In a strategic pivot reflecting the sweeping changes in India’s fintech landscape, Paytm founder Vijay Shekhar Sharma has announced that the company will adopt an “AI-first” approach as part of its next phase of transformation. This declaration comes in the backdrop of reports of significant layoffs across Paytm’s various verticals amid an ongoing restructuring to optimise costs and achieve profitability.
What Vijay Shekhar Sharma Said
Addressing employees this week, Vijay Shekhar Sharma highlighted the critical importance of artificial intelligence (AI) in building efficiency, enhancing user experience, and maintaining a competitive edge in the rapidly evolving digital payments and financial services sector.
“We are transitioning Paytm to become an AI-first company. Our focus will be on deploying AI-led solutions across customer service, risk management, operations, and product innovation to drive efficiency, profitability, and long-term growth.”
His statement indicates a decisive shift towards AI adoption as the fintech giant navigates operational challenges and market pressures.
Background: Layoffs And Restructuring At Paytm
In recent weeks, multiple reports emerged indicating that Paytm initiated layoffs affecting hundreds of employees across lending, payments, operations, and onboarding teams. While the company has not disclosed official figures, market analysts estimate workforce rationalisation between 700-1,000 employees as part of broader cost optimisation and structural streamlining.
Reasons Behind Layoffs
- Profitability Focus: With rising market competition and regulatory tightening, Paytm is prioritising sustainable profitability after years of cash-burning growth.
- Regulatory Constraints: Recent RBI restrictions on Paytm Payments Bank have impacted parts of its operational workflows, leading to rationalisation.
- Technology-Led Efficiency: The AI-first approach will automate several manual-intensive processes, requiring fewer human resources in specific areas.
Paytm’s AI-First Strategy: Key Pillars
1. Customer Service Automation
Deploying AI-powered chatbots and virtual assistants to handle queries, onboarding support, and user grievance redressal efficiently, thereby reducing turnaround time and manual intervention costs.
2. Risk & Fraud Management
Leveraging AI and machine learning to enhance credit underwriting, detect fraudulent transactions in real-time, and improve KYC verification accuracy with computer vision and NLP models.
3. Operations Optimisation
Using AI for workflow automation across reconciliation, settlements, and backend processing, driving cost reduction and scalability.
4. Product Innovation
Integrating generative AI models to build intuitive user interfaces, personalised financial advisory tools, and merchant recommendation engines to deepen customer engagement.
Current Financial Performance Snapshot
| Metric | Q4 FY24 | Q4 FY23 | YoY Change |
|---|---|---|---|
| Revenue | ₹2,470 crore | ₹2,334 crore | +5.8% |
| EBITDA (before ESOP cost) | ₹110 crore | ₹91 crore | +20.8% |
| Net Loss | ₹560 crore | ₹170 crore | -229.4% |
While Paytm continues to report revenue growth and positive EBITDA (before ESOP cost), net losses have widened due to regulatory impacts on its payments bank arm and operational restructuring expenses.
Why Paytm Is Embracing AI Aggressively
- Competitive Pressures: Rivals like PhonePe and Google Pay are expanding into AI-driven merchant solutions, lending underwriting, and business analytics tools.
- Regulatory Tightening: Automating compliance and risk workflows will enable faster adaptation to evolving guidelines from RBI and SEBI.
- Global Benchmarking: International fintech leaders are increasingly adopting AI to reduce costs, personalise services, and build scalable profitability models.
Industry Expert Views
Suresh Ganapathy, Macquarie Capital:
“An AI-first approach is timely for Paytm, but execution will determine its success. The company needs to balance automation efficiency with user trust and regulatory compliance.”
Ritika Gupta, Fintech Analyst:
“The layoffs reflect an industry-wide shift where fintech firms are becoming more disciplined on cost structures. AI adoption, if implemented strategically, can create sustainable margins and differentiated offerings.”
AI Deployment In Fintech: Global Trends
| Use Case | AI Impact |
|---|---|
| Credit Underwriting | Faster, more accurate risk assessment leveraging ML models trained on alternative data |
| Fraud Detection | Real-time anomaly detection reducing transaction fraud rates by up to 80% |
| Customer Service | AI chatbots resolve 60-80% of routine queries, improving customer satisfaction |
| Investment Advisory | Personalised robo-advisory with AI recommendations tailored to user risk profiles |
Recent Strategic Moves By Paytm
- AI Partnerships: Exploring collaborations with AI startups to co-develop underwriting and customer service solutions.
- Product Restructuring: Rationalising non-core offerings to sharpen focus on profitable lending and merchant payments segments.
- Leadership Alignment: Strengthening technology leadership to accelerate AI integration and digital transformation.
Challenges Ahead For Paytm
Despite the promise of an AI-first transformation, Paytm faces significant challenges:
- Regulatory Overhang: RBI’s restrictions on Paytm Payments Bank continue to impact operations and user confidence.
- Talent Management: Layoffs may affect morale and talent retention, especially in key technology and product teams.
- AI Execution Risks: Integration of AI at scale requires robust data governance, model reliability, and explainability to meet regulatory standards.
Paytm’s Vision: AI For Scale And Profitability
In his address, Vijay Shekhar Sharma emphasised that AI is not just a technological upgrade but a foundational shift for Paytm’s future:
“AI will enable us to serve our customers better, build world-class products, and do so efficiently with lower operational costs. This is our path to scale with profitability.”
Investor Sentiment
Following the announcement, Paytm’s shares showed marginal gains amid broader market volatility, reflecting cautious optimism among investors on AI’s potential to enhance operational efficiency.
The Road Ahead
- Short-term focus: Operational restructuring and stabilising core businesses post Payments Bank challenges.
- Medium-term goals: AI-led automation to reduce operational costs, improve margins, and regain market competitiveness.
- Long-term ambition: Build an AI-first fintech ecosystem offering seamless payments, lending, insurance, and wealth solutions to over 300 million consumers and merchants.
Conclusion
Paytm’s pivot to an AI-first strategy marks a critical turning point as it strives to reclaim leadership in India’s fintech ecosystem while navigating layoffs and operational challenges. Whether this technological transformation will translate into sustainable growth and profitability will depend on execution discipline, regulatory navigation, and continuous innovation in a hyper-competitive market.
Disclaimer: This news content is based on publicly available statements, financial data, and market insights. It does not constitute investment advice or a recommendation to buy, sell, or hold any securities. Readers are advised to consult SEBI-registered investment advisors or certified financial professionals before making any investment decisions.
