Varun Goswami, Global Product and AI Head at Newgen Software on how AI and low-code are democratizing enterprise software.
CIO&Leader: How is the convergence of AI and low-code changing who can build enterprise software, and how fast it happens?
Varun Goswami: The convergence of AI and low-code platforms is democratizing enterprise software development by making it accessible to a broader range of users, including those without deep technical expertise. AI automates complex tasks like design, testing, and configuration, significantly reducing the learning curve and eliminating traditional barriers. This shift enables employees closest to business challenges, such as domain experts or operational teams, to build solutions directly, allowing innovation to emerge from the ground up.
For instance, NewgenONE ’s AI Agents enable users to create applications simply by prompting, accelerating development cycles from months to days. This not only speeds up delivery but also promotes cross-functional collaboration, as AI handles repetitive tasks while humans focus on strategic problem-solving.
CIO&Leader: What impact will agentic AI have on traditional business workflows, and where do you see the biggest risks and rewards?
Varun Goswami: Agentic AI takes automation to a new level by enabling systems to not only perform tasks but also make decisions and adapt in real time. The upside is massive, more agile, adaptive workflows, deeper personalization, and the ability to respond dynamically to change. Financial institutions can use these agents for real-time underwriting, regulatory bodies can optimize compliance processes, and insurers can accelerate claims with intelligently assisting claims adjudicators.
But this level of autonomy comes with risk. Governance becomes the elephant in the room. If these agents are reasoning and making decisions, we must ensure those decisions are explainable, compliant, and aligned with business rules. That’s why frameworks like ethical and reliable AI become quintessential to ensure that, as AI scales, it remains accountable and secure.
Newgen offers Agentic Workspace, a dynamic digital environment that allows AI agents to work alongside users, handling complex workflows with minimal manual intervention. These agents understand the “what,” reason through the “why,” and execute the “how,” bringing contextual, human-like intelligence to enterprise operations. Agentic Shield and Trusted AI safeguard our Agentic framework to ensure that decisions and AI Agents are built with trust and guardrails.
CIO&Leader: As AI takes on more decision-making, how should organizations ensure accountability, especially in regulated sectors?
Varun Goswami: Accountability in an AI-powered environment hinges on transparency, governance, and control. When AI is embedded into decision-making, especially in regulated industries, organizations must be able to explain not just what a system did, but why it did it.
Newgen approaches this with guardrails built into its AI fabric. Trusted AI ensures that every decision made by an AI model is auditable and secure. Agentic Shield adds another layer of governance, ensuring agents act responsibly within organizational policies. These aren’t just technical safeguards; they’re structural principles that help organizations maintain control as AI becomes more autonomous.
In regulated sectors, this is critical. Whether it’s compliance in financial services or secure knowledge management in government, explainability and traceability of decisions are non-negotiable. So even as AI expands its role, organizations must ensure a clear chain of accountability.
CIO&Leader: What’s holding enterprises back from meaningful AI adoption—and how are leaders closing that gap?
Varun Goswami: It’s not a lack of access to AI that’s holding enterprises back; it’s the way they’re structured to use it. Many organizations still treat AI as an add-on rather than embedding it into their core operations. There’s also a fear of failure and a shortage of skills, which keeps innovation siloed within tech teams.
The leaders breaking through these barriers are doing a few things differently. They’re investing in AI-first, low-code platforms that make innovation more accessible. They’re fostering a culture of experimentation where imperfect outputs aren’t failures; they’re starting points. They’re empowering domain experts to build and iterate using AI, shifting from centralized tech ownership to a more democratized model.
CIO&Leader: What mindset and structural shifts do leaders need to embrace to become truly AI-ready?
Varun Goswami: To be truly AI-ready, leaders need to go beyond just adopting new technologies, they need to foster a mindset of openness, agility, and collaboration. Follow the Mantra: Build what matters, scale what matters. Here’s how you do it:
- Avoid automating “as-is” processes. Instead, rethink your workflows from the ground up by understanding what digital and AI can truly enable.
- Redesign with orchestration in mind. Integrate portals, APIs, and event-driven flows for end-to-end transformation.
- Invest in your people with intent. One of the most overlooked levers of transformation is structured upskilling. Create space for growth: dedicate 5–10% of employee time to hands-on experimentation with digital tools. Run internal hackathons, fund micro-innovations, and reward digital-first thinking. This not only fosters talent but also uncovers IP-grade use cases with real customer impact.
- Create a culture where innovation is guided but decentralized. Centralized vision, decentralized execution, that’s the innovation sweet spot. Equip teams with clear digital guardrails but let them lead discovery. Employees closest to the workflow often surface the most practical and high-impact automation opportunities. Don’t just empower them, expect innovation from them.
CIO&Leader: How can AI-powered platforms help bridge skills gaps and drive innovation across large, complex organizations?
Varun Goswami: AI-powered platforms provide intuitive tools that allow anyone to participate in solution-building. It gives users a strong starting point, whether it’s a workflow, a test case, or a compliance document. From there, they can refine, iterate, and deliver value faster. This considerably reduces reliance on niche technical skills and frees up expert developers to focus on more strategic work.