Inside AI Co-Pilots as productivity gamechanger: Rohan Chhatre, Volkswagen Group
In today's rapidly evolving enterprise landscape, artificial intelligence is no longer a backroom experiment or a shiny add-on. It is now central to how organizations build, operate, and grow. At the forefront of this shift are AI copilots, context-aware digital assistants designed not just to automate tasks, but to augment human potential. In a compelling DeepTalks conversation,
Rohan Chhatre
, at Volkswagen Group Technology Solutions India, unpacks what this evolution means for enterprises, leadership, and the future of work.
Rethinking work with AI copilots
AI copilots are not a futuristic dream, they are already reshaping the way organizations think about productivity and collaboration.
Chhatre
sets the tone, 'AI copilots are not just intelligent. They are contextually intelligent,' he emphasizes. These digital colleagues are capable of understanding the business context, whether that's an organizational policy, project workflow, or customer interaction, and responding with nuanced, relevant support.
Think of an AI copilot as a hyper-organized team member who knows every file location, meeting detail, and deadline. But unlike static automation, copilots adapt, learn, and evolve with usage, making them indispensable partners in both routine operations and complex decision-making.
'AI copilots are like digital colleagues, context-aware, intelligent, and always ready to assist. They know where every file is, what deadlines are coming up, and how to help you work smarter', states Chhatre
Inside the enterprise use cases
Across industries, the use cases are multiplying.
Rohan
outlines three core areas where AI copilots are already proving transformative:
Software Development: Tools like GitHub Copilot are acting as real-time pair programmers, handling documentation, code reviews, and even refactoring, freeing up developers for more strategic and creative work.Customer Support: Copilots can unify fragmented data across ticketing systems, emails, and knowledge bases to deliver fast, contextual responses to customers and agents alike.HR and Business Functions: From summarizing interview notes to drafting employee communications, copilots can streamline administrative tasks that are critical yet time-consuming.
Other promising areas include finance (detecting payment anomalies), procurement (pattern recognition), and sales (dashboard generation and trend analysis).
'DevOps and customer support are leading the adoption curve, GitHub Copilot is a game-changer for developer productivity, and AI copilots are transforming how we resolve customer issues', says Chhatre.
Redefining the CIO's mandate
For CIOs and tech leaders, the AI Copilot era presents a mandate that is both thrilling and daunting.
'If you're still on the fence, you're already behind.'
Chhatre offers a three-pronged checklist for CIOs embarking on this journey:
Data Readiness: 'Your copilots are only as smart as the data you feed them.' Enterprises must clean, structure, and contextualize their internal datasets to unlock meaningful copiloting experiences.Security & Compliance: With great power comes greater responsibility. Copilots must operate within tightly defined guardrails to ensure privacy, compliance, and enterprise integrity.Change Management: Tech alone won't drive adoption. Organizations must cultivate evangelists, early adopters who showcase the benefits, bust myths, and build cultural trust.
'If you're still on the fence about AI copilots, you're already behind. But adoption must come with guardrails, data readiness, security, compliance, and change management', observes Chhatre
Building a responsible AI culture
Rohan debunks a common myth: that copilots will replace human jobs. 'Instead of fearing replacement, think delegation,' he urges. Identify the 20-30% of tasks in every role that are repetitive or cognitively draining. Then, let copilots handle them so that humans can focus on creativity, problem-solving, and innovation.
'AI won't take your job. But someone using AI might. It's time to embrace copilots and delegate the mundane, so you can focus on what truly matters,' says Chhatre
However, Chhatre also warns against blind trust. 'Copilots hallucinate. They make mistakes. Human oversight is critical.' As such, CIOs must define governance frameworks that include:
Ethical model designBias mitigationHuman-in-the-loop supervisionAudit trails and access controls
'Copilots can be wrong, they hallucinate. Don't delegate decisions to AI. Use it to assist, not replace. Keep humans in command,' Chhatre emphasizes.
The Human-AI symbiosis
Perhaps the most profound insight from the conversation is the vision of the next-gen digital workforce, not one where humans and machines compete, but one where they collaborate. 'That line between human work and copilot work is already thinning,' Chhatre notes.
'Old automation was like pressing a button on a vending machine. AI copilots are different, they understand you're thirsty, know your preferences, and hand you the right drink before you ask.', reflects Chhatre
The most successful copilots will be those that embed seamlessly into existing platforms like Microsoft 365, Salesforce, or SAP. Their strength lies not in complexity, but in usability and design. 'User-centered design, emotional tone, multi-language capabilities, these factors will decide which copilots become indispensable,' he adds.
'The copilots that work best are the ones embedded right into
Gmail
, Outlook, Word, right where you already are. You shouldn't have to go somewhere else to use them', he adds.
On the ground, DevOps and customer support teams are already reporting efficiency gains, with early metrics showing up to 25% increase in productivity. The future looks even brighter as copilots move beyond backend tasks to shape sales strategies, legal reviews, and even leadership decision-making.
How a Copilot transformed support efficiency
At a global enterprise working across automotive and manufacturing verticals, the customer support team faced a familiar challenge, resolving tickets that spanned multiple disconnected systems. Knowledge bases lived in one platform, past ticket logs in another, and product documentation in yet another. Support agents were spending 30-40% of their time manually searching for relevant answers, often leading to delayed responses and inconsistent customer experiences.
The company deployed an AI copilot trained specifically on its internal documentation, ticket history, and FAQs. Within weeks, the results were visible. Agents could now simply prompt the copilot with a query and receive a pre-validated, cross-referenced response in seconds.
Impact:
Average ticket resolution time dropped by 25% Agent satisfaction scores rose, as repetitive hunting for answers was eliminatedEscalations reduced due to more consistent and faster replies
Customer support is a great use case for copilots. They can pull from different knowledge bases and give a singular view to the support agent. It helps reduce time and cognitive load. Rohan also mentioned: Old ticket data, knowledge base, workflow logs, copilots bring them together for better resolution.
Looking ahead: The roadmap and the realization
Over the next 12-24 months, Rohan predicts a surge in enterprise copilots tailored for specific functions, legal, procurement, HR, and sales. These copilots will summarize lengthy reports, surface hidden anomalies, and drive faster insights at scale. But success will hinge on three pillars:
Strong strategy with short sprints - Think six months ahead, not three years.
Upskilling at scale - From prompt engineering to ethical AI design, literacy must go mainstream.
Measurable impact - Usage metrics, productivity benchmarks, and user feedback loops must be built in from day one.
Chhatre concludes, 'Lead with purpose. AI copilots are not just a trend, they are a strategy. And strategy needs alignment, clarity, and recalibration.'
In the age of copilots, CIOs are no longer just technology stewards. They are architects of intelligent collaboration, custodians of ethical innovation, and enablers of the human-machine partnership.
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