From legacy modernization to intelligent automation, the way enterprise systems are built is undergoing a seismic shift. As businesses reimagine their digital infrastructure for speed, scale, and intelligence, few voices such as Rachit Gupta’s are more relevant than ever. Rachit is a Senior Technical Architect at Guardian Life, and a Globee Award winner in Artificial Intelligence.  

With years of experience leading enterprise transformation efforts, Gupta brings a pragmatic lens to topics like cloud-first architecture, AI integration, and sustainable system design. In this conversation, he shares insights on where cloud-first thinking is headed, what architectural decisions matter most, and why adaptability is the future of technical leadership.

Rachit, thanks for joining us. Let’s start with something foundational, what does 'cloud-first' really mean to you in 2025?

Thanks for having me. To me, 'cloud-first' isn’t just about infrastructure, it’s a mindset. It’s about designing for elasticity, modularity, and rapid change. In 2025, we’re beyond lift-and-shift. Organizations now understand that cloud-first is not about migrating old problems, it’s about re-architecting systems that can scale intelligently and adapt in real time. 

You’ve written about this in your article “The Future of Cloud-First Enterprise Architecture: Why Businesses Must Adapt Now”. What are the common pitfalls enterprises face when transitioning to a cloud-first architecture?

Yes, in that article I emphasized how many companies fall into the trap of mimicking their legacy architecture in the cloud. They move monoliths without rethinking dependencies or data flows. The result? They end up paying more for cloud than they did on-prem and still lack agility. True cloud-first design means rethinking APIs, security models, data governance, and monitoring strategies, before you migrate. 

How do you see artificial intelligence reshaping enterprise architecture today?

AI is no longer a bolt-on feature. It’s becoming part of the core fabric. Whether it's intelligent routing in microservices, predictive alerting in observability, or AI-assisted development in CICD pipelines, AI is baked into how systems operate. The challenge is ensuring that AI is explainable, maintainable, and integrated responsibly. Done right, AI doesn’t just automate, it augments decision-making and accelerates delivery. 

Let’s talk about governance. How do you balance innovation with compliance and data stewardship?

Great question. Speed means chaos without governance. We use the term “controlled innovation” quite frequently to describe the architecture of systems that allow for experiments but only within certain predefined guardrails. These could be automated policy enforcements, decentralized identities, or system auditing built right into the pipelines. AI comes into play in these areas by flagging anomalies, recommending additional guardrails, or even optimizing permissions based on usage. 

What role do low-code and no-code platforms play in cloud-first enterprises today?

They are now gaining popularity at an unprecedented speed. Truly, on the cloud-first approach, not every team needs to write code all the time. Low-code development platforms allow business teams to address their issues autonomously, while engineering focuses on areas of highest impact. However, the key is governance: embedding the policies and security into the tool itself so that it cannot circumvent IT. If implemented correctly, this greatly increases productivity.

What’s one architectural decision that companies often underestimate?

Observability. In many teams, it's an afterthought. Accessing logs, traces, and metrics in real time has now become the core of distributed systems for performing any kind of debugging, optimizing them, and ensuring compliance. My recommendation is always having "observability by design," meaning systems that are transparent, measurable, and under active monitoring since day one. 

And finally, what advice would you give to engineers and architects entering this space now?

Don’t chase trends. Focus on principles: resilience, modularity, and clarity with which to learn reasoning about systems rather than tools. Stay curious. Valuable engineers of the next decade will be those who can connect the dots between cloud, AI, and sustainability to design evolution-ready systems to meet business needs.

For those building the digital backbone of tomorrow’s enterprises, voices like Rachit Gupta, who is also a paper reviewer for the 1st International Conference on Sustainable Computing and Intelligent Systems (ICSCIS 2025), offer a roadmap rooted in experience, foresight, and clarity. In a world full of AI buzz and cloud confusion, it’s this kind of pragmatic architecture that truly sets companies up for long-term success.