Dual role of AI in security—both as a tool for protection & a vulnerability

The panel discussion "How Indian IT Services Can Lead in the AI Revolution" was moderated by Dhaval Gupta, Director, Cyber Media India Ltd. The panelists were Niraj Kumar, VP & Head – IT, Sinch; Faizul Mufti, Vice President – Information Security, Genpact; Irshad Saifi, Director IT & Digitization (CDIO), Amarchand Shardul Mangaldas and Baidyanath Kumar, CISO & Data Protection Officer, J K Lakshmi Cement. 

The panel discussion brought together industry experts to discuss the evolving role of AI, security, and data in enterprise transformation. The conversation revolved around key challenges and opportunities in AI adoption, security concerns, and the crucial role of data governance in shaping the future of digital businesses.

The Growing Need for Agility, Scalability, and Security

One of the dominant themes discussed was the increasing demand for agility, speed, and scalability in enterprise solutions. As organizations integrate AI into their workflows, they are also focusing on revenue margins and operational efficiency. However, security remains a primary concern, with businesses seeking to leverage AI not only to drive outcomes but also to safeguard their models against threats.

Experts highlighted the dual role of AI in security—both as a tool for protection and a potential vulnerability. Ensuring robust security measures for AI models is crucial to building confidence and ensuring compliance with industry requirements.

AI in Manufacturing: The Road to Smart Transformation

The manufacturing sector is undergoing a shift with Industry 4.0 and beyond. AI-driven smart manufacturing is gaining traction, but it comes with its own set of challenges, including developing industry-specific AI models and ensuring their security. The integration of AI in manufacturing demands a strategic approach to application development, IT operations, and cybersecurity.

A key discussion point was the need to invest not just in AI applications but also in the underlying infrastructure that supports them. Participants debated whether organizations should build proprietary AI models or rely on existing solutions, weighing factors such as cost, expertise, and scalability.

The Role of AI in Business and Service Delivery

Organizations are actively investing in AI-powered SaaS (Software as a Service) platforms to deliver efficient solutions to customers. Many enterprises are adopting general-purpose AI models while also developing specialized models tailored to industry-specific needs, such as finance, healthcare, and supply chain management.

AI is streamlining processes, reducing inefficiencies, and enhancing customer experience. However, panelists emphasized the importance of a structured approach to AI adoption, broken down into three phases:
1. Planning & Strategy – Identifying relevant areas for AI implementation and making strategic build-or-buy decisions.
2. Development & Training – Synthesizing data, training AI models, and ensuring accuracy.
3. Deployment & Optimization – Gradual implementation with a focus on scalability and continuous improvements.

Data Quality and Governance: The Backbone of AI Success

AI’s effectiveness is heavily dependent on data quality. Panelists stressed that structured, well-integrated data is key to predictive analytics and decision-making. Manufacturing and other industries need to focus on data integration across systems to derive meaningful insights.

Additionally, data security is a pressing issue, with organizations investing in governance models to mitigate risks. Companies are increasingly adopting AI-driven data governance strategies, ensuring transparency, accountability, and compliance. Segmentation of customer data was highlighted as a best practice to prevent breaches and maintain trust.

AI and Cybersecurity: Building Resilient Enterprises

Cybersecurity remains a major focus as organizations deploy AI-driven solutions. Despite significant investments in security, enterprises continue to face evolving threats. Experts suggested integrating AI with cybersecurity frameworks to enhance threat detection and response capabilities.

Governments and enterprises are also working towards regulatory frameworks that balance AI innovation with security. Panelists advocated for stronger public-private collaboration, government support for cybersecurity startups, and a well-defined policy landscape to foster AI-driven growth.

The Future of AI: Innovation with Responsibility

The discussion concluded with a call for responsible AI adoption. Organizations need to embed AI governance policies at both corporate and operational levels. Regular audits, awareness programs, and ethical AI practices should be prioritized to ensure AI is used effectively and responsibly.

As AI continues to evolve, enterprises must navigate challenges while capitalizing on opportunities. By focusing on security, data governance, and strategic implementation, businesses can harness AI’s full potential while mitigating associated risks. The insights from the conclave provide a roadmap for enterprises looking to accelerate their digital transformation journeys.

(Report By Bharti Trehan)