Inside Cyient’s AI Journey: A Candid Conversation with CIO Sujeet Kumar

As organizations across industries race to integrate AI into their operations, Cyient has taken a structured and pragmatic approach to embedding AI and Generative AI into core business workflows. At the helm of this transformation is Sujeet Kumar, Chief Information Officer at Cyient, who is playing a pivotal role in shaping the company’s digital and AI-first strategy. Under Sujeet’s leadership, Cyient has moved beyond experimentation to enterprise-wide deployment of AI, spanning engineering design, manufacturing, supply chain, regulatory compliance, and customer support. Initiatives like CyAI, the company’s in-house GenAI platform, are streamlining service delivery, automating support workflows, and enhancing productivity through deep integration with RPA and enterprise systems.

Cyient’s platform-led, agent-based approach to AI ensures not just scalability, but alignment with business objectives and industry-specific needs. Whether it’s AI-driven CAD modeling, predictive maintenance, or GenAI-powered diagnostics and documentation, each solution is designed with an operational impact in mind.

Some edited excerpts from the interview:

Can you take us through some of the recent digital initiatives undertaken by Cyient that have had a huge impact?

Cyient has launched a series of transformative digital initiatives that are embedding AI and Generative AI (GenAI) deeply into its core business processes across sectors. A key initiative is the CyAI Platform, an internal GenAI solution seamlessly integrated with RPA to automate service requests, deliver contextual responses, and enhance employee support experiences.

In engineering and design, Cyient has implemented AI-driven tools for CAD analysis, 2D–3D modeling, BOM creation, document generation and validation, and parametric model tuning—leading to reduced design cycle times. In the aftermarket domain, GenAI solutions are enabling automated customer support, guided diagnostics, and decision support using historical failure data and technical documentation.

In manufacturing, AI is powering predictive analytics for yield enhancement, anomaly detection using sensor data, and delivering insights for more autonomous plant operations. The supply chain has also benefited, with AI models improving parts forecasting, vendor evaluation based on historical performance, and logistics cost optimization through simulation.

On the compliance front, Cyient has automated regulatory reporting, document validation, and audit preparedness using AI. Additionally, GenAI is being used to convert 2D drawings into BIM models—accelerating infrastructure and rail project planning. To sustain innovation, Cyient has also established GenAI Centers of Excellence (CoEs) that continuously co-create solutions tailored to client needs.

Further, the company is boosting productivity through Microsoft Copilot by enabling quick access to internal assets like case studies and capability documents, integrated across Office tools. All of these initiatives are tightly aligned with customer goals and geared toward addressing today’s dynamic economic and technological challenges.

As AI becomes a cornerstone of business operations, what high-impact AI use cases (e.g., predictive analytics, process automation) is Cyient implementing to enhance efficiency and innovation, and how do you ensure alignment with business objectives?

Cyient is integrating AI and GenAI across the entire engineering value chain to drive innovation and efficiency. For instance, in design and engineering, AI is expediting CAD analysis and 2D-to-3D model conversion, while GenAI is automating the generation of engineering documentation—enhancing accuracy and significantly reducing manual work.

In manufacturing, AI-based systems are enabling real-time optimization through autonomous plant operations and machine learning models that improve yield and minimize defects. The supply chain benefits from AI-driven optimization models that refine routing, inventory management, and warehouse operations, leading to significant cost savings.

Customer service is also being transformed. AI-powered assistants are automating support interactions, while GenAI tools retrieve contextual insights from product data and historical records to guide diagnostics and decision-making. On the compliance side, GenAI is streamlining audit preparation and regulatory documentation.

To ensure these AI initiatives remain aligned with business goals, Cyient involves business stakeholders in the development process to ensure domain relevance. The company’s agent-based modular architecture promotes reusability and quick deployment of AI components across use cases. Continuous feedback from users helps fine-tune model performance, while human-in-the-loop oversight ensures responsible and accountable AI use. With flexible deployment models—cloud, on-premises, or hybrid—Cyient ensures integration within enterprise environments while adhering to security and operational requirements.

With generative AI transforming customer and employee experiences, how is Cyient embedding generative AI into its workflows, and what steps are you taking to address concerns around data privacy and ethical use?

Cyient is strategically embedding Generative AI into its workflows to elevate both customer and employee experiences, while placing a strong emphasis on responsible and secure implementation.

The company has adopted a platform-led, agent-based architecture that allows scalable deployment of GenAI capabilities. These agents are coordinated via a central Master Agent that includes human-in-the-loop mechanisms, enabling automation with oversight. In customer support, for instance, CyAI—Cyient’s internal chatbot—can access information from vast document repositories, resolve queries, raise tickets, and guide users via RPA integration.

In engineering, GenAI is supporting faster product iterations through capabilities such as CAD analysis, 2D–3D conversion, and BIM modeling. It’s also helping digitize legacy engineering data. For content workflows, GenAI automates documentation, part forecasting, and validation processes—improving throughput and accuracy. In the aftermarket domain, GenAI aids in service part identification, diagnostics, and manual creation based on historical and sensor data—enhancing uptime and customer satisfaction.

Cyient addresses concerns around data privacy and ethical use with a comprehensive governance framework. Solutions are offered in on-prem, cloud, or hybrid environments to match client security policies. Customer data is securely segmented using containerized infrastructure, while strict role-based access control (RBAC) governs user permissions. All data is encrypted in transit and at rest, and AI models are designed to escalate ambiguous queries to human agents for further resolution. A robust feedback loop also ensures continuous learning and bias reduction.

Looking ahead, Cyient is institutionalizing GenAI through a dedicated CoE, ongoing workforce training in AI/ML, and promoting reusable architectures to accelerate innovation while maintaining trust and transparency.

How is Cyient’s IT team positioning cybersecurity as a strategic asset to build customer trust and drive business growth, especially in industries with stringent data security requirements?

At Cyient, cybersecurity is regarded not just as a safeguard but as a strategic enabler of customer trust and long-term business resilience. Recognizing the criticality of data confidentiality, integrity, and availability—especially in high-regulation sectors—Cyient has invested significantly in advanced cybersecurity technologies.

The company utilizes a range of cutting-edge tools, including XDR, PAM, ZIA, ZPA, WAF, and others to protect endpoints, servers, cloud applications, and on-prem assets. Its AI-enabled Security Information and Event Management (SIEM) platform allows real-time threat monitoring, detection, and rapid response, enabling a proactive security posture.

Cyient’s cybersecurity infrastructure includes 24×7 surveillance, integrated threat intelligence, and structured mitigation protocols. Regular training sessions ensure employees remain up to date with the latest security practices, while strong governance frameworks aligned with global standards (GDPR, ISO 27001:2022, CERT-In) help mitigate internal and external risks.

Cyient also collaborates with industry partners to continuously improve its cybersecurity posture and adopt best practices. Its ongoing investments in people, technology, and process enhancements ensure the company stays ahead of evolving threats. Strong security scores across third-party platforms bear testimony to the robustness of Cyient’s cyber defense strategy.

With automation being a key driver of operational efficiency, how is Cyient leveraging robotic process automation (RPA) or AI-driven tools to streamline IT software services and reduce technical debt?

Cyient is using automation as a core lever to enhance service delivery and streamline IT operations. At the heart of this initiative is CyAI, an AI-driven virtual assistant designed to automate routine IT support and reduce reliance on manual interventions.

CyAI provides employees with contextual access to information from internal systems and knowledge bases, minimizing the need for human support. It’s also integrated with RPA tools to perform tasks like ticket creation, password resets, and service request initiations—significantly improving response times and reducing workload.

By automating these repetitive tasks, Cyient is effectively addressing technical debt—removing legacy inefficiencies, standardizing service delivery, and freeing up IT teams to focus on high-impact initiatives. The platform evolves continuously by learning from user feedback, leading to smarter interactions and higher service quality over time.

This automation-first approach allows Cyient to boost operational agility, lower maintenance costs, and elevate overall employee experience across its IT ecosystem.

What specific training programs is Cyient implementing to equip its IT workforce with skills in AI, machine learning, and data analytics?

Cyient has taken a multi-pronged approach to upskill its workforce in emerging digital technologies, with a strong focus on AI, ML, and data analytics.

A key initiative is the ‘EnGeneer’ Centre of Excellence, developed in partnership with Microsoft. This CoE aims to increase engineering lifecycle agility by building tools and platforms that integrate automation and GenAI into daily workflows—boosting productivity and design quality.

In parallel, Cyient is collaborating with academic institutions to develop training modules tailored to CAD, CAE, PLM, and electrical system development. These partnerships ensure that workforce skills align with real-world industry needs.

The company has also introduced a Technology Leadership Program, a six-month intensive course aimed at equipping associates with digital competencies to navigate disruption. In addition, over 5,000 associates have been cross-trained in cloud, data analytics, software engineering, and other emerging tech domains.

To embed a culture of continuous learning, Cyient offers access to global trainers, mentoring programs, on-demand modules, and executive education opportunities—ensuring its employees grow both technically and professionally in a fast-evolving digital world.

What are some of the future digital initiatives planned?

Looking ahead, Cyient is focused on scaling digital transformation by advancing its AI and GenAI capabilities across the product lifecycle. One of the major initiatives underway is the development of an Agentic AI Framework—a network of specialized AI agents designed to collaboratively handle complex engineering and operational challenges. These agents aim to operate at ~80% of human efficiency, driving down costs and enhancing speed and quality.

Cyient also plans to expand its CyAI platform, deepening its RPA integration to support tasks like ticketing, troubleshooting, and personalized service delivery for both customers and employees.

Additionally, domain-specific GenAI solutions are being enhanced for use in CAD analysis, BIM modeling, compliance automation, content generation, and aftermarket diagnostics—making AI a seamless part of customer engineering workflows.

In manufacturing and supply chain, the company is scaling autonomous operations through predictive analytics, anomaly detection, and simulation-based optimization. Cyient is also investing in digital twin technologies that blend AI with performance monitoring to improve product development cycles and operational outcomes. By combining deep domain knowledge with AI-first thinking, Cyient aims to empower employees and clients alike with intelligent tools that automate repetitive tasks and enable sharper strategic focus.