New Delhi, Sep 12 (UNI) Indian industries can balance rapid AI adoption with legacy limitations by taking a step by step and pragmatic approach. Instead of replacing entire systems, companies can overlay AI using modular tools, middleware and data adapters that integrate with existing infrastructure, Hemant Jain, president of PHD Chamber of Commerce and Industries (PHDCCI) told UNI.
“The first step must be getting the basics right—digitizing invoices, inventory, and connectivity—so that useful data is available for AI. For MSMEs, lightweight AI-as-a-service models delivered through cloud subscriptions or industry platforms can provide affordable entry points. Alongside technology, industries must also prioritize change management and workforce skills to ensure adoption.”
On regulation, Jain said, “The perceived paradox between AI regulation and innovation can be resolved through first principle based guardrails that allow flexibility. Regulations should focus on core principles such as transparency, safety, and accountability rather than stiff prescriptions."
“Mechanisms where companies can test high-impact AI applications under supervision, allow innovation while managing risk. Co-regulation is another path, where industry associations and government work together to frame technical standards and codes of conduct.”
Highlighting the sectors poised for transformation, he noted, “Over the next five years, AI will drive the deepest transformation in sectors such as IT and IT-enabled services, financial services, logistics, healthcare, and advanced manufacturing. In finance for example, AI can strengthen underwriting, risk management, and fraud detection.”
“Logistics and warehousing will benefit from automation, while healthcare and pharma will leverage AI for drug discovery, diagnostics, and supply chain efficiency. On the other hand, traditional informal services, artisanal crafts, and some public utilities may lag due to lack of resources.”
“India today has strong advantages in software engineering talent, cost competitiveness, and IT services delivery, but it lags advanced economies in areas like high-end chip design,” Jain said on global competitiveness.
“Despite these gaps, AI offers India a major opportunity to reposition itself in global value chains. By moving up from labour-based outsourcing to providing AI-enabled services and solutions—such as domain-specific models, enterprise SaaS, and localized AI applications—India can boost exports significantly.”
On ethics, he said “Industries must strike a balance between the commercial imperatives of scaling AI and the ethical dilemmas of bias, accountability, and job displacement by embedding governance into their deployment strategies.'
“A risk-tiered approach is useful—high-impact applications in health, credit, or legal services should face stricter transparency, audits, and human oversight, while lower-risk applications can scale more freely.”
Addressing small businesses, Jain said, “MSMEs really are the backbone of Indian industry, but we agree that the cost and complexity of AI often keep them from taking full advantage of it. What we see ahead is a wave of AI solutions built with small businesses in mind, lighter, more affordable, and focused on everyday problems like improving cash flow, managing supply chains, or reaching new customers.”
“This is where industry bodies like PHDCCI can make a real difference. We can help by spreading awareness, creating partnerships between MSMEs and technology providers, and pushing for supportive policies that lower the barriers to entry. Just as importantly, we can encourage collaborative models, shared platforms, open tools, and training programs that make AI less intimidating and more practical.”
“AI should not just be for big corporations. It must be within reach of every entrepreneur who wants to grow, no matter the size of their business. That is how India’s MSME sector can truly unlock the benefits of this technology.”
On jobs, he added, “Rather than focusing only on reskilling, Indian industries must redesign workforce strategies to align with the new job ecosystem AI will create. New roles will emerge in areas such as data stewardship, AI model operations, human-in-the-loop processes, and domain-specific analysis.”
On data sovereignty, Jain concluded, “AI models are only as strong as the data that feeds them, which makes industrial data a strategic asset. Indian industries must navigate this carefully by classifying data into categories—critical industrial IP, personal data, and non-sensitive operational data—so that governance rules can be applied proportionately.
“At the same time, industries cannot afford to be cut off from global supply chains; cross-border data flows should therefore be governed by risk-based mechanisms like contractual clauses, approved transfers, and encryption standards. The goal should be sovereignty—protecting critical datasets while enabling India’s global competitiveness.”
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