Job Displacement in Routine Roles:
Graduates employed in repetitive, data-driven roles (e.g., data entry, customer service, basic bookkeeping, or administrative tasks) face the highest risk of displacement. AI tools can automate these tasks exponentially faster and at lower costs.
Example: In banking, entry-level roles like transaction processing or loan document verification could be automated.
Upskilling Demand:
AI will elevate the value of skills like data analysis, AI/ML development, cybersecurity, and digital literacy. Graduates who adapt to AI-driven workflows (e.g., learning Python, AI tools like ChatGPT, or data visualization platforms) will remain competitive.
Shift Toward Hybrid Roles:
Jobs will evolve from manual execution to AI oversight, ethical supervision, and decision-making. For instance, auditors may shift from sifting through paper to interpreting AI-generated risk models.
Polarization of the Job Market:
Entry-level and mid-skilled jobs may shrink, while demand for high-skilled roles (e.g., AI engineers, ethicists, and compliance specialists) grows. Graduates unable to reskill may face unemployment or underemployment.
How Organizations Use AI to Reduce Expenses
Organizations can cut costs by automating labor-intensive, low-value tasks and reallocating human resources to strategic roles. Key strategies include:
1. Automation of Repetitive Tasks
Customer Service: AI chatbots handle routine queries, reducing reliance on human agents.
Document Processing: AI extracts and categorizes data from invoices, contracts, or tax forms.
Compliance & Auditing: AI identifies anomalies in financial data faster than manual audits.
2. Predictive Analytics
AI identifies operational inefficiencies (e.g., fraud detection in banks or cash flow gaps in accounting firms).
3. Scalability Without Proportional Hiring
Once deployed, AI systems handle increased workloads without additional costs (e.g., servicing millions of banking customers via chatbots vs. hiring thousands of employees).
Example 1: AI in a Bank
O
Cost-Saving AI Use Case:
Bank deployed AI-powered chatbots (e.g., “OnChat”) to handle customer inquiries about account balances, loan eligibility, and transaction histories. This reduced the need for 24/7 human customer support staff.
Traditional cost: ~2.5 lakh/month for 20 agents (assuming 12,500/agent).
AI cost: One-time investment of 15–20 lakhs for chatbot development + maintenance.
Result: Annual savings of ~27 lakhs and faster response times.
Additional AI Integration:
Bank uses AI for fraud detection, analyzing transaction patterns to flag suspicious activity. This reduces the need for large compliance teams to manually monitor transactions.
Example 2: AI in a Chartered Accountants Firm
Organization: A mid-sized CA firm in Mumbai (hypothetical case)
Cost-Saving AI Use Case:
The firm adopts AI-powered software like QuickBooks Advanced or Xero with inbuilt AI to:
Automate Invoice Processing: AI extracts data from client invoices, matches them with purchase orders, and flags discrepancies.
Generate Financial Reports: AI compiles monthly/annual reports for small businesses, reducing the need for junior accountants.
Traditional cost: Hiring 3 junior accountants at 4 lakhs/year = 12 lakhs/year.
AI cost: Subscription to AI software (~1 lakh/year) + oversight by 1 senior accountant.
Result: Annual savings of ~11 lakhs and reduced human error.
Potential Risks:
Lower-tier jobs (e.g., data entry clerks) are eliminated, but demand rises for roles managing AI systems (e.g., interpreting AI-generated tax recommendations).
Balancing Cost Savings and Social Responsibility
While AI drives cost efficiency, organizations must address its societal impact:
AI will reshape India’s workforce, disproportionately affecting graduates in routine roles while creating demand for high-skilled positions. For organizations like banks and CA firms, AI offers significant cost savings by automating tasks such as customer service, fraud detection, and financial reporting. However, failure to invest in reskilling and ethical AI adoption risks widening unemployment gaps and stifling social mobility. The future hinges on collaborative automation—where AI augments human creativity and empathy rather than replacing it.