As artificial intelligence reshapes enterprise technology, software companies are under pressure to move beyond incremental upgrades and rethink core platforms. Ramco Systems is betting on this shift through a combination of growth in payroll and aviation software and a broader effort to rebuild its ERP platform around AI-native capabilities. Sandesh Bilagi, president and COO, discusses the company’s growth priorities, AI strategy and the changing dynamics of enterprise technology in an interview with Sudhir Chowdhary. Excerpts:
Ramco has been through phases of reinvention – where are you placing your biggest bets: ERP, aviation, payroll, or platform-led offerings?
We are seeing the biggest opportunities for our Payce and Aviation Software offerings, where decades of deep domain expertise give us a durable advantage in mission-critical environments defined by complexity, scale, and strict compliance requirements. Both offerings are seeing sustained demand and strong customer pull for intelligence-led transformation. At the same time, our ERP offering is undergoing a deliberate reinvention. We are re-architecting it into an AI-native platform that replaces menu-heavy workflows with conversational, agent-led experiences and faster time-to-value.
How do you differentiate Ramco in a crowded enterprise software market?
We differentiate Ramco by taking responsibility for the entire customer outcome, not just the software. Many vendors sell licenses and leave execution to partners; we own the implementation and remain accountable for results. This accountability is reinforced by decades of deep domain expertise built by serving complex industries such as payroll, aviation, cement, textiles, and third-party logistics, where generic software often falls short. We also recognise that enterprises want flexibility. For example, customers can deploy our Payce platform on cloud, consume it as a fully managed service, or adopt a hybrid model depending on regulatory, scale, and operational needs. This combination of domain understanding, delivery ownership, and deployment choice allows customers to modernise with far less risk.
How are you embedding AI and automation into ERP without overcomplicating workflows?
We recognised early that workflows in traditional ERP systems become overly complicated when AI is layered on top, rather than built in. Our approach is different: we are transforming ERP to be AI-native from the outset, so intelligence works quietly in the background instead of becoming another workflow users must manage. We embed automation through role-based hubs, conversational interfaces that enable easy access to information, and agentic workflows that execute tasks based on business context and policy, while always keeping people in control. By combining an API-first architecture with human-in-the-loop design, we reduce clicks, avoid rigid customisation, and ensure AI simplifies work, empowers users and avoids adding another layer of complexity.
Are customers asking for AI, or are vendors pushing it?
Our customers do ask for AI, but that is really shorthand for wanting better outcomes: speed, accuracy, resilience, and simpler experiences in increasingly complex operations. AI has become relevant because it delivers on these expectations, not because customers are chasing a buzzword. In our conversations, customers are clear that they want software that understands their context, reduces manual effort, provides actionable intelligence from their data, and helps teams make better day-to-day decisions. That is what brings AI into the core of enterprise platforms. As a company at the cutting-edge of innovation, we have anticipated our customers’ needs and have been developing and launching AI-enabled features for our products. Our responsibility as a vendor is to embed AI thoughtfully, grounded in deep domain capability, so it creates real value, stays under human control, and earns trust rather than distracting from the work that matters.
Ramco has a strong positioning in aviation software – how are airlines and MROs using data and analytics differently?
Airlines and MROs use data to achieve the same objective: keeping aircraft safe, compliant, and available for service. The difference lies in where accountability sits. Airlines primarily apply analytics at the fleet and network level, using aircraft health, defect, and parts data to support dispatch, routing, and maintenance-timing decisions that protect schedules and minimise disruption. MROs apply many of the same data inputs within maintenance execution, focusing on task sequencing, labour allocation, material staging, and work-in-progress control to deliver predictable turnaround times. While responsibilities overlap, data use reflects each organisation’s role in the aviation value chain.
Will AI reduce the need for large enterprise software suites?
AI will not reduce the need for enterprise software suites; it will redefine what distinguishes meaningful ones. Large suites endure because they embody decades of deep domain knowledge: industry-specific workflows, regulatory nuance, and operational realities that have been shaped in partnership with customers over time. That depth is not something AI can replicate on its own. What AI does enable is a shift from systems that merely record transactions to systems of intelligence that understand intent and drive outcomes. At Ramco, our long experience across complex domains allows AI to work with trusted business logic, compress workflows, surface insights, and automate intelligently. The future is not fewer enterprise platforms, but smarter suites built on deep domain foundations.