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Infosys AI Day 1 February 17th, 2026
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Agenda 2 February 17, 2026 Convention Center, Infosys Campus, Bengaluru Session Name Networking Lunch Time (IST) Infosys Living Labs Walkthrough 01:45 – 03:00 PM Speaker Tech transitions – Why is the AI transition different? 11:00 – 11:20 AMNandan Nilekani Chairman of the Board 11:20 – 11:50 AM Salil Parekh Chief Executive Officer and Managing Director AI Services Playbook 11:50 – 12:20 PMSatish H.C. Chief Delivery Officer Infosys Topaz Fabric – AI platform suite 12:20 – 12:30 PMMohammed Rafee Tarafdar Chief Technology Officer Unlocking AI Value – Manufacturing 12:40 – 12:50 PMJasmeet Singh Segment Head – Manufacturing Unlocking AI Value – Financial Services 12:30 – 12:40 PM Dennis Gada Segment Head – Banking & Financial Services Unlocking AI Value – Communication, Media and Technology 12:50 – 01:00 PM Anand Swaminathan Segment Head – Communication, Media and Technology Ashiss Kumar DashUnlocking AI Value – Energy, Utilities, Resources & Services 03:00 – 03:10 PMSegment Head – Energy, Utilities, Resources & Services Unlocking AI Value – Retail, CPG and Logistics 03:10 – 03:20 PMAmbeshwar Nath Industry Head – CPG, Logistics and Retail Partnership Ecosystem for AI value delivery 03:20 – 03:30 PMAnand Swaminathan Segment Head – Communication, Media and Technology The Human-AI Workforce Reimagination 03:30 – 03:40 PMShaji Mathew Chief Human Resources Officer Brand as a Growth Catalyst 03:40 – 03:50 PMSumit Virmani Chief Marketing Officer Summary, Q&A 03:50 – 04:30 PMSalil Parekh Chief Executive Officer and Managing Director Dinesh Rao Chief Delivery Officer Balakrishna D.R. Head – Global Services Jayesh Sanghrajka Chief Financial Officer Title The AI Services Opportunity
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T ech transitions - Why is the AI transition different? Nandan Nilekani 4 Chairman of the Board
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Safe harbor Certain statements mentioned in this presentation concerning our future growth prospects, our future financial or operating performance, our use of AI and its effects on our Business, and the United States H-1B visa program are forward looking statements intended to qualify for the 'safe harbor' under the Private Securities Litigation Reform Act of 1995, which involve a number of risks and uncertainties that could cause actual results or outcomes to differ materially from those in such forward-looking statements. The risks and uncertainties relating to these statements include, but are not limited to, risks and uncertainties regarding the execution of our business strategy, increased competition for talent, our ability to attract and retain personnel, increase in wages, investments to reskill our employees, our ability to effectively implement a hybrid working model, economic uncertainties and geo-political situations, technological disruptions and innovations such as Generative AI, the complex and evolving regulatory landscape including, our ESG vision, our capital allocation policy and expectations concerning our market position, future operations, margins, profitability, liquidity, capital resources, our corporate actions including acquisitions, the outcome of pending litigation, the outcome of the US government investigation, the timing, implementation, duration and effect of the September 19, 2025 proclamation signed by the president of the United States related to the H-1B visa program, and the effect of current and any future tariffs. Important factors that may cause actual results or outcomes to differ from those implied by the forward-looking statements are discussed in more detail in our US Securities and Exchange Commission filings including our Annual Report on Form 20-F for the fiscal year ended March 31, 2025. These filings are available athttps://www.sec.gov/. Infosys may, from time to time, make additional written and oral forward-looking statements, including statements contained in the Company's filings with the Securities and Exchange Commission and our reports to shareholders. The Company does not undertake to update any forward-looking statements that may be made from time to time by or on behalf of the Company unless it is required by law. 5
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Technology has seen fundamental shifts over the years 6 Source: Coatue $500 Bn $5 Tr $50 Tr $500 Tr Global GDP (adjusted $Mn) 1400 1900 1960 2000 2025 Printing Press Electrification & Telegraph Transistors PCs & Internet Mobile Physical, Static Information Digital, Dynamic Operations Cloud GenAI Agentic AI
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Tech innovations have continuously redefined enterprise operations 7 Computerization Internet Access Cloud Access Mainframe Minicomputer PC Client Server Web Computing Mobile Enterprise apps Big data LAN • Digital scalability • Modular business architecture and microservices • Enterprise IT • Globalization and digital reach • Platform-based business models • Enterprise data • Replacement of paper-based workflows • Enterprise systems • Addition of IT operations Enterprise tech transitions
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AI adoption is faster than the earlier tech transitions 8 Years from launch Public data sources 0 5 10 20 1 Bn users AI Smartphones Internet AI – the fastest tech innovation to reach 1 Bn users
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The shift has multiple dimensions 9 AI is not a layer of technology nor is an adjacency Technology Business Talent Operating Model Mental Model • AI-ready systems • AI-enabled data platform • AI-native architecture • Integrated business functions with AI at core • AI-embedded workflows • Scalable AI- augmented workforce • Adaptive learning and change management • Cross-functional knowledge graph • Exponential engineering • Evident-first principle • Responsible AI AI transformation is not a lift and shift; it requires a fundamental root and branch surgery
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Modernization of legacy systems cannot be deferred anymore 10Source: US GAO, Adalo research The true cost of delaying modernization 60-80% of IT budgets spent on outdated systems Financial drain Average breach detection exceeds 200 days in legacy environments Security vulnerabilities Legacy systems act on data silos Innovation paralysis Demand side needs modernization Supply side makes it easier Low agility Tech debt Slow rate of change Cost of security High rate of change Enhanced Security and Compliance Efficient & productive Easily scalable Accumulated tech debt over decades must be paid
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AI as a core of enterprise IT Build vs Buy: balance moves towards build and re- engineering as AI becomes the core 11 23% % of IT spend on AI As of 2025, ~50% of firms have dedicated AI budget Enterprises prefer proprietary agentic layer on top of the foundational models — building customizable to composable solutions Source: Foundry’s AI Priorities study, 2025 Build Customizable Standardized Proprietary Vendor dependency Organic and steady Faster deployment High internal control External control Continuous investment Lock-in & renewals Buy
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AI is evolving at an astonishing speed led by hyper competitive market, large capital access and rapid R&D 12 Innovation cycles are tightening Leaderboards remain in constant motion, driven by a significant rise in AI investments — spending rose from $24Bn in 2023 to $140Bn (E) in 2025. Gemini GPT-4 Claude 2 Mistral-medium 100 Bn+ parameters Gemini 3 Pro GPT-5.2 Claude Sonnet 4.5 Claude Opus 4.5 GPT-5 GPT-5.1 Claude Hiku 4.5 Kimi 2 Thinking Gemini 2.5 Flash Grok 4.1 Deepseek R1 Llama 4 Mistral-3 Gemma 3 Foundation models2023 2025 Source: Github, S&P Global, Medium 10-12 agent frameworks 1 Tr+ parameters 60+ agent frameworks
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The foundational technology is ahead of its diffusion and deployment 13 Benchmark model performance Realized enterprise value The deployment gap Deep learning Frontier models Performance / Value creation Tech progress Source: Snorkel AI progress is outpacing enterprise readiness A widening gap between AI progress and enterprise value
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Talent demand is pivoting from legacy roles to high-growth AI skills 14Source: WEF New/upcoming IT jobs 170 Mn New jobs to be created Fastest declining IT jobs 92 Mn Traditional jobs to be displaced Front-End Web Developers QA Testers IT Support Specialist Blockchain Developers Forward Deployed Engineers AI leads AI Engineer AI Forensic Analyst Data Annotator
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Greenfield AI development is easier than brownfield 15 Legacy environments • Technical debt • Data silos • Undocumented dependencies • Brownfield = high overhead + rework • Deterministic Business function level Only 1% fully scaled to AI The greenfield-brownfield productivity gap Source: Mckinsey, International Center for Law & Economics New build environments • Clean structure and consistent patterns • Real-time data availability • Structured environments • Probabilistic Task level 15-50% productivity Organizational productivity is different from task level productivity
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AI implementation requires laser focus 16 AI’s zero marginal cost of generation AI slops Illusion of productivity Organizational atrophy Structure AI usage guidelines Set clear quality gates for AI content Maintain explainability & traceability Establish AI value capture instead of usage Empower high skilled workforce AI investments are meaningful only if they lead to major productivity gains
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What still matters 17 First Principles thinking Understanding enterprise context Agnostic design Getting the house in order Leadership in effective change Strong collaboration Intense focus on productivity Engineering bent of mind
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18 Thank Y ou
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The AI Services Opportunity Salil Parekh Chief Executive Officer and Managing Director 19
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Clients trust Infosys for their AI Journey 20 “Partnering with leading technology firms like Infosys and leveraging Infosys T opaz Fabric is helping transform how we serve our customers by integrating advanced AI at the core of our operations to deliver more modern, secure, and personalized banking experiences” - Michael Ruttledge, CIO, Citizens Bank “Now, like most companies, we're still early in our AI dream. The real transportation is still to come. But with Infosys, we now have the delivery model, the talent, the platform, and a partner that can move from pilots to meaningful enterprise-wide impact. I'm really excited about what's ahead, and very, very proud to be building it together with Infosys” - Mike Fries, CEO, Liberty Global Infosys provides AI Services to 90% of our large 200 clients “As part of our recently launched Forward ’28 strategy, we announced our ambition to be a leading bank in a digital age. T o support us in this digital and technology transformation, we now enter a strategic partnership with Infosys, a global leader in digital services and consulting. Infosys has the tools, experience, and expertise to support us in accelerating our transformation using cloud and AI technologies.” - Frans Woelders, COO, Danske Bank 20
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Unlock AI Value Data for AI Physical AI INSIGHT INNOVATE Our AI First Value framework is comprehensive 21
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We see six areas of new services opportunity from AI 22 1 AI Strategy and Engineering AI strategy, building AI agents, and orchestrating across platforms, tools and assets 2 Agentic Legacy Modernization Use agents to modernize legacy estates 3 Data for AI Make enterprise data ready for AI models, and drive business insights 4 Process AI Reimagine core business processes using agents 5 Physical AI Design products and embed AI in physical devices 6 AI Trust Ensure responsible and secure AI
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Unlock AI Value Data for AI Physical AI INSIGHT INNOVATE We have successful AI programs at several clients in these areas 23
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Scaling AI First Services 24 AI First Services New offerings in high growth areas 30 offerings 100 sub offerings Humans and agents Enabled by Topaz Fabric and partnerships with AI disrupters
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We help clients create impact with AI 25 Clients’ AI Journey Infosys strengths The Future • Reimagined business and engineering workflows • Modernized tech and data foundations • Secure, scalable operating model Today • Fragmented data • Legacy systems • Talent scarcity Navigate Your Next 1 Deep understanding of client landscape Domain knowledge2 Robust engineering talent 3 Platform & IP4
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The dynamic in AI services 26 AI First services opportunity*: $300 – $400 billion by 2030 Several entities have estimated that AI productivity will lead to compression in IT services revenue AI services led expansion AI Productivity led compression * NASSCOM’s Future of Tech Services 2030 – In partnership with McKinsey & Co.
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Infosys aspires to be the leading partner to “unlock AI value” and deliver business outcomes on revenue growth, cost optimization, and innovation Infosys AI Playbook 27 AI First Services Reinvent existing services to win higher wallet share AI Augmented Services Capture new demand to drive growth Go To Market and Partnership Ecosystem Talent and Culture Platforms and IP Brand equity Vision Pillars Foundation
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Infosys AI Playbook 29 AI First Services Reinvent existing services to win higher wallet share AI Augmented Services Capture new demand to drive growth Go To Market and Partnership Ecosystem Talent and Culture Platforms and IP Brand Equity Infosys aspires to be the leading partner to “unlock AI value” and deliver business outcomes on revenue growth, cost optimization, and innovation Vision Pillars Foundation
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30 AI Services Playbook Satish H.C. Chief Delivery Officer Dinesh Rao Chief Delivery Officer
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Enterprise AI is much more than plug and play 31 C loud
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Enterprise Stack is transforming – Myth vs Reality 32 Enterprise AI Reality State of Enterprise Enterprise AI Myth Amplified Intelligence
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Monetizing the Opportunity 33 Context | Accountability | Growth Pathways Codifying Enterprise Context Agentic Engineering (Infosys Topaz Fabric + Specialist talent) New Domain Stack New Deal Archetypes Human + Agent Workflow Reimagination New Services Stack Unlock AI Value Data for AI Physical AI INSIGHT INNOVATE
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AI First Journey for a Multinational Food Products Company 34 Strategy Oct 2023 Jan 2024 May 2024 Aug 2024 Jan 2025 Apr 2025 Jul 2025 Oct 2025 Reimagine Business Jan 2026 Feb 2026+ Agentic App for Digital Marketplace Shelf Creation Knowledge Agent (Internal + Web) Agentic App for Competitive Brand Intelligence Pilot: Market Research HR Concierge Agent Product Research & Spend Analysis Agents HR Concierge Agent Market Research Procurement Agent Defect Detection (Edge + ML+AI) Food Storage Optimization Agentic App: Inventory Replenishment & Rebalancing AI Governance & Value Office Setup AI for IT Transformation Enterprise AI Architecture Blueprint Value Mgmt. Framework AI Use Case Prioritization AI Risk Assessment Framework AI Governance Policies Knowledge Harvesting & Con- versational AI (text, image, data) Enterprise AI Foundation Setup (Data Fingerprinting, Knowledge Harvesting, AI Governance Gateway, Lowcode Studio) Foundry + Factory Operating Model AI Foundation Enhancements (Agent Canvas, Semantic Caching, Video) 4-6 Week Idea-to-Production Cycle Content Translator Enterprise Rollout FinOps Agent R&D Assist: Recipe Retrieval from 5K Handwritten Documents and connected Research documents 50+ Mn USD New business opportunities 25+ Mn USD Annual savings from efficiency 40+% Business productivity improvement 10+ AI Applications Productionized 2 Weeks Time of Ideation to Beta rollout Build Foundations
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Unlock AI Value Data for AI Physical AI INSIGHT INNOVATE Introducing Infosys AI First Value framework 2 Growth drivers • Enterprise data is not AI ready • Need for high quality data foundations 2 AI Data Strategy AI Ready Data Platform Build AI Grade Data Engineering Indicative offerings • Re-imagining end to end business processes • Domain-aware AI orchestration • Need for holistic interventions for ops, tech and consulting 3 AI Use Case Prioritization Domain Specific Agent Foundry Agentic Extensions Of Func. / Vertical Stacks 35 • AI experimentation to enterprise- scale deployment • Optimize AI infra cost and performance 1 AI Strategy, Roadmap And Architecture Agentic AI Platform Build & Implementation Context Engineering
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Introducing Infosys AI First Value framework Growth drivers Indicative offerings Unlock AI Value Data for AI Physical AI INSIGHT INNOVATE 5 • Accumulating tech debt slowing change • Compelling business case driven by AI T ech Debt Assessment Reverse Engineering & T arget State Design Agentic-led Full-stack Modernization • Cloud AI to real-time intelligence at the edge • Growth of autonomous systems in physical environments 5 Physical AI Strategy AI First Product Design Physical AI Labs, Digital Twins • Agent led autonomy risks • Increasing regulatory and compliance expectations 6 Responsible AI Risk Assessment AI Policy Design AI Governance Services 4 36
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Physical AI at Nova Chemicals 37 Business context Impact AI First Solutions Infosys has brought deep domain & AI expertise through accelerators like Infosys Agri-Chemical AI Cloud in this journey. The components of this solution have enabled manufacturing operations insights & analytical capabilities that position NOVA Chemicals to streamline operations, drive efficiencies, and unlock greater value from its industrial assets. Leveraged Azure Databricks, Azure Foundry, Azure Open AI. Agentic AI solutions deployed NOVA Chemicals is evolving into an AI-enabled, insight-driven industrial enterprise with agentic experiences , smart maintenance advisors, knowledge graphs to accelerate AI development, and GenAI assistants that simplify information discovery. • Increase in planning efficiency • Improvement in asset utilization • Increase in productivity • Faster decision making AI algorithms for diagnostics and prognostics Multi-modal AI – For structured and unstructured operation data Agentic AI to orchestrate multiple maintenance workflows Smart Maintenance Advisor Unlock AI Value Data fo r AI Physical AI
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Agentic Legacy Modernization at Hertz 38 Business context Impact Need for Agility as Critical workflows run on legacy COBOL-based HP Tandem Non-Stop platforms (~3mn lines of code) Strategic objective to migrate to domain-centric Java microservices on AWS Cloud 60% Accelerated modernization timelines 80% Increase of reusable, cross- channel capabilities Unlock AI Value Data fo r AI Physical AI AI First Solutions AI-first modernization strategy to speed code comprehension, reverse engineering, and cloud - ready redevelopment leveraging Open AI, Claude Sonnet and AWS Bedrock Agentic AI solutions deployed AI-powered reverse engineering Infosys iLEAD + GitHub Copilot AI-driven forward engineering AI-enabled testing to validate modern domain- centric architecture 60% Cost reduction in Hosting Services
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39 Thank Y ou
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Infosys AI Playbook 40 AI First Services Reinvent existing services to win higher wallet share AI Augmented Services Capture new demand to drive growth Go To Market and Partnership Ecosystem Talent and Culture Platforms and IP Brand equity Vision Pillars Foundation Infosys aspires to be the leading partner to “unlock AI value” and deliver business outcomes on revenue growth, cost optimization, and innovation
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41 AI Services Playbook Balakrishna D.R. Head - Global Services
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Differentiated services powered by Agentic AI 42 Engineering Services Reimagined Services Migration & Modernization Application Development, Maintenance and T esting Back-Office Operations Powered by Best-in- Class Models and Tools MCP Servers Amplified by Infosys Enterprise Context Topaz Fabric AI Agents & Orchestrators Enterprise Context Graphs Forward-Deployed AI Engineers Delivered by World Class AI Native Talent Continuous Upskilling & Certification Programs Dedicated AI Centre of Excellence (GitHub, Cursor, Devin, etc.) Cross-Domain Expertise (Industry + AI) Package Implementation Models Tools 20+ PLAYBOOKS BEST-IN-CLASS TOOLS 100+ ASSETS 90% AI TRAINED
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Application Development and Support at Microsoft 43 Business context Impact AI First Solutions ▪ Microsoft is transforming the way they engage with their Enterprise Customers through ▪ Unified agreement ▪ Direct selling ▪ Simplified offers ▪ Accelerating the migration to Microsoft Customer Agreement (MCA) is critical for: • Accelerating the sales motion for new age offerings • Reduce sales and operations overhead ▪ Microsoft’s Intelligent Cloud is growing at a rapid rate of approx. 25% YoY Infosys is involved in Greenfield development of new commerce platform to transition to MCA. Infosys also provides mission-critical support safeguarding uptime and trust - key to cloud growth and retention. 2.5x increase in developer velocity 40% Faster incident response 35% improvement in time to market for large features 10x Faster RCA turnaround Agentic solutions: Agentic RCA engine auto-generates incident insights and resiliency recommendations Agentic case triage & routing accelerates classification and reduces manual handling Self-learning model refine accuracy based on analyst feedback AI-driven document feedback provides real-time guidance 1 2 3 4
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AI and Cloud powered transformation at Danske Bank 44 Business context Impact AI First Solutions AI first strategy and governance co -led with Client Chief AI Officer and technology leadership to become AI First Bank setting up AI Innovation Lab and multiple AI solution workstreams. Using agentic AI for software development and reducing technical debt. Agentic / Generative AI solutions HR assist, Credit Risk, Advisor Assistant Enterprise compliant Chat GPT Risk Assessment Ranked No.1 AI Bank in Nordics in the 2025 Evident AI Index <1 min (from 6 min) Reduced Financial Advisors call time 16K+ Employees have adopted Enterprise compliant Chat GPT ▪ Accelerate the bank’s "Forward '28" strategy to modernize technology estate, Improve operational efficiency, and become a leading digital bank in the region 97% GitHub copilot adoption ~2M Lines of AI generated code (accepted) 1 2 3 4
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45 Thank Y ou
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Infosys AI Playbook 46 AI First Services Reinvent existing services to win higher wallet share AI Augmented Services Capture new demand to drive growth Partnership Ecosystem Talent and Culture Platforms and IP Brand equity Vision Pillars Foundation Infosys aspires to be the leading partner to “unlock AI value” and deliver business outcomes on revenue growth, cost optimization, and innovation
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47 Infosys T opaz Fabric - AI platform suite Mohammed Rafee Tarafdar Chief Technology Officer
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Enterprise complexity & AI Scaling 48 Infosys IP & Platforms power the AI runways to scale and realize value faster AI runways required for enterprise adoption & scaling Governance, Guardrails & Explainability by Design Enterprise Context, Twin with Hybrid intelligence Rapid experimentation & innovation infrastructure Evolvable architecture with optionality across AI stack Value driven, end to end reimagined workflow & ways of working
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Infosys Topaz Fabric powering AI at scale 49 AI Models & Framework AI Native Platforms Cloud Infrastructure Business Platforms Data Platforms Enterprise Platforms Services powered by agents and automation workflows Infosys Topaz Fabric provides out of box agents, models and tooling Integration with Client’s Enterprise Landscape & AI Native Platforms Agent SuiteEnterprise Context Process Reengineering Data & AI Services RAI Services AI Strategy & Engineering Data for AI Process AI Agentic Legacy Modernization Physical AI AI Trust 5 SLMs (Enterprise, Banking, ITOps, Cybersec & Code) 600+ AGENTS (IT Services & Domain Specific Agents) 20+ MCP (Connectors to Business, Enterprise, Data Platforms) AI CLOUD (Hybrid AI infrastructure for training & inferencing) 25+ BLUEPRINT (Industry specific AI blueprints and solution accelerators) 155 PATENT (Filed in FY’25 and till FY’26 Jan end) Topaz Fabric (Core & AI Next)
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AI Innovation pillars 50 Applied Research Centre on Agentic AI, Cybersecurity & Physical AI University Collaborations 6 Global Experts 8 Indian Academia Experts Industry Partnerships with LFN, CNCF, TMForum 200+ Startups with 100 AI Innovators 39 Client Living Labs 14 Infosys Living Labs • Innovation Network • Living Labs • Research partnerships
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Platform deployment at a global shipping and logistics group Business context Impact AI First Solutions Complex customer care workflows spanning multiple teams and geographies led to high TAT and operational inefficiency, focus was • End-to-end automation across Customer Care and Operations • TAT reduction to improve customer satisfaction AI solutions deployed: Preference digitization by capturing business and customer rules from tribal/tacit knowledge Platform-led, AI-driven automation deployed across Customer Care workflows (Booking, Bill of Lading, Freight Auditing & Invoicing) across 3 GBS centers operating in 119 countries. 24H → 30m SLA time reduction 0% → 70% STP automated across16 languages 8,000 policies digitized Multilingual free-text AI processing for highly contextual, domain -intensive scenarios Freight auditing & invoicing automation 1.5 Mn transactions orchestrated per month 116 countries transactions processed 1,400 GBS operators enabled Unlock AI Value Data fo r AI Physical AI 51
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52 Thank Y ou
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53 Unlocking AI Value - Communication, Media and T echnology Anand Swaminathan Segment Head - Communication, Media and Technology
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State of AI in CMT - Opportunities & Challenges CSPsSemiconductor OEMs Cloud & Software Media & Ent. Memory & Non-Memory Telcom, Storage & Compute Wireless, Wireline, Satellite Enterprise + Consumer Studios, OTT, Broadcasters MEDIA & TECHNOLOGY 4. Spending Surge: Massive spend in a fierce AI infrastructure race 5. Diffusion and ROI: Limited gains net of reciprocity 6. Innovation: Aggressive need for reinvention to drive up user , partner adoption COMMUNICATIONS 1. Growth Void: Stagnation across B2C, B2B, Edge 2. Sovereignty: Managing "Data Debt" and national resilience 3. Productivity Expectations: High expectations for AI to drive massive efficiency 54
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Top 15 clients account for 60%+ of CMT segment revenues and we are integral to their AI Journey 30% NPS improvement 50%+ reduction in outages ~25% support-cost reduction 30% faster ticket resolution 20–30% productivity gains Faster Resolution Improved Customer Exp. Better Reliability Lower Cost-to-Serve Higher Productivity Gains Customer & Partner Self - Serve & Discovery Predictive Network Ops & AI Network Triage AI-Driven Case Diagnosis, Routing & RCA AI-Automated Service Workflows in Operations AI-Accelerated Engineering Outcomes Use Cases 55 Operations
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Unlock AI Value Data fo r AI Physical AI Business Context Impact * AI First Solutions • 10 million + subscribers • AI is moving from Experiment to Foundation Customer/Agent Assist: Open AI Based Personalized FAQ/chat for self-serve and customer care 1 Super Search: Uses Gemini to make content discovery conversational and intuitive 2 Employee Assist: Co-Pilot based HR & Employee Chat 4 60% Fewer Customers Impacted 100M+ EUR Run Rate Savings 1000+ Annual Platform Deliveries 50%+ Reduction in Outages Tangible Improvements in Customer Satisfaction * Calendar Year 2025 AI Journey with Liberty Global 56 Network Reliability: Enabling faster fault isolation, automated RCA, across heterogenous networks 3
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57 Thank Y ou
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58 Unlocking AI Value - Manufacturing Jasmeet Singh Segment Head – Manufacturing
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Manufacturing players are embracing AI 59 - Ted Ogawa, President and CEO, Toyota Motors NA - Roland Busch, CEO and President - John J. Engel, Chairman, President and CEO Accelerating ERP consolidation, technical debt reduction, cloud adoption to enable AI driven transformation 1 2 Getting massive data sets AI ready: structured, unstructured, time series, streaming, spatial 3 Digital core leveraging AI Process & business model transformation Applying AI for reimagined processes, as a service business model, smart products, smart manufacturing From dashboards to decision support “AI is helping accelerate what we offer our customers, transforming Toyota into the mobility company we need to be to compete in this changing landscape. ” “There was a world before AI, right now we are transitioning to a world that makes full use of it – including in factories, buildings, grids and transportation” “The next phase will focus on advancing new technologies, including artificial intelligence and other digital innovations.”
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AI use cases across value chain Vertical use cases High impact AI use cases across the value chain Predictive demand, inventory & S&OP Smart factory operations & scheduling Accelerated design, simulation & testing Supplier performance & risk intelligence Yield, quality & throughput optimization AI-driven product & portfolio optimization Lifecycle and innovation performance analytics Intelligent procurement & cost optimization Predictive maintenance & asset performance Make Design Source Precision marketing, pricing & lead scoring Sales performance & revenue optimization Intelligent order management & fulfilment Sell Horizontal use cases Enterprise-wide AI deployment Predictive & proactive service operations Installed base & parts lifecycle optimization Customer experience & support intelligence Service 10-20% lower maintenance costs2-7% Margin uplift~30% reduction in cycle time Source: Industry reports and Infosys research Legal Finance HR AI enabled financial close and controls Predictive demand and cash -flow forecasting Intelligent cost and margin analytics Patent Analysis and Monetization Supplier Contract Risk Analysis Automated regulatory and trade compliance monitoring AI Enabled Learning Platform AI Driven Workforce Planning and Scheduling HR Agents for Employees 60
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Process AI and Physical AI at Rolls-Royce Business context Impact AI First Solutions $ Multi Mn Revenue uplift Multi agent framework to augment engineering decision-making across the MRO lifecycle Initiate agent: Feature identification Technical variance matching Scale To be confirmed Speed-up Engine Turn Around Time by improving engineering workloads and compliance-drive workflows Improve first-time-right rates Unlock capacity Intel agent: Cause identification Triage assistance Author agent: Investigation summary Repair procedure assistance 40% Reduction in engineering effort 75% First-time-right (from <40%) “ In partnership with Infosys, Rolls -Royce has successfully operationalized agentic AI within a business -critical MRO process. T his has delivered measurable improvements in Engine turnaround time & engineering efficiency. As an EASA -approved capability, it establishes a trusted found ation for scaling AI adoption across our Civil Aerospace engineering operations “ – Declan Mc Caffrey , Engineering Director , Rolls -Royce 61 Unlock AI Value Data fo r AI Physical AI
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AI Engineering, Process, and Trust at GE Vernova AI First Solutions Use of agentic AI for reimagination of priority value stream workflows, enabling repeatable scaling of AI Agentic AI solutions: Enterprise-wide AI strategy 25+ multi-agent AI use cases Enterprise wide scale up of AI use cases Embedded AI in end to end value streams Unlock AI Value Data fo r AI Physical AI Scott Strazik Chief Executive Officer GE Vernova Justin John AI Strategy & Technology Leader GE Vernova Message from GE Vernova 62
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64 Unlocking AI Value - Financial Services Dennis Gada Segment Head - Banking & Financial Services
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Financial Services is at the forefront of AI adoption 65 In the near term, generative A.I. will drastically improve productivity. Over the long term, it has the potential to revolutionize all functions across our bank and the industry changing how we write code, onboard clients, service customers, detect fraud, develop market research and strengthen compliance and controls. Jane Fraser, CEO To me, the promise of AI is not just efficiency… it’s not just an end in itself. What it does is it makes some of the more routine aspects of people’s jobs easier to accomplish and frees them up to do much more in their internal time faster, better and in a more streamlined way. CS Venkatakrishnan, CEO We’ll be applying more and more of automated intelligence, or augmented intelligence, as we call it, with a person using AI, using that to be more effective, and that’ll affect all the businesses Brian Moynihan, CEO AI outpaces all other tech in growth and budget share, consistently for 2 years, with several AI initiatives already delivering value 1. Increased enterprise spend Shift from siloed focus on cost initiatives to strategic growth priorities, amplified by AI 2. Pivot towards growth AI adoption is not as constrained by use-case discovery, as by the ability to operationalize data privacy, regulatory compliance, and governance 3. Trust, Governance as primary AI Scaling Battleground We are investing in a portfolio of large -scale transformational AI programs designed to increase our operational resilience, enhance the client experience and unlock higher levels of efficiency and effectiveness across the organization Sergio Ermotti, CEO Public Sources
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AI use cases across sub verticals 66 Fraud Detection & Prevention AI Agents scale servicing, sales Voice AI becomes primary interface Consumer Banking RM copilots to multiply coverage AI enabled credit decisioning AI powered treasury & liquidity Commercial Banking AI hardens real- time fraud defense Agent payments and commerce Industrial-scale dispute automation Cards & Payments Always-on KYC for compliance Anomaly Detection for AML & fraud Firmwide AI& Data governance Risk Management & Compliance Advisor copilots productize advice Portfolio Mgmt Insights Automating middle-office flows Asset & Wealth Management AI-native SDLC with Topaz Fabric and Partners e.g. Devin Agentic AI for multi-step business process execution Unified data layers that power enterprise GenAI and SLMs Horizontal use cases Enterprise-wide AI deployment common to all business functions Vertical use cases Function- specific AI deployment
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Re-imagining Citizens Bank 67 Unlock AI Value Data fo r AI Physical.AI Multi-year journey to “re-imagine the bank” and deliver modern, secure, and personalized banking experiences Our AI-first Innovation Hub reflects Citizens’ long-term commitment to building modern, secure, and intelligent banking capabilities. Partnering with leading technology firms like Infosys and leveraging Infosys Topaz Fabric is helping transform how we serve our customers by integrating advanced AI at the core of our operations to deliver more modern, secure, and personalized banking experiences Michael Ruttledge Chief Information Officer and Head of Enterprise Technology & Security at Citizens Bank Business context AI First Solution 1 Industry award in 2025 Modernizing tech delivery and stack E2E customer ops redesign Risk and Analytics Client-facing enhancements Business model simplification Impact $450Mn Cost run-rate savings projected 14 to 1 day SMB onboarding 5x Productivity gains expected 44% Reduction in mobile banking related calls Accelerated platform modernization and AI adoption through full-stack transformation ▪ 700 applications migrated to cloud, exiting on-prem data centers ▪ Established Industry leading cloud native platforms (Fraud1, Customer 3601 etc.) ▪ Driving Gen AI and Agentic AI adoption across the Enterprise ▪ Deploying Topaz Fabric to co-create Gen AI and Agentic AI platform ▪ Scaling Conversational AI adoption for contact center AI Innovation Hub will drive many initiatives to “Re - imagine the bank” – across 5 themes
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AI First services at other leading Financial Services clients 68 • Enterprise AI Platform Buildout • Enabled AI-driven development lifecycle (AI-DLC) with productivity uplift, agentic execution, and end-to-end automated QA. • AI-First Business Process Reimagination: Redefine and implement end-to-end AI-led processes, including KYC, contract analysis, and similar workflows A Top 5 US Bank • Modernization of Cards Platform using Domain-Driven, GenAI and Deterministic Automation • Platform with > 40 Mn lines of COBOL and IMS code; evolved over 40 years • Accelerated the ‘time to market’ by 50% and compressed the effort by 40% • 100% code coverage and functional equivalence A Top 3 Cards Provider • Productivity improvement by 30-50% for Financial Advisors with AI assisted tools. Meeting preparation and summarization time reduced by 60%. • GPT-powered AI assistant for advisors, to query a secure database of 100k+ research documents. • Modernizing legacy code from languages like Cobol at scale • 30-35% ROI from AI investments One of the largest global Wealth Management Firms Infosys Financial Services: Strategic AI Partner for 15 of Top 25 Clients
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69 Thank Y ou
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70 Infosys Living Labs Walkthrough
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71 Unlocking AI Value - Energy , Utilities, Resources & Services Ashiss Kumar Dash Segment Head - Energy, Utilities, Resources & Services
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Rapid adoption of AI across EURS Industries 72 Energy, Utilities & Resources industries are the engines of AI and have a massive impact on this circular economy 1 • Demand Up + Digital Intensity Up - These sectors will grow, but only AI-enabled operators will expand margins • AI is becoming operating system of Industrial Infrastructure – Predictive Ops, autonomous assets, grid automation, sub surface modeling, remote mining, industrial co-pilots etc. • AI is central to ERP-led business transformation programs. 2 Industry outlook Circularity in action • Energy decides AI’s physical scalability • Utilities decide AI’s reliability and sustainability • Resources decide AI’s material availability • Services continues to realize the benefits through inference Utilities power AI and determine where AI can grow and how fast • AI Data centers to consume 10-12% of global electricity by 2030 O&G underwrites global energy supply stability • AI’s computational needs require Natural Gas plants, LNG for grid reliability and load balancing Resources provide the raw materials that AI runs on • Copper, Lithium, Nickel and Cobalt, Rare Earths, Aluminum We are helping EURS clients redeploy OPEX savings into AI transformations. Our leadership position is underpinned by our deep , differentiated domain capabilities , built over decades #AIforEnergy #EnergyforAI
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Infosys is the AI Partner of choice for 15 of our Top 25 clients 73 Data for AI Digital Twins, Autonomous Systems and Edge AI 15+ Clients AI Grade Data Engineering, AI led business insights 20+ Clients Business process redesign, Domain specific agent foundry 20+ Clients Agentic AI Platform Build and Implement 15+ Clients Agentic led full stack modernization, Servitization of Software 15+ Clients Responsible AI, Security Testing and validation 15+ Clients EURS clients see us as their leading partner to “unlock AI value” and deliver business outcomes on revenue growth, cost optimization and innovation Unlock AI Value Data for AI Physical AI INSIGHT INNOVATE
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Impact 18% Y1 improvement in IT Operations efficiency 50% Faster contract validation 95% Payment accuracy AI First Transformation at BP 74 Business context AI First Solutions Enhance enterprise-wide operations by modernizing systems and optimizing workflows across trading, supply chain, retail, sustainability, and operations. Unlock AI Value Data fo r AI Physical AI Established AI leverage points across the energy value chain - refining optimization, dynamic pricing, contract automation, IT operations, and corporate functions. Leveraged Azure Foundry, OpenAI Stack and GitHUb Copilot 50+ AI and agentic AI initiatives, including GitHub Copilot–enabled SDLC acceleration, RAG/LLM- based knowledge automation, AI-led legacy modernization, and digital decision advisors including Trading Finance AI Assistants. “ …We've coupled together Palantir and Infosys to really start to help us drive AI and digitization across the company. I think that's super cool…” - Murray Auchincloss, CEO of bp at the 2025 Investor Call “We are delighted to further develop our relationship with Infosys to help accelerate our digital transformation and scale growth through tech -enabled operations. Together, we look forward to delivering innovative solutions that meet the evolving needs of our customers and drive growth for the future. “ - Leigh-Ann Russell, EVP, Innovation & Engineering, bp
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AI Strategy and Engineering, Data for AI and Process AI at Woodside Energy 75 Business context Impact AI First Solutions 20-35% Efficiency gains in Upstream value chain use cases 15-20% Productivity gains in Employee experience use-cases Unlock AI Value Data fo r AI Physical AI Scale Enterprise-wide AI adoption across Production & Operations, Contracting & Procurement, Finance, HR, and IT Ops 16+ high-value AI use cases were identified for implementation Unified Enterprise AI Platform with GenAI workflows, multi-agent orchestration, and enhanced UI capabilities. Delivered AI solutions across 4 major value vectors: • Asset Operations Assistance Agents • Employee Experience Agents • Intelligence Agents for O&G Analytics • Enterprise Grade Platform - Unified AI Platform Development & Configuration Leveraged Amazon Bedrock Agentic AI for Upstream functions, Azure OpenAI Foundry for corporate functions “The scale-up of our AI pods to 11 or 12 was done in conjunction and partnership with Infosys. We could only hire about ten people locally, but we onboarded over a hundred through our partnership with Infosys. The ability to leverage your brand, expertise and capacity to scale was immensely helpful to us.” — Andrew Maloney, VP Digital, Woodside Energy
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77 Unlocking AI Value - CPG, Logistics and Retail Ambeshwar Nath Industry Head – CPG, Logistics and Retail
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AI is transforming CRL players 78 - Ramon Laguarta, Chairman and CEO - Nicolas Hieronimus, CEO - Willem Uijen, Chief Supply Chain and Operations Officer • LLM-powered Loyalty • Physical-AI powered Perceptive Vision • Agentic Commerce 1 2 • Real-Time Demand Forecasting • Self-optimizing Supply Chains • Net-Zero and Sustainability 3 Retail Consumer Goods • Precision Revenue Growth Management • Hyper-personalized Marketing • AI-powered Planogram Compliance Logistics “We are embedding AI throughout our operations to better meet the increasing demands of our consumers and customers” “New technologies like GenAI, agentic AI, are redefining what beauty means to consumers and how they experience it…” “We see technology as the next frontier to make existing processes better and more efficient, and to do things that were simply impossible before.”
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Process AI and Data for AI at Ralph Lauren Business context AI First Solutions Use of conversational and personalization AI to transform high-intent customer queries into curated, shoppable experiences powered by real-time inventory, leveraging Microsoft stack Conversational AI styling assistant (“Ask Ralph”) enabling natural-language product discovery Personalization at scale, generating curated recommendations Real-time inventory integration Impact 12.2% YoY revenue increase 50% Increase in engagement driven by styling and outfit discovery • Needed to reimagine how consumer shops online creating experiences similar to interactions with stylists in physical stores • Styling and outfit curation rely on manual merchandising, restricting personalization at scale • Disconnected inventory data limited the ability to convert real-time, shoppable recommendations to sales Unlock AI Value Data fo r AI Physical AI Scaling ‘high-touch’ service in luxury physical stores on mobile device 79
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Agentic Legacy Modernization and Process AI at Posti Business context Impact AI First Solutions 50+% Software code developed by agents AI-first operating model across Run and Transform Run-to-Grow transformation, reallocating spend from maintenance to growth capabilities AI orchestrator layer leveraging best-of- breed AI solutions, including (GitHub, AWS BedRock, LangChain, Copilot) 35% Improvement in productivity Legacy IT estate driving key business issues: • High run-costs • Operational risk • Slow change cycles Critical need to execute a strategic pivot toward end-to-end logistics and e-commerce services 70% Improvement in mean time to recovery Unlock AI Value Data fo r AI Physical AI As we navigate the next phase of our evolution with enterprise AI, with Infosys, Posti will not only become a leader in the logistics and e -commerce sector, but a true digital frontrunner in the Nordics” - Petteri Naulapaa, SVP and CIO, ICT and Digitalisation Posti Group 80
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Infosys AI Playbook 82 AI First Services Reinvent existing services to win higher wallet share AI Augmented Services Capture new demand to drive growth Go To Market and Partnership Ecosystem Talent and Culture Platforms and IP Brand Equity Vision Pillars Foundation Infosys aspires to be the leading partner to “unlock AI value” and deliver business outcomes on revenue growth, cost optimization, and innovation
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83 Partnership Ecosystem for AI Value delivery Anand Swaminathan Segment Head - Communication, Media and Technology
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AI Partnership Ecosystem MODEL LAYER CLOUD ENTERPRISE AI APPLICATIONS DATA LAYER ENTERPRISE APPLICATIONS INFRASTRUCTURE COMPUTE PLATFORM DOMAIN SPECIALISTS SECURITY AND GOVERNANCE PHYSICAL AI 84
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Examples of Joint GTM (1/3) AI Strategy & Engineering PARTNERS AI ADOPTION 30% 30% 80% 40% THEME 30% Bringing AI to Life Data for AI 50K AI-ready Fabric data core , cutting 50,000 reports to 1,200 insights driven by Copilot at a major rail road company 92% Accuracy in processing Text, Tables and Images of 20000+ HTML & PDF files through Multi modal RAG at a major Telco. Enterprise Data Platform (EDP): Built on Databricks Delta Lake at a retailer Faster onboarding process with Infosys AI Next; reputation and financial Risk Reduction at a large Financial Services client Effort saved for a logistics major in order booking using Infosys AI Next. 5X improvement in Turnaround Time reduction in operating costs through 4000+ Gen AI user actions/month at a major furniture retailer Scaled agentic AI at a major Telco major to power AI Chatbot across sales, service and operations – 80% faster response, Improvement in NPS using Agentic AI Voice Entertainment Super Search at a telco major Shifting from linear productivity to exponential at Infosys, AI-powered delivery - unified 40,000+ repositories on GitHub & activated 25,000+ engineers with Copilot Azure OpenAI Conversion efficiency driven by GenAI -driven Spark SQL conversion. Migration of complex ~2M -line Hadoop/Spark codebase to Snowflake at a regional bank. 85% Azure OpenAI LLM 85
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Examples of Joint GTM (2/3) PARTNERS AI ADOPTIONTHEME Process AI 400K+ Invoices automated per year; autonomous finance operations by AI Agents at a Restaurant chain 1st Organization to deploy a live AI led Sales Development Representative (SDR ) agent on Agentforce at a Nordics major Annual reports and 1K+ product filings automated saving 30% compliance effort at an Insurance major 350+ GenAI-driven content curation using LLM to classify data for all published articles and stories . Unlocking productivity improvement for editorial team at a publisher Bringing AI to Life Agentic Legacy Modernization P A R T N E R S A I A D O P T I O N 30-40% Reduced cycle time 1M Mainframe lines of code modernized with iLead (leveraging AI models) at a car rental company AI-first Agri-Chem Industry Cloud :- 40–65% increase in forecast accuracy, 30% increase in planning efficiency, 30% energy reduction. Reimagined enterprise software delivery leveraging agentic AI: Lower toil, faster remediation, policy compliant automation at scale at a regional bank 1000+ Developers Reimagined enterprise software delivery and transformed engineering productivity leveraging agentic AI: Higher throughput, lower cycle time, governed autonomy at a leading manufacturer 250+ Developers Azure OpenAI Azure OpenAI OpenAI LLM OpenAI 86
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AI Trust Secure-by-design AI Trust foundation : Protected data and IP while scaling AI & embedded RAI controls at a leading beverage company Physical AI Autonomous smart store solution through AI -powered computer vision & video analytics -based solutions Planogram compliance, store traffic analysis, inventory mgt. Reimagined retail experience and transformed in -store productivity leveraging AI technologies: Higher accuracy, lower labor needs Azure OpenAI Examples of Joint GTM (3/3) PARTNERS AI ADOPTIONTHEME Bringing AI to Life LLM 87
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Infosys AI Playbook 89 AI First Services Reinvent existing services to win higher wallet share AI Augmented Services Capture new demand to drive growth Go To Market and Partnership Ecosystem Talent and Culture Platforms and IP Brand Equity Vision Pillars Foundation Infosys aspires to be the leading partner to “unlock AI value” and deliver business outcomes on revenue growth, cost optimization, and innovation
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90 The Human-AI Workforce Reimagination Shaji Mathew Chief Human Resources Officer
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AI Talent Transformation Strategy 91 1 2 3 Talent Operating Model Talent Career Model Talent Development Model Ambidextrous Organization Y AI First Talent Transformation Strategy
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Talent Operating Model 92 Building an Ambidextrous Organization Specialist Programmers, Power Internships Bridge Programs 2X Full-Stack Engineers Assessment COE, Capability Quotient (CQ) Enhanced focus on Domain Expertise Business Incubator Series External Hiring Internal Development
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Talent Career Model 93 Integrated Future-Ready Dual Pathway Career Structure Current Structure Continues to drive stability, specialization at scale Smaller % constitutes specialist roles Deep skills (Engineering / Domain / Functional) Enhanced Role-Based Organization (Core) Expertise-Led Organization (Accelerator) ManagementExecution AI led Execution Flat Structure – Drive expertise led innovation, and client value Experts – Domain / Technology Evolving Structure
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Talent Development Model 94 AI Builder AI Enabled AI Master Build contextual AI platforms & IP Develop tools and interfaces Leverage AI tools Boosts productivity and decisions Drive AI adoption Set vision, governance, & culture Forward Deployed Engineers Embed AI in client environment Integrate, deploy, and scale
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In Summary 1 2 3 Talent Operating Model Talent Career Model Talent Development Model Ambidextrous Organization Y AI First Talent Transformation Strategy We are building deep engineering and domain expertise We are redesigning career architecture to future proof the organization We are developing a future ready workforce leveraging our global best-in- class learning infrastructure 95
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Infosys AI Playbook 97 AI First Services Reinvent existing services to win higher wallet share AI Augmented Services Capture new demand to drive growth Go To Market and Partnership Ecosystem Talent and Culture Platforms and IP Brand Equity Vision Pillars Foundation Infosys aspires to be the leading partner to “unlock AI value” and deliver business outcomes on revenue growth, cost optimization, and innovation
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Mindshare Leads Market Share 98 Brand as a Growth Catalyst Sumit Virmani Chief Marketing Officer
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The Mathematics of Strong Brands 99 Greater Growth & Higher Shareholder Value Source: ‘Building Lasting Brand Equity in the Age of AI’ 2025 by Boston Consulting Group +2pp Revenue Growth -0.4% 1.4% +2pp -0.5% 3.4% +4pp Low budget share on brand High budget share on brand +4pp Total Shareholder Value Source: Kantar BrandZ 2025 Most Valuable Global Brands And they Consistently Outperform the Market
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When a Billion Hearts Beat With Infosys AI
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Infosys: Fastest Growing IT Services Brand Globally 101 Source: Brand Finance: Infosys 2026 Brand Value Results Infosys Brand Value ($Mn) Infosys brand value grew at 15% CAGR over 6 years 12,777 13,010 14,213 16,338 16,413 7,087 8,402 2020 2021 2022 2023 2024 2025 2026
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An Industry Leading Enterprise AI Brand 102 17 36 45 10 20 30 40 50 2023 2024 2025 AI Client Voice (Infosys) Number of Unique Clients 890 808 928 1549 1734 1347 0 500 1000 1500 2000 Q1 Q2 Q3 FY25 FY26 AI Thought Leadership (Infosys) Total AI Global Volume (#) 70% 72% 73% 67% 65% 65% 74% 72% 73% FY26 Q1 FY26 Q2 FY26 Q3 Global IT Peers Indian IT Peers Infosys AI Association (Top 10) Source: Enterprise AI Top 10 Brand Study (Infosys)
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Industry Analysts Acknowledge That As Well 103 Topaz (FY26 YTD) Digital (FY26 YTD)
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Brand Mathematics is Showing up in Business Too 104 Revenue growth CAGR (FY 20-25) Others Infosys Source: 20 IT Services Companies Business Performance 4.6 8.6 0 1 2 3 4 5 6 7 8 9 10 Revenue share FY25 Incremental market share (FY20 -25) 93.4% 6.6% 87.7% 12.3%
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The Next Frontier Data for AI Physical AI INSIGHT INNOVATE UNLOCK AI V ALUE=
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107 Summary and Q&A Salil Parekh Chief Executive Officer and Managing Director Jayesh Sanghrajka Chief Financial Officer
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Summary 108 Comprehensive AI services offerings1 Large opportunity2 Large enterprise clients trust Infosys3 We are working with clients in each of the AI services areas4 We have a strong platform5 We have deep engineering talent and culture6 We have built strong partnerships7 Go to market plan for our large clients8 9 We are a leading brand
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Unlock AI Value Data for AI Physical AI INSIGHT INNOVATE AI First Value framework 109
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