In a conversation with CIO&Leader, Birlasoft’s Anand K Sinha shares how structured enablement, stakeholder trust, and ethical AI frameworks are redefining GenAI success – beyond just tools and tech.
As enterprises accelerate their AI journeys, the real differentiator isn’t just the technology, it’s the people, processes, and principles behind it. In an exclusive interaction with CIO&Leader, Anand K Sinha, CIO & Global Head IT at Birlasoft, shares how the company’s AI First Mover Strategy is driving large-scale transformation across functions from HR and Legal to IT and Sales.
He discusses the critical lessons learned in moving AI from pilot to production, the frameworks helping de-risk adoption, and the importance of embedding ethics, governance, and continuous learning into every stage of the AI lifecycle.
CIO&Leader: What has been your most significant learning while moving AI projects from pilot to production?
Anand k Sinha: AI Adoption as a People-First Transformation : At Birlasoft, we believe that AI adoption is fundamentally a people-first transformation. Our AI First Mover Strategy positions us at the forefront of technological innovation, where we leverage AI to drive substantial change across core operations in HR, Legal, Pre-sales, IT Support, Sales Operations, and core delivery. we have delivered significant productivity gains and operational efficiencies, setting new benchmarks within our industry. However, our most valuable learning has been that structured enablement, stakeholder alignment, and continuous learning are far more critical to success than simply focusing on model accuracy or infrastructure readiness.
A standout example of this is the Copilot rollout, where we achieved over 12,450 assisted hours within just 9 months. This success underscores the power of a phased adoption model supported by comprehensive training—a testament to the fact that effective AI adoption is as much about people as it is about technology.
CIO&Leader: What challenges did you encounter in scaling AI initiatives (e.g., data readiness, model drift, stakeholder buy-in, integration with legacy systems)?
Anand k Sinha: We faced several challenges while scaling AI initiatives:
- Data readiness was hindered by legacy systems that lacked standardization and accessibility.
- Model drift required ongoing monitoring and periodic retraining to maintain accuracy and relevance.
- Gaining stakeholder buy-in was initially difficult, but was gradually achieved by demonstrating clear business outcomes.
- Integration with legacy infrastructure posed complexities, which we addressed using custom connectors and middleware solutions.
CIO&Leader: What best practices or frameworks have helped you de-risk and accelerate AI adoption?
Anand k Sinha: Birlasoft’s AI adoption is anchored in a metrics-driven operating model and a robust Center of Excellence (CoE). Weekly POD reviews using RAG indicators enable rapid issue resolution, while outcome-focused dashboards track business impact. Standardized automations to ensure consistent delivery across teams. “AI for All” programs foster cross-functional understanding, and responsible governance embeds ethical principles into scalable deployment. This structured approach empowers Birlasoft to drive innovation, operational efficiency, and trust in AI systems across the enterprise.
CIO&Leader: Could you share a specific use case where AI delivered tangible business value for your organization?
Anand k Sinha: Gen AI Adoption and Benefits: We automate tasks, enhance decision-making, and improve productivity. Our efforts reduce mean-time-to-resolve for IT tickets and boost employee support efficiency. The B-Hive GenAI Bot handles over 94% of policy-related queries with personalized responses. Our Solución GenAI, integrated with ServiceNow, manages over 10 internal apps and resolves 73% of application-knowledge-related tickets, improving efficiency and employee experience. We’re also developing GenAI apps for risk assessment and project health evaluation to enhance decision-making and operational excellence.
We envision a future where Agentic AI solutions are seamlessly integrated into every facet of our operations. By leveraging the transformative power of AI & GenAI, we aim to enhance efficiency, accuracy, and innovation across Human Resources, Finance, Recruitment, Legal, Sales, and Learning & Development functions. These enhanced capabilities and reaffirm our commitment to excellence and growth.
CIO&Leader: How are you approaching governance, ethics, and monitoring of AI in production environments?
Anand k Sinha: We believe AI should be developed and deployed with integrity. That’s why we’ve built a comprehensive governance framework to ensure our AI systems are transparent, fair, and aligned with our values. Ethics isn’t an afterthought — it’s embedded from the start. With safeguards like bias mitigation, human oversight, and explainability, we’re committed to building trustworthy AI. We monitor performance continuously, maintain detailed audit trails, and stay ahead of global regulations to ensure our AI supports better decisions and meaningful innovation — responsibly.