

Artificial intelligence is no longer a futuristic concept. Instead, it has started to affect industries and change business operations. With a wide range of applications from automating processes to improving the customer experience, the benefit of adopting technology is immense.
In the latest episode of the Analytics Insight Podcast, host Priya Dialani speaks with Ganesan Karuppanaicker, the Chief Technology Officer (CTO) of Birlasoft, about inclusive AI readiness and how companies can transform into AI-first firms without neglecting the human aspect.
Priya starts the discussion by emphasizing the challenges IT leaders face in a fast-paced technological landscape. “The pressure to invest in technologies like AI is immense, but chasing breakthroughs without a clear strategy can delay long-term innovation,” she notes.
Ganesan agreed with her and stressed the importance of a structured approach. “Technology implementation is easier, but ensuring inclusive AI is so critical for any organization,” he explains. Further, he highlights three most vital aspects, including AI readiness: skill democratization, cultural alignment, and technical preparedness.
Skill democratization ensures employees understand AI and can use it responsibly. “We trained over 70% of our talent in Gen AI and analytical AI, then moved to advanced concepts like prompt engineering and AI-assisted tools such as M365 Copilot,” Ganesan says.
Cultural alignment fosters openness to experimentation and collaboration. “This can happen only when every talent understands AI’s role as a co-pilot, assisting rather than replacing them,” he adds.
Technical Preparedness emphasizes Transparency, Explainability, and Bias-Free Outcomes. Birlasoft has invested 550,000 training hours into preparing its teams to effectively apply AI through Monthly Gen AI Days, Prompt-a-thons, and Co-Pilot Studio. These initiatives will enable Technical and Non-Technical Teams alike to benefit from AI.
Ganesan reveals that the objective of Birlasoft is to evolve into a next-generation, AI-driven enterprise and, at the same time, ensure that technology investments deliver quantifiable business results. “When we define an inclusive AI principle, it is not only technology readiness but also skill democratization and cultural alignment,” he says.
By combining robust AI infrastructure with human-centric adoption, enterprises can move from experimentation to scalable, outcome-driven AI implementation.