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The Emerging Talent Requirements for the AI Era
The Emerging Talent Requirements for the AI Era
With continuous innovation and advancements in AI and related technologies, their applications in the financial services industry provide a vast scope for further innovation in products, customer servicing and operations. End-to-end automation of processes and personalisation with better understanding of customer behaviour and emotions would be feasible. Regulation and compliances will also undergo significant changes, and ethical functioning of businesses would be a challenge that AI has to address.
In this context, there would be a radical change in the talent required for the industry. Some of the existing roles will become redundant and some of them will exist, but new or additional skill sets would be required. Additionally, new talent with these skill sets would also be required. An estimated 2.5 lakh permanent jobs would be created by 2030, driven by growth in Tier II/III cities in the Indian BFSI sector as per Adecco India Report 2025.73 Let us examine the changes in the talent landscape of the financial services industry in Tables 5.5 and 5.6.
Table 5.5 Evolving Roles in the BFSI Industry
| Functional Area | Roles Likely to Disappear / Evolve | Drivers of Change | New / Emerging Roles | Description / Key Skills Needed |
|---|---|---|---|---|
| Retail & branch banking | Branch tellers; manual cashiers | UPI/QR, digital onboarding, branch-lite models | Digital relationship banker (AI-augmented) | • Manages customer portfolios via video banking & AI copilots • Skills in digital Know Your Customer (KYC), conversational banking & cross-sell through analytics |
| Retail & branch banking | Traditional customer service executives | Chatbots, WhatsApp banking, virtual assistants | Omnichannel customer experience manager | • Orchestrates service across chat, voice, app & branch • Skilled in journey mapping, Net Promoter Score and escalation via AI insights |
| Lending & credit | Manual loan officers; |
field verifiers
AI underwriting, eKYC/video KYC, account aggregators
Digital credit & risk analyst (AI-scored)
• Uses AI-driven credit models, alternative data & account aggregator consent flows
• Must know model interpretation & bias checks
Physical collections agents
Digital collections, behavioural nudges
Digital collections & recovery strategist
• Runs AI-driven repayment nudges, segmentation, and digital collection journeys
• Behavioural science + data ops
Payments & cards
Card-focused product managers
Wallets, UPI, tokenisation, central bank digital currency
Real-time payments product manager
• Designs instant payment journeys, cross-border UPI, ISO 20022 flows and value-added services on real-time payments rails
POS device sales staff
SoftPOS, QR, tap-on-phone
Merchant experience & acceptance lead
• Builds value for micro-, small and medium enterprise merchants with SaaS + payment bundles
• Requires go-to-market, merchant analytics & fintech UX skills
Wealth management & investments
Traditional relationship managers for high-net-worth (relationship-only)
Robo-advisory, fractional investing, AI portfolios
Hybrid wealth adviser (human+AI)
• Combines personalised advisory with AI portfolio modelling
• Skills in behavioural finance, systematic investment plan/systematic transfer plan strategy and digital advisory tools
Paper-based research analysts
GenAI research, real-time market intelligence
AI-enabled investment research curator
• Aggregates & validates AI-generated research
• Ensures compliance, explainability & risk disclosures
Insurance (life, health, general)
Field agents reliant on manual onboarding
Digital issuance, embedded/affinity insurance, API-led
Embedded insurance partnerships manager
• Builds insurance APIs into e-commerce, travel, mobility & fintech platforms
• Partnership & product bundling skills needed
Manual claims processors
AI image/video claims, telematics, IoT
Claims automation & fraud intelligence lead
• Uses AI/machine learning for claims triage, anomaly detection & fraud rings
• Domain, data science and forensics skills
Risk, compliance & fraud
Document-heavy compliance officers
Regulatory technology (RegTech), continuous compliance, AI monitoring
RegTech & compliance automation specialist
• Deploys tools for automated KYC/anti-money laundering
• Conducts model risk testing
• Ensures regulatory reporting accuracy
Manual anti–money laundering analysts
AI + network graph-based anti–money laundering
Financial crime & threat intelligence analyst
• Uses network analytics, open-source intelligence & typology modelling to detect complex laundering & cyber financial crime
Technology, data & cybersecurity
Traditional IT support roles
Cloud-native BFSI, AI copilots, automation
AI banking product engineer
• Builds AI-powered workflows, copilots for staff & customers
• Needs LLM usage, prompt engineering & domain knowledge
Data entry/reporting staff
Automated reporting, Reserve Bank of India/Securities & Exchange Board of India/Extensible Business Reporting Language API filings
Banking data product owner
• Owns data models, lineage, access & quality
• Bridges tech, compliance & business using data mesh principles
Traditional cybersecurity analysts
Identity-first, zero-trust, API fraud
Cyber-fraud & identity security architect
• Designs zero-trust, identity-proofing, API and device-risk analytics
• Deep security and fraud prevention skills
Corporate & institutional banking
Relationship manager roles focused on relationship-only
Platform banking, API-ecosystem models
Corporate banking solutions adviser
• Helps corporate clients digitise finance ops with API cash management, supply chain finance & treasury automation tools
Manual trade finance officers
Blockchain, electronic bill of lading, trade digitalisation
Digital trade & supply chain finance specialist
• Manages e-documentation, tokenised assets, cross-border trade rails
• Knowledge in International Chamber of Commerce rules & digital trade platforms
Product, strategy & innovation
Product managers with slow-release cycles
Open banking, A/B experimentation, fintech competition
Bank-fintech ecosystem strategist
• Designs co-create models with fintechs
• Manages APIs, revenue-share constructs
• Strong partnership & regulatory navigation
Traditional analysts (deck/report-led)
Scenario AI & data-led strategy
AI-enabled business strategy analyst
• Uses data, simulation & GenAI to model scenarios
• Ensures governance & strategic prioritisation clarity
HR, learning & workforce
HR generalists (policy/admin)
Skills-based orgs, talent analytics
BFSI workforce & skills architect
• Designs future skill maps, capability academies, AI upskilling & role transition journeys across BFSI
Classroom-only trainers
AI learning, microlearning, simulations
Immersive BFSI learning and development experience designer
• Builds compliance + sales training using simulations, AR/VR & adaptive learning
• Learning science + design tech
Operations & shared services
Large operations back-offices (manual processing)
Automation, AI copilots, workflow orchestration
Banking automation & copilot orchestrator
• Designs human+AI work allocation systems
• Reduces manual load
• Improves turnaround & compliance
On-shore only ops teams
‘Follow the Sun’ and nearshore and gig experts
Distributed operations network manager
• Manages multi-site ops with productivity, quality & risk
• Cross-cultural operations leadership skills required
Source: Curated with inputs from ChatGPT
Table 5.6 Understanding the New Roles in the BFSI Industry
| New Role | Why This Role Is Emerging (Key Drivers) | Primary BFSI Segments | Key Skills Needed |
|---|---|---|---|
| AI model risk & ethics officer (financial services) | AI in credit, underwriting, surveillance requires fairness, explainability & ethical guard rails | Banks, non-banking financial companies (NBFCs), insurers, fintech | • AI governance, model risk • Reserve Bank of India/ISO ethics guidelines |
| Digital public infrastructure product architect | India Stack, Open Network for Digital Commerce, Open Credit Enablement Network, UPI account aggregator ecosystem | Banks, fintech, neo-banks | • Digital public infrastructure protocols • API design • Ecosystem partnerships |
| Embedded finance partnership designer | BFSI products embedded into e-commerce, mobility, health, agri & small and medium enterprise workflow | Banks, insurers, NBFCs | • Platform strategy • API economy • Co-creation models |
| Financial generative pre-trained transformer/SLM trainer for financial services | Need for domain-trained SLMs for BFSI |
Banks, fintech AI labs, RegTech
• Data annotation
• Prompt engineering
• BFSI domain
Tokenised assets & digital securities specialist
Rise of tokenised bonds, funds, real-world assets, central bank digital currencies (CBDCs)
Investment banks, asset management, exchanges
• Blockchain, tokenisation
• Custody, compliance
CBDC product & ecosystem manager
Rollout of digital rupee & CBDCs for cross-border corridors
Banks, fintech, central bank programmes
• CBDC rails
• Wallet UX
• Offline payments
• Security
Financial behavioural science strategist
Behavioural nudging in collections, saving, investing, fraud prevention
Banks, insurers, wealth, NBFCs
• Behavioural economics
• Data experiments
• Nudging
AI-powered hyper-personalisation designer
1:1 personalised finance experiences at scale
Retail banking, wealth, insurance
• Data science
• Personalisation engines
• Customer psychology
Green finance & ESG lending analyst
Climate-linked loans, ESG scoring of borrowers & investments
Banks, development finance, funds
• ESG frameworks
• Climate finance
• Impact metrics
Financial wellness & money coaching adviser
Rising middle-class stress, need for financial well-being
Banks, neo-banks, HR partnership programmes
• Human coaching and digital tools
• Behavioural finance
Cyber-fraud threat intelligence analyst
Sophisticated fraud rings, deepfake scams, mule networks
Banks, cards, payments, fintech
• Open-source intelligence
• Network analytics
• Crypto-fraud detection
Risk tech & RegTech solution integrator
Automated compliance and regulatory reporting tech adoption
Banks, insurers, NBFCs
• RegTech tools
• Automated KYC/anti-money laundering
• API/regulatory mapping
Credit-in-the-cloud product owner
Credit products built as micro-services and cloud workflows
Banks, fintech, lending platforms
• Cloud credit stacks
• Account aggregator data
• Bureau and alt-data modelling
Super-app financial services curator
Cross-selling BFSI inside lifestyle super-apps
Fintech, payments, telcos
• Product bundling
• Ecosystem business development
• Urban+vernacular strategy
Digital trust & consent steward (BFSI)
DPDP Act, data portability & consent-based finance
Banks, insurers, wealth management firms
• Consent UX
• Privacy engineering
• Data policy
Gig-economy & creator wealth solutions designer
New income models needing new credit, insurance & tax solutions
Banking, insurtech, wealthtech
• Product innovation
• Segment insights
• Creator economy
Climate & catastrophe risk data scientist
Climate risk as a core banking and insurance risk driver
Insurance, reinsurance, banks
• Climate models
• Geospatial, actuarial and machine learning
Insurance parametric product specialist
Parametric products triggered by events (rainfall, flight delay, crop)
General insurance, insurtechs
• Parametric design
• Satellite/IoT data
• Actuarial innovation
Small and medium enterprise embedded credit stack developer
Lending inside small and medium enterprise, enterprise resource planning systems, POS, agri, supply chain workflows
Banks, NBFCs, agri/microfinance institution/lending tech
• API lending
• Cashflow underwriting
• Workflow UX
Wealth-as-a-service (WaaS) platform manager
White-label wealth infra for non-banks & brand platforms
Wealthtech, asset management companies, fintech infra providers
• Partner management
• Modular productisation
• Compliance mapping
Crypto/DeFi risk & compliance analyst*
Web3 and crypto-linked transactions (where permitted)
Crypto exchanges, banks (per regulation)
• DeFi
• On/off-ramp risk
• Travel rule compliance
*Adoption of crypto roles depends on country-specific regulatory stance in Asia.
Leadership Imperatives for the Service Industry in the AI Era
Given the impact of change that is beginning to happen in the services industry due to internal or external forces as a result of continuously evolving technology trends, leadership would have to adapt and steer the businesses in very different ways as compared to the earlier times as can be seen from Table 5.7. While the core of leadership would have to continue to be centred on people, inspiring them to attain higher levels of performance to keep pushing the boundaries of growth and profitability, it has become critical for leaders to have an in-depth understanding of technology and AI trends. In this ability lies the current and the future potential of the business. Success is no longer measured by how many customers are served but by how smartly customers are served in real time with personalisation.
The success metrics in the traditional bank would have been branch expansion to improve customer service, whereas in the AI-led banking system, customer touch points and servicing would be through deployment of intelligent chatbots. The founder of Walmart, Sam Walton, focused on cost control through economies of scale. Presently, the focus of Doug McMillion and Satish Meena, the CEO and AI strategy head of Walmart, respectively, is around the ‘Intelligent Retail Lab’ aimed at data-driven store optimisation. Isadore Sharp, the founder of Seasons Hotels, centred his business on treating guests and employees alike with dignity and respect, whereas now Seasons Hotels has adopted virtual concierge bots and machine learning models to predict guest preferences for providing customised experiences. In summary, traditional leaders in the service industry built human-driven cultures with process orientation, whereas in the AI-led era, successful leaders are combining data insights with the human touch to foster algorithm-driven empathy.
Table 5.7 Service Industry Leadership in the Traditional vs AI-Led Era
| Dimension | Traditional Service Industry Leadership | AI-Era Service Industry Leadership |
|---|---|---|
| Decision making | Hierarchical and experience-driven; relies on intuition and past performance | Data-driven, agile and model-assisted; uses AI analytics for predictive insights and adaptive decision-making |
| Leadership style | Transactional or transformational; focused on people management and customer service quality | Techno-empathetic and ecosystem-oriented; blends emotional intelligence with algorithmic intelligence |
| Organisational structure | Vertical hierarchies with clearly defined roles and standard operating procedures | Networked and decentralised; relies on cross-functional, AI-augmented teams and autonomous decision nodes |
| CRM | Manual and relationship-based; personalised service delivered by staff | Hyper-personalised and algorithmic; AI agents predict and fulfil customer needs proactively |
| Performance metrics | Efficiency, customer satisfaction and compliance | Innovation velocity, data accuracy, ethical AI use and customer lifetime value driven by personalisation |
| Innovation approach | Incremental and process-based improvements (lean, Six Sigma) | Continuous and generative; AI enables rapid prototyping, automation and new service models |
| Talent & skills focus | Soft skills, domain expertise and operational know-how | Digital fluency, AI literacy, prompt engineering and human–machine collaboration capabilities |
| Leadership development | Mentorship, experiential learning and hierarchical promotions | Continuous reskilling via digital platforms; flatter growth paths with AI-enabled performance analytics |
| Culture & values | Stability, trust and service consistency | Agility, experimentation, ethical governance and transparency in AI usage |
| Risk management | Focus on operational and financial risks | Focus on algorithmic bias, data privacy, cybersecurity and reputational risks linked to AI outputs |
| Employee engagement | Employee motivation through interpersonal leadership | Human–AI co-working engagement; leaders motivate teams to trust AI while retaining creative autonomy |
| Customer experience leadership | Frontline managers lead through hospitality and empathy | AI experience designers and ‘customer experience scientists’ lead through predictive personalisation and digital empathy |
| Success definition | Stable growth, loyal customers and consistent brand image | Scalable innovation, adaptive resilience and sustainable differentiation through AI insights |
练习题
Which statement best summarises how AI is expected to affect financial services innovation and talent requirements?
A bank is replacing branch-lite cash transactions with video banking, AI copilots, digital KYC and analytics-based cross-selling. Which emerging role most directly fits this shift?
Which emerging role is most associated with AI underwriting, eKYC/video KYC, alternative data, account aggregator consent flows, model interpretation and bias checks?
Which options correctly match a driver of change with an emerging BFSI role? Select all that apply.
Which statements correctly describe emerging roles in risk, compliance, fraud, technology and data? Select all that apply.
AI is expected to make regulation, compliance and business ethics less important in BFSI because automated systems remove the need for oversight.
The Indian BFSI sector is expected to create an estimated lakh permanent jobs by , driven by growth in Tier II/III cities.
In wealth management, the emerging role that combines personalised advisory with AI portfolio modelling is the ___.
Explain why some BFSI roles may disappear while other roles may continue but require new skills in the AI era.
How do emerging BFSI roles in payments, insurance and corporate banking show that AI and digital technologies are creating new business models rather than only automating old tasks?
A bank wants to launch an AI-enabled wealth service that gives customers personalised investment suggestions in real time based on their goals and risk profiles. Which emerging role is the best fit for leading this service?
Which of the following emerging BFSI roles are most directly connected to AI-based fraud prevention, identity verification, or compliance automation? Select all that apply.
Because AI can enable end-to-end automation and personalisation, the AI era in financial services will only remove jobs and will not create any significant new permanent roles.
The emerging role of is closely linked to the use of AI for continuous monitoring of customer financial behaviour and for sending proactive repayment nudges in lending.
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