log into all their SaaS tools with one secure identity, and access can be granted or revoked based on role, location, or device.
So even if teams are using multiple SaaS apps, IT can still see what’s happening, manage who has access, and make sure sensitive data stays protected.
SaaS tools are powerful, but only when they’re not operating in the shadows.
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