September, 2025 Confidential and proprietary © 1Lattice Foreword The rapid evolution of Generative AI (GenAI) marks a defining moment in the trajectory of artificial intelligence. Once a domain of academic exploration and speculative fiction, GenAI now stands as a transformative force reshaping industries, economies, and societies. With capabilities that span natural language processing, image generation, music composition, and synthetic data creation, GenAI is revolutionizing how we create, communicate, and solve complex problems. This report by 1Lattice provides a comprehensive point of view on the GenAI landscape—exploring its foundational technologies, diverse applications, and far-reaching implications. It highlights not only the tremendous opportunities GenAI offers for innovation, economic growth, and social progress but also the ethical and regulatory challenges that demand urgent and thoughtful attention. Abhishek Maiti Director-Technology & Internet, From healthcare breakthroughs and Industrial goods & services personalized education to workforce transformation and digital inclusion, GenAI is poised to deliver unprecedented value. Yet, responsible adoption will be key to unlocking its full potential. As organizations navigate this new frontier, we hope this report serves as a strategic guide—informing decisions, sparking dialogue, and encouraging the responsible deployment of GenAI for inclusive and sustainable progress. Executive summary • AI has potential to impact global economy by Overview of Generative AI US$ 17.1 -25.6T by CY23-40, driven by new use cases technologies & enhanced worker productivity • Generative AI, a field of AI, creates human-like text, images, audio, & even code using various models , Background & evolution of each with unique content generation methods. It Generative AI can be broadly classified into six different types : • GenAI's evolution began in the mid-20th century - Variational Autoencoders (VAEs): Generate from ML algorithms in the 1950s to ELIZA (1960s), Deep synthetic data for training other AI models Blue (1997), Siri (2011), GPT (2018-& Voicebox(2023) - Generative Adversarial Networks (GANs): • Leading tech companies have developed advanced Generate realistic synthetic images & videos AI systems & tools, some of the notable ones are: - Autoregressive models: Creates coherent & - OpenAI: Dall-E, ChatGPT, Sora contextually relevant text - DeepSeek: V3, R1 - Recurrent Neural Networks (RNNs): Processes & generates sequential data like text & speech - Google: Vertex AI, Gemini, Gemma - Transformer-based models: Generate - Microsoft: GitHub Copilot, Copilot Studio, Muse high-quality, coherent text - Reinforcement learning for generative tasks: Challenges & opportunities Creates content based on user feedback & preferences • GenAI can lead to regulatory challenges including • GenAI is transforming industries by streamlining issues with IP rights, data privacy, AI governance, processes, personalizing experiences & improving ethical use, & concerns over misinformation & safety, thus driving efficiency & productivity gains deepfakes across sectors like retail & e-commerce, hospitality, • Key ethical considerations in GenAI include bias in automotive, education, fashion & others algorithms, privacy, transparency, social impacts, • GenAI is driving diverse innovation across factual accuracy, & cybersecurity risks industries, from content creation & drug design to • Use of GenAI represents significant economic workflow optimization & organizational opportunities for the Indian economy through transformation sectoral growth, with education, employment, & skill development Product in Spotlight: 1Insights Powered by 1Insights, our latest report, potential of GenAI while addressing critical “Generative AI: Shaping the Next Era of challenges such as ethical considerations, Technology and Innovation”, offers an in-depth regulatory frameworks, and workforce perspective on one of the most transformative transformation. technological advancements of our time. The 1Insights, our cutting-edge intelligence platform, report explores how GenAI is revolutionizing continues to empower business leaders with industries from enhancing productivity and actionable insights and future-ready strategies. driving innovation to reshaping business With advanced analytics, real-time forecasting, models and unlocking new opportunities. and deep sector expertise, 1Insights equips Backed by robust data, global benchmarks, organizations with the clarity and confidence to and expert analysis, the report decodes the lead in an AI-driven future. Glossary Terminology Description Occurs when gradients become too Vanishing small as they propagate from output to gradient problem earlier layers, complicating training Non-human-created data that mimics Synthetic data real-world data, but is artificially generated using algorithms & simulations Involves evaluating & assessing risk to Underwriting determine the terms & conditions for process issuing insurance or loans Gap between regions with access to modern information & communications Digital divide technology (ICT) & those with limited or no access Gradient-based algorithm used to Backpropagation train artificial neural networks (ANNs) in ML & AI Incorporating uncertainty & Probabilistic randomness into decision-making decision processes Finds groups in data by transforming it Support vector into higher dimensions & using key data clustering points (support vectors) to define clusters Models that split data into branches Decision trees based on feature values to make predictions or decisions An ensemble of decision trees that Random forest combines their predictions to improve accuracy & robustness Statistical language modeling approach Neural Probabilistic that uses artificial neural networks to Language Model learn the probability of word sequences (NPLM) in a sentence Computational models that simulate Biomolecular structure & behavior of biological molecules, such as proteins & DNA, to models study their functions & interactions Tailored sequences of tasks or Custom processes designed to meet specific workflows requirements © 1Lattice 05 01 OVERVIEW OF GENERATIVE ARTIFICIAL INTELLIGENCE Definition & types of Generative AI [1/3] 1 Generative AI , a field of AI, creates human-like text, images, audio, & even code using various models, each with unique content generation methods What is GenAI? Types of GenAI • Generative AI (GenAI) encompasses various Variational Autoencoders (VAEs) models & techniques to produce new & • Encode data into latent space, decode it to original content that resembles reconstruct original data, learn statistical human-created data, including: representations 2 - Text generation: Models like GPT -3 & • Generate new samples from this learned ChatGPT can generate human-like text, like distribution, useful in image, text, & audio articles, stories, scripts, & code in response generation to user prompts Recurrent Neural Networks (RNNs) - Image generation: Tools like DALL-E can • Process sequential data & predict next element , create unique images from text struggle with long sequences due to vanishing descriptions gradient problem - Audio & video generation: Can create 3 4 • Advanced variants like LSTM & GRU address this synthetic audio, music, & video content limitation for improved sequence generation - Synthetic data generation: GenAI models Generative Adversarial Networks (GANs) can generate realistic synthetic data for training other AI systems • GANs use generator to create fake data & discriminator to tell real from fake, competing in game-like setup • This process allows GANs to generate highly realistic content like images, art, & videos Transformer-based models • Transformers use attention mechanisms to model 5 relationships in sequences effectively for NLP & generative tasks • Handle long sequences efficiently, making them ideal for generating coherent & contextually relevant text Autoregressive models • Generate data sequentially , conditioning on previously generated elements, & predict next element's distribution to generate new data • Used in models like GPT for coherent text generation Reinforcement learning for generative tasks • Generates data by receiving rewards or feedback based on quality of samples through agent-environment interaction • Used in tasks like text generation, it fine-tunes outputs based on user feedback 1 2 3 4 5 Note(s): Artificial intelligence, Generative Pre-Trained Transformers, Long short-term memory, Gated recurrent unit, Natural language processing Source(s): Industry reports & articles, 1Lattice analysis © 1Lattice 07 Definition & types of Generative AI [2/3] GenAI models include applications like content creation, diagnosis, immersive experiences, & language understanding across text, image, audio, & video domains Types Application Impact Industry use case • Generate realistic • Accelerate content • StyleGAN synthetic images & creation & production • Imaginaire Generative videos • Improve medical Adversarial • RunwayML • Enhance medical diagnosis accuracy Networks imaging & diagnosis • Enable more immersive (GANs) • Can develop virtual & engaging virtual worlds & environments experiences • Genrate synthetic data for • Reduce the need for large • TensorFlow training other AI models labeled datasets Probability Variational • Can compress & • Enable more efficient data • Pyro Autoencoders reconstruct storage & transmission • PyTorch (VAEs) high-dimensional data • Improve the performance • Model complex probability of downstream AI models distributions • Create coherent & • Enhance conversational • OpenAI’s GPT contextually relevant text AI & chatbots • WaveNet • Predict the next element • Automate content • T5 Autoregressive in a sequence creation & summarization models • Model long-range • Improve language dependencies in data understanding & generation • Process & generate • Power speech • TensorFlow sequential data like text & recognition & synthesis • OpenAI’s GPT speech • Improve forecasting & Recurrent • Wavenet • Model temporal prediction in various Neural Networks dependencies in time series domains (RNNs) data • Enable interactive & • Enable real-time generation responsive multimedia of audio & video experiences • Generate high-quality, • Enhance machine • OpenAI’s GPT coherent text translation & language • BERT understanding • Translate between Transformer- • Gemini based models languages • Automate content creation & summarization • Summarize long documents • Improve performance on a wide range of NLP tasks • Create content based on • Enable personalized & • OpenAI’s gym user feedback & engaging content • SageMaker preferences generation Reinforcement • ReAgent learning for • Optimize generation for • Improve the quality & generative specific objectives or relevance of generated tasks constraints content over time • Adapt generation to user • Enable interactive & interactions & adaptive generation preferences systems Source(s): Industry reports & articles, AI Company’s websites, 1Lattice analysis © 1Lattice 08 Definition & types of Generative AI [3/3] Artificial intelligence evolves into machine learning, deep learning, & Generative AI, each adding greater autonomy, complexity & content creation capabilities Artificial intelligence (AI) Machine learning (ML) • Techniques that equip computers • ML is a subset of AI which uses to emulate human behavior advanced algorithms to detect patterns in large data sets • Enable computers to learn & make decisions • Allows machines to learn & adap • Recognize patterns effectively • ML algorithms use supervised or unsupervised learning methods • Solve complex problems akin to human intelligence Artificial intelligence Machine learning Deep learning Generative AI Deep learning (DL) Generative AI (GenAI) • DL is a subset of ML that uses neural • GenAI is a subset of DL models that networks for in-depth data generates content like text, images, processing & analytical tasks or code based on provided input • Leverages multiple layers of • Trained on vast data sets, these artificial neural networks models detect patterns & create outputs without explicit instructions • Extracts high-level features from raw input data • Uses a mix of supervised & unsupervised learning • Simulates how human brains perceive & understand the world Source(s): Industry reports & articles, 1Lattice analysis © 1Lattice 09 02 APPLICATIONS AND IMPACT Examples of applications & impact GenAI transforms industries by streamlining processes, personalizing experiences & improving safety, thus driving efficiency & productivity gains across sectors Industry GenAI application examples Impact • Generates synthetic medical data • ~70% of healthcare organizations, including 1 Healthcare payers, providers, & HST groups, are • Personalized treatment planning adopting or have implemented GenAI • Automates administrative tasks • Optimizes production processes • ~77% of executives see GenAI as pivotal ; ~71% plan adoption within two years, • Predicts machinery failures Manufacturing highlighting manufacturing’s • Enables efficient collaboration transformative potential between humans & robots • Fraud detection & risk assessment • ~85% of financial institutions view GenAI as Finance & transformational; ~26% are significantly • Streamlines underwriting processes banking investing in it • Transforming decision-making in financial sector 2 3 • Creation of novel music, videos & • ~65% M&E CXOs believe that GenAI would animations help in revenue acceleration & ~45% of 4 Entertainment CXOs claim that CEOs are driving GenAI • Immersive gaming experiences agenda • Streamlines content creation & enables dynamic storytelling • Property visualization & design • ~80% of real estate companies are optimization increasing their technology budgets to Real estate integrate GenAI solutions • Virtual tours • Streamlines real estate processes • Personalized shopping experiences • ~52% ofusers replaced search engines with Retail & GenAI for product recommendations & • Demand forecasting & dynamic pricing e-commerce purchase • Supply chain optimization • Personalized guest experiences • Hospitality & tourism leaders focusing on new tech, like customer-centric GenAI, • Revenue management Hospitality could boost revenues by ~25% • Predictive maintenance & operational optimization 5 • Optimizes vehicle design & • Numa claims integrating its chatbot can performance speed up repair order approvals 5x & Automotive increase customer satisfaction by ~16% • Predicts maintenance needs • Autonomous driving capabilities • Personalized learning content creation • ~42% of primary & secondary teachers have used GenAI for schoolwork • Virtual tutoring Education • Administrative task automation • Creative design & textile generation • Gen AI projected to add US$ 150-275B to apparel, fashion & luxury operating profits • Personalized shopping & virtual try-ons Fashion in 3-5 years • Anti-counterfeiting measures 1 2 3 4 Note(s): Healthcare services & technology, Media & entertainment, Chief experience officer, Chief executive officer Source(s): Industry reports & articles, Industry surveys, 1Lattice analysis © 1Lattice 11 Potential benefits for innovation GenAI drives diverse innovations across industries, from content creation & drug design to workflow optimization & organizational transformation Content generation • GenAI excels in generating text, images, music, & molecules*, exemplified by GPT-4 & DALL-E 2 • In pharmaceuticals, GenAI aids in faster, cost-effective drug design by companies like Generate Biomedicines & Iktos Workflow efficiency • GenAI optimizes workflows & automates tasks , as seen with Roche using synthetic medical data for clinical research • Freshworks uses ChatGPT to accelerate software development, showcasing GenAI's efficiency in industrial processes Marketing transformation • GenAI transforms marketing with personalized content creation , such as Zalando's deepfake videos for customer engagement • Coca-Cola uses ChatGPT & DALL-E for tailored ad & images, showcasing GenAI's impact on marketing effectiveness & consumer relationships Organizational redefinition • GenAI redefines roles & improves coordination within firms, like IBM's recruitment chatbot handling 700 daily queries • Heineken integrates GenAI in agile transformation, boosting collaboration & operational agility across departments & partners New frontiers • GenAI pioneers new artistic & scientific realms like art, music, literature, & generative chemistry • Drives innovation with tools like Midjourney for images, Riffusion for music, & ChatGPT for automated marketing content Note(s): *Chemical compounds whose structures are designed or optimized using GenAI technologies Source(s): Industry articles, 1Lattice analysis © 1Lattice 12 Potential benefits for economic growth AI is projected to impact GDP & has potential to impact global economy by US$ 17.1 - 25.6T, driven by new use cases & enhanced worker productivity Higher GDP impact in U.S. & Western Europe; limited gains in developing regions Impact of AI investment on GDP (%, CY23-33) 1.9 1.7 1.5 1.4 0.9 0.8 0.7 0.6 0.6 0.4 0.3 0.1 USA Western Central Southern MENA* Sub-Saharan Europe & Eastern Europe Africa Europe Impact on GDP Impact on GDP (conservative scenario) (widespread adoption scenario) GenAI could unlock incremental value beyond traditional AI & analytics AI’s potential impact on global economy (US$ T, CY23-40) 2.5-4.5 2.6-4.4 17.1 -25.6 13.6 -22.1 11.0-17.7 Advanced New Total use All worker Total AI analytics, GenAI use case- driven productivity economic traditional ML & cases potential enabled by potential deep learning GenAI, including use cases Note(s): *Middle East & North Africa Source(s): Industry reports & articles, 1Lattice analysis © 1Lattice 13 Potential benefits for societal advancements GenAI accelerates drug discovery, enhances education, promotes sustainability, improves disaster response & bridges digital divide, boosting social mobility Potential benefits for societal advancements Improved healthcare outcomes GenAI is accelerating drug discovery, improving clinical-trial planning & execution, & leading to more precision medicine therapies Enhanced education & learning experiences ~65% of educators recognize the potential benefits of GenAI in enhancing learning experiences, offering personalized education, & interactive engagement Advancements in sustainability & environmental protection Drives sustainability & innovation by boosting efficiency & enabling renewable energy solutions across industries Bridging the digital divide Boosts social mobility by bridging the digital divide, providing access to well-paying jobs, reducing wage disparities, & distributing productivity gains across society Workforce transformation GenAI integration reshapes workforce dynamics, displaces some roles, demands new skills, drives reskilling & upskilling, cultivates agility & capability Enhanced disaster response & resilience Analyzes data for better disaster preparedness & response, coordinating emergency efforts & supporting communities effectively Source(s): Industry articles, 1Lattice analysis © 1Lattice 14 03 GROWTH & DEVELOPMENT Milestones in research & technological advancements From ML algorithms in 1950s to ELIZA (1960s), Deep Blue (1997), Siri (2011), GPT (2018-20) & Voicebox (2023), GenAI has hit key milestones GenAI's evolution, beginning in the mid- 20th century, including key research & technological milestones 2022 -2023 2023 2024-2025 Released in 2022, ChatGPT MusicGen is a transformer model Rise of Grok -3/4 with 3.5 rapidly gained that generates music from text or advanced reasoning & popularity, reaching 180M audio prompts, while Meta's multimodal capabilities; users by Nov 2023, & Voicebox is an advanced model DeepSeek -R1 emerges drawing 1.5B monthly for text-to-speech, audio editing, as a cost-efficient, visitors to openai.com stylizing, & sampling open-weight GPT-4 rival 2021 -2022 2018-2020 2017 2016 Microsoft's DALL -E & Open AI’s GPT series , NVIDIA's Progressive GANs Google DeepMind DALL -E2 , which can based on transformer generate high- resolution developed WaveNet,a generate original, architecture, a game synthetic images for generative model that high-quality images changer in language various applications, produces natural- from language prompts generation tasks including healthcare & sounding speech entertainment 1997 Early 2000s 2003 2011 st st IBM's Deep Blue, a chess ML models matured 1 neural Apple's Siri , 1 computer, defeated with support vector probabilistic AI / NLP voice world champion Gary clustering, decision language model assistant, made Kasparov, marking a trees, random forest, & was developed, GenAI widely pivotal AI breakthrough other advanced revolutionizing accessible algorithms for sentence-level word supervised learning prediction in NLP 1980s Mid 1960s 1956 Early 1950s 1 RNNs pioneered MIT created ELIZA , Logic Theorist, ML exploration with advanced generative first NLP-powered an automated algorithms began, models with backprop chatbot using reasoning program , focusing initially on agation, learning pre-programmed was among the rules-based patterns & making responses pioneering efforts systems to mimic probabilistic decisions that laid the human reasoning foundation for GenAl & decision-making 1 Note(s): Early natural language processing program Source(s): Infosys BPM, Industry reports, 1Lattice analysis © 1Lattice 16 Key contributors & breakthroughs in the field [1/2] Leading tech companies have developed advanced AI systems & tools, including OpenAI, DeepSeek, Amazon (Bedrock, Q), Meta & Apple BREAKTHROUGH Contributor Launch year Description Tools Efficiently generates images from text , saving time, costs, & resources 2021 OpenAI Dall-E versus traditional methods Generates human-like text for content creation, Q&A, conversations, 2022 ChatGPT & explanations Create videos featuring highly detailed scenes & complex 2024 Sora camera motion from text instructions Fast, general-purpose model for tasks like writing, summarization, DeepSeek 2024 V3 translation , or casual Q&A Reasoning-focused model for math, coding, research , or any task 2025 R1 that requires step-by-step logical thinking Helps users train, build, & manage AI models Google Vertex AI 2021 Provide human-like responses to text, image, & audio prompts Gemini 2023 Smaller, efficient AI model demonstrating high performance with Gemma 2025 reduced computational resources Help with a variety of tasks, including data analytics , GenAI, & inference NVIDIA NVIDIA AI 2006 NVIDIA NeMo Allows developers to build, customize, & deploy GenAI models / / NVIDIA 2022 Enables building biomolecular models with pre-trained models, BioNeMo custom workflows, & criteria-based molecule generation Allows software developers & service providers to create & deploy NVIDIA 2024 visual content models Picasso Streamlines coding for faster, easier development, enhancing focus on Microsoft GitHub 2021 problem-solving & collaboration Copilot Graphical environment for building AI copilots with advanced dialog Copilot 2023 creation, knowledge integration, actions, & built-in analytics for Studio Microsoft conversational AI tools Microsoft’s 1 st GenAI model designed for gameplay ideation, can Muse 2025 generate game visuals & controller actions Amazon Amazon 2017 Allows developers to create, train, & deploy ML models on the cloud SageMaker 1 Fully managed service that makes high-performing FMs from leading Amazon 2023 2 AI startups & Amazon available for use through a unified API Bedrock Helps developers & IT professionals with coding, testing, upgrading Amazon Q 2023 applications, diagnosing errors, performing security scans, fixing issues, & optimizing AWS 3 resources Source(s): Company websites, Industry articles, 1Lattice analysis © 1Lattice 17 [2/2] BREAKTHROUGH Contributor Launch year Description Tools Seamless Meta Family of AI research models that aim to make communication 2023 communication across languages more natural & authentic models Help users with social connections , such as making plans, Meta AI 2024 sparking conversations, & getting recommendations Family of LLMs, offering enhanced natural language understanding Llama 3 2024 & generation capabilities Virtual assistant that uses voice recognition & AI to perform tasks Apple Siri 2011 on Apple devices including answering questions, sharing information, control devices, get directions & other tasks Personal intelligence system for iPhone, iPad, & Mac that uses Apple 2024 generative models & personal context to provide highly useful & Intelligence relevant insights Computer system capable of answering questions posed in IBM Watson 2010 natural language Commercial GenAI & scientific data platform based on cloud; offers Watsonx 2023 a studio, data store, & governance toolkit, supports multiple LLMs Open-source, enterprise-grade AI model designed to deliver Granite 3.0 2024 state-of-the-art performance while maximizing safety, speed, & cost-efficiency for business applications 1 2 3 Note(s): Foundation models, Application Programming Interface, Amazon web services Source(s): Company websites, Industry articles, 1Lattice analysis © 1Lattice 18 04 CHALLENGES & OPPORTUNITIES Regulatory challenges Regulatory challenges for GenAI include issues with IP rights, data privacy, AI governance, ethical use, & concerns over misinformation & deepfakes Intellectual property (IP) rights • High chance of violating IP rights when using AI trained on copyrighted data as it might create duplicated content • Difficulty in establishing ownership & rights for AI-generated content poses a major regulatory challenge Data privacy & protection • Training GenAI on extensive datasets, including sensitive information, requires robust data privacy measures 1 2 • Regulations like GDPR & CCPA impose stringent rules on data handling to protect user privacy AI governance 3 • Global rules , such as the EU AI Act place strict requirements on high-impact AI models to tackle new AI issues • Multiple regulations can create inconsistencies & increase costs , putting small developers at a disadvantage Ethical use of AI • Ensuring AI doesn’t produce biased or unfair results is crucial, as training on biased data can create negative societal biases • Training AI on inclusive data & maintaining transparency in operations are essential for preventing discriminatory outcomes & building trust Misinformation & deepfakes • GenAI can create highly realistic but fake content , including text, images, & videos • Poses a significant risk to information integrity & can facilitate the spread of misinformation & deception 1 2 3 Note(s): General Data Protection Regulation, California Consumer Privacy Act, European union Source(s): Industry articles, 1Lattice analysis © 1Lattice 20 Ethical considerations Key ethical considerations in GenAI include bias in algorithms, privacy, transparency, social impacts, factual accuracy, & cybersecurity risks Bias in AI Social algorithms implications Biases in GenAI systems can Misuse of GenAI can cause produce discriminatory outputs economic disruptions & worsen & lead to inequitable outcomes existing social challenges Cybersecurity & Factual accuracy & misinformation tampering risks GenAI models can lack precision GenAI amplifies cybersecurity & be less accurate due to their challenges, introducing sophisticated predictive nature phishing attacks & deepfakes Transparency & Regulations for accountability data privacy Complexity of GenAI systems often Ensuring compliance with regulations results in lack of transparency in their like GDPR & EU AI Act crucial for decision-making processes, which protecting sensitive data & respecting can lead to diminished trust & public individual privacy accountability Source(s): Industry articles, 1Lattice analysis © 1Lattice 21 Economic opportunity Sectoral growth, with education, employment, & skill development, represent significant economic opportunities for Indian economy through use of GenAI • Indian government is developing a WhatsApp Sector wise growth chatbot with ChatGPT integration, recognizing value of GenAI 1 • ~69% of India's GDP growth through • GenAI can transform agriculture into a more GenAI will come though business & precise, & efficient industry, leading to increased financial services , education, retail, productivity & profitability & healthcare sector • Manufacturing, wholesale & retail trade industries are potentially the biggest contributors (~55%) to Research & development economy-wide gains from GenAI, as 3 these comprise a large share of the • In last 20 years , AI research has led local workforce & account for high to significant innovations , labor productivity including advancements in big 2 data, robotics, medical research, & • ~ 60% of IT leaders are planning to autonomous vehicles implement GenAI in their organizations to boost efficiency & • By CY27, GenAI is expected to productivity autonomously generate ~ 15% new mobile applications, without human intervention • ~ 80% of CEOs believe GenAI has Employment & skill potential to significantly enhance development business efficiencies within their organizations • ~44% of workers ' core skills are expected to change in the next five years . Training employees to leverage Education GenAI will be crucial • ~1% of Indian workforce will use GenAI • ~65% of educators recognize the for more than ~ 20% of their work potential benefits of GenAI in • ~45% of Indian workforce will use enhancing learning experiences, GenAI for ~ 5-20% of their regular offering personalized education, & activities in interactive engagement • GenAI has potential to help Indian • NITI Aayog, CBSE, Intel India workers save ~51M hours a week by 4 launched the AIoT program in CY26 CY22 to integrate GenAI & tinkering into pedagogies at 50 schools, 5 aligning with NEP of FY20 Agriculture • AIoT program aims to equip teachers with skills to integrate AI • GenAI enables farmers to access into teaching, enhancing student learning & preparing them to use agronomic data facilitating AI responsibly near-real-time decisions on ▪ soil treatments ▪ seed varieties ▪ market conditions • KissanAI utilizes GPT-3.5 & Whisper models, handling ~40K queries monthly 1 2 3 4 5 Note(s): Gross Domestic Product, Information Technology, Artificial Intelligence, Artificial Intelligence of things, National Education Policy Source(s): Industry publications, media articles, 1Lattice analysis © 1Lattice 22 We are here for you Let us know how we can meet your business requirement? Amar Choudhary CEO, 1Lattice E: amar@1lattice.com Abhishek Maiti Director, Technology & Internet, Industrial goods & services E: abhishek.maiti@1lattice.com For media queries, Urbashree Bayan Associate Manager – Corporate Communications please contact E: communications@1lattice.com www.1lattice.com Disclaimer: This material has been prepared by 1Lattice, which is the trade name of Lattice Technologies Private Limited (“1Lattice”, “we” or “our”) with the intent to showcase our capability and disseminate learnings to potential partners/clients. This material can be referred to by the readers on the internet but should be referenced to 1Lattice, if reused or adapted in any form, or medium and on any forum. The frameworks, approaches, tools, analysis and opinions are solely 1Lattice’s intellectual property and are a combination of the collection of the best data we could find publicly, and the 1Lattice team’s own experiences and observations. 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