Impact of Generative AI

AI is not hype. Let's talk about AI productivity gains. Walmart CEO on using AI in their latest earnings: "We've used multiple LLMs to accurately create or improve over 850,000,000 pieces of data in the catalog. Without the use of generative AI, this work would have required nearly 100X the current headcount to complete in the same amount of time" These are some of the use cases he mentioned: 1. Improvement of Product Catalog: Using generative AI to accurately create or improve over 850 million product catalog data pieces. 2. Order Picking: AI assists associates in picking online orders by showing high-quality product packaging images to help them quickly find what they're looking for. 3. AI-Powered Search: Customers and members benefit from AI-powered search on Walmart's app and site. 4. Shopping Assistant: A new AI shopping assistant provides advice and ideas, answering customer questions like "Which TV is best for watching sports?" 5. Follow-up Questions: The AI assistant is being developed to respond to more specific follow-up questions, such as "How's the lighting in the room where you'll place the TV?" 6. Supporting Sellers on Marketplace: AI helps sellers on Walmart’s marketplace by improving their experience and helping them grow their businesses. 7. Testing New Experience for Sellers: A new experience is being tested for U.S.-based sellers that allows them to ask AI anything, focusing on making the selling experience seamless. 8. Summarizing and Answering Queries: The AI assistant provides concise answers to sellers without requiring them to sort through long articles or other materials. The sooner you begin moving quickly, learning, and iterating, the sooner you'll start transforming your business and integrating AI across all operations. Companies that fail to do this will inevitably face disruption.

It is natural to think that if you live in Bengaluru, a shopping app would realise it’s 28°C outside and recommend products for your day, like a coffee meeting in Indiranagar. Right? 🤔 But it doesn’t! 😶 Current personalisation is mostly theatre. “People who bought this also bought this!” 🤦 It’s reactive, not proactive. It never answers the one question that actually matters: “Will this actually look good on ME?” I was recently looking at the architecture behind Glance’s Agentic Commerce, and as an engineer, the shift from intent-based to agentic is where the real story is. 🔥 But Glance isn’t just scaling a recommendation engine; they are deploying a multi-agent architecture. Instead of one model guessing your vibe, multiple specialised agents work in parallel, coordinated by an orchestrator agent. An agent analyses your skin tone, undertones, and body type from a selfie. No more buying emerald green only to realise it washes you out. It also has agents that understand real-time Bengaluru microclimates and fabric science. The agent knows if you lean minimalist, and it checks global signals to keep you current. After parallel processing, the orchestrator agent synthesises everything into a unified strategy. It’s not just a list of items; it’s 20+ unique collections built specifically for your life. Instead of stock photos of models who look nothing like us, Glance uses its generative AI model to create 100+ magazine-quality images of YOU wearing the clothes. It’s an agentic styling chat. You talk to it the way you’d talk to a friend who happens to have impeccable taste. The AI doesn’t just understand the words. It understands YOU — your body, your skin tone, your style preferences from prior interactions — and generates a complete, shoppable look in seconds. Here’s what’s happening under the hood: → The Glance agent interprets your natural language request → It factors in your context: weather, trends, occasion, budget → The generative AI creates a magazine-quality image of YOU wearing the look → Every piece in the image is shoppable, right there in the chat Glance is calling it agentic commerce. And I think it changes everything about how people discover and buy fashion. Engineering lesson: In the corporate world, “time to impact” is the only metric that matters. The search bar makes the user do the work — searching, filtering, and hoping. Agentic commerce flips the script: the AI understands you and works for you. 🏋️ Mitron… the search bar is dead. The only question is: are we ready for the conversation? 😬 #Glance #AICommerce #AgenticAI #FutureOfShopping #GenAI

Generative AI (GenAI) has ushered in a renaissance age for the generalist. For years, organizations have spent a disproportionate amount of capital hiring hyper specialized talent with deep technical knowledge. Now, with the democratization of #GenAI, the value offered by hiring ‘capable generalists’ is on the rise. People who articulately frame their thoughts, pose well-formed questions (prompts), and exercise #AI tools to their advantage, stand to benefit greatly. The demand for specialized AI talent - model developers, AI ops talent, and engineers to build and maintain infrastructure - will persist. But demand for non-technical talent is shifting to a more balanced state. Those who have the skills to extract value from platforms are becoming as valuable to organizations as those who build them.  I strongly encourage business leaders to incorporate skills like curiosity, critical thinking, and effective writing into their hiring profiles. These skills are becoming increasingly important - and valuable - in this next phase of technology and operations.

𝗤𝘂𝗮𝗻𝘁𝗶𝗳𝘆𝗶𝗻𝗴 𝘁𝗵𝗲 𝗳𝘂𝘁𝘂𝗿𝗲 𝗶𝗺𝗽𝗮𝗰𝘁 𝗼𝗳 𝗚𝗲𝗻𝗔𝗜 𝗼𝗻 𝘁𝗲𝗹𝗰𝗼 𝗻𝗲𝘁𝘄𝗼𝗿𝗸𝘀: Proud to have contributed to our Ericsson Mobility Report that launched today! There is a lot of noise out there when it comes to AI and GenAI, with predictions varying wildly. We have thus gone back to the drawing board, evaluated factual market data, engaged with key Silicon Valley players ... and established a baseline methodology on how to estimate that traffic growth. Check out https://lnkd.in/g89u26HR for a complete overview; and specifically pages 17-19 on the quantification of GenAI traffic (also attached below). My personal key take-away is that traffic in absolute terms does not slow down at all, and GenAI is an accelerant! Important to understand is that we are designing networks not in % increase but in absolute terms: we are talking about absolute spectrum availability, actual number of base station locations, real features, etc. It is time for the industry to wake up and acknowledge that we are short on IMT mid-band spectrum to cater for the continued increase of (absolute) datarate; with massive uplink requirements coming. Let me know what you think, and what your main take-aways are. cc Erik Ekudden | Hans Vestberg | Tian Chong Ng | David Willis

Generative AI is quietly becoming a valuable tool for entrepreneurs, helping them streamline tasks, save time, and progress faster on their start-ups. Sean Ammirati, a seasoned entrepreneurship professor at Carnegie Mellon University, noticed a significant change this year. His students, who typically spend a semester building start-ups, made unprecedented progress. The reason? They embraced generative AI as part of their process. From coding to market research, these tools are revolutionizing the start-up landscape, offering a more efficient path to turning ideas into viable businesses. 🚀 Faster Start-Up Growth: Generative AI helps entrepreneurs speed everything from product development to customer outreach. 🤖 AI as a Resource: Entrepreneurs are using AI for coding, legal advice, and marketing, cutting down on costs and time. 💼 Practical Support: AI tools are becoming the go-to resource for small businesses with limited resources. 📊 Investor Attention: Venture capitalists are noticing the rapid growth of AI-powered start-ups. 💡 Real-World Impact: AI is helping start-ups get off the ground faster, offering potential long-term economic benefits. #Entrepreneurship #AI #Startups #GenerativeAI #BusinessInnovation #TechTrends #AIFounder #Productivity #VentureCapital #SmallBusiness 

🧨 AI in luxury fashion & beauty (retail) seem to go hand in hand, but where are we today and where are we heading? 👇 Remzi Ural came up with an interesting framework for how AI will transform retail in 3 waves. While some companies are still preparing for Wave 1, the consumer's expectation is already halfway Wave 2... ⚙️ WAVE 1 - The Engine Layer The first wave happens where customers don't come: in the machine room of ops, supply chains, content creation, ... → AI making existing processes faster & cheaper. • American Eagle uses AI for predictive restocking. Data shows that a shelf is about to be empty in 1 hour, AI predicts sales loss & sends an alert: 'Restock shelf X.' • Stella McCartney uses AI to select eco-friendly materials & optimize cutting patterns = reducing fabric waste by 30%. • Burberry analyzes historical patterns + real-time social sentiment to forecast trends. • Mango uses AI for content creation. From turning studio pics into videos, to virtual influencers.. making production of content cheaper & faster. ❤️ WAVE 2 - The Experience Layer The second wave is a shift in interaction with customers. AI moves to the front, creating experiences that feel less like shopping and more like having an assistant. • Cucinelli launched a full AI-website, centred around conversational AI first. No pages, no menus. Worth a visit 😉 • Faces launched Layla AI, a Gen AI-powered beauty assistant. Almost 10% of their customers use it on a daily basis! L'Oréal has something similar, confirming the trend. • LV introduced an in-store Extraordinaires AI-Configurator. Using a photo of the customer or prompts, this VA suggests products that are matched to the customer’s style & needs. • Google VTO lets users try on thousands of clothing items by simply uploading a picture of themself. → Wave 2 is not about cheaper or faster, but better ... and requires rethinking processes. The question isn't whether to invest in Wave 2, but if you can move fast enough, before the competitive advantage's gone. 🤖 WAVE 3 - The Agentic Layer The last wave represents the most profound shift. "Agentic" will COMPLETELY change how commerce occurs. AI agents don't just assist, they execute autonomously on behalf of customers. We're still in the early days of this wave, with only few examples: • Perplexity launched "Buy with Pro" • ChatGPT has "Operator" • OpenAI, Shopify & Stripe are partnering up The user sets preferences & budgets and the agent handles discovery, comparison, negotiation and purchase. No browsing. No abandonment. No checkout (friction). Knowing that 51% percent of Gen Z consumers already starts product research in LLM platforms like ChatGPT or Gemini, this will be the future! ➡️ The brands that will thrive aren't necessarily the ones with the biggest tech budget or the best engineers. The winners will be those that understand what problem they're solving and have the courage to act, even when the path isn't perfectly clear. ⏳

GenAI Beyond Art, Video, Text: Addressing the World's Challenges   McKinsey & Company Global Institute modelling of trends in AI adoption revealed that AI has the potential to deliver additional global economic output of about $13 trillion by 2030, which would increase GDP by approximately 1.2 percent per year. There are many examples of global AI applications and use by governments to improve social welfare, national health care systems, domestic security and surveillance, and transportation. We have seen during Covid that global interconnectivity for data and treatments is lacking. +Disaster Relief and Infrastructure Development: Generative AI can model natural disasters, generating new patterns to help governments prepare and respond effectively. Real-time text and voice generation ensure efficient communication with affected populations, aiding in disaster relief efforts. +Healthcare: AI applications revolutionize healthcare by diagnosing diseases, recommending treatments, and enhancing patient engagement. Synthetic medical image generation augments datasets, improving diagnostic accuracy. Accelerates drug discovery and molecular design, enabling the development of life-saving medications. Text-generation educates patients effectively. +Education: Generative AI enriches learning experiences by generating quizzes, exercises, and interactive simulations. Personalized learning plans and textbook recommendations. Virtual tutors and language learning companions, powered by image and voice generation, provide adaptive learning experiences. +Wildlife Conservation: With a 69% average reduction in species populations since 1970, generative AI becomes vital. Predicts ecological changes and population dynamics, aiding researchers in creating proactive strategies to protect endangered species. +Financial Inclusion and Human Rights: Generative AI can also contribute to solving challenges in these areas. It helps promote financial inclusion through personalized financial planning and innovative credit scoring models. In human rights, it aids in automated translation, document analysis, and combating online harassment. KOREAN APPROACH TO AI The Korean government released its national strategy for AI on December 17, 2019. The strategy was formed based on the AI ecosystem, AI use, and people-centered AI and consists of 100 government-wide action tasks under nine strategies (Figure 12 see report). With its New Deal strategy, Korea is expected to transform into the smarter country to use data and digital technologies, including AI, and leads the innovative public services. 💜Generative AI's evolving nature and increasing capacity to contribute to global society make it an exciting field. By harnessing its innovative potential, we can address complex challenges, climate, inclusion and create a better future for all of us. What are the use cases you a excited about making a change in your life? #AI #generativeAI #innovation #smartcities #marthaverse

Quick commerce might create new rails for fashion in India. But AI is about to rewrite the stack. It won’t just improve margins or automate workflows. It will reshape how demand is created, what gets made, and how we buy. Here’s my prediction: 1. Search becomes intent-led Nobody wants to scroll through 400 SKUs. AI will learn your taste, body, budget, event, and mood, and surface five things that just work. Think: Spotify-style discovery, but for clothes. Discovery becomes contextual, not chaotic. We’re already seeing this in early interfaces like Perplexity’s shopping copilots. 2. Assortments get micro-targeted Massive catalogs are a liability. AI lets brands adapt SKUs dynamically, by user, region, season, even returns history. Shein scaled fast fashion through supply speed, but never cracked fit. Newme is flipping the model by doing weekly drops of 10–15 SKUs based on real-time feedback As merchandising behaves like content, inventory becomes a live system. 3. Returns are engineered out Returns were the biggest margin killer. Now they’re a solvable product problem through predictive sizing + fit-tech + try-at-home delivery. Zalando and H&M are already running fit-tech integrations + virtual try-ons at scale. Fit-tech will become table stakes. 4. Supply chains go real-time From design to drop to replenish to clear. AI enables live demand forecasting, smarter markdowns and faster reaction cycles. Urbanic, Zara, and Myntra are tightening feedback loops using browsing + returns + trend signals Fashion will respond to signals, not seasons and less dead stock will lead to better margins. 5. Shopping shifts from search to recommendation Shopping will shift from browsing to context-driven nudges. AI copilots will shop with you, not for you. Voice-first agents are already live. AI doesn’t just improve conversion: it changes the loop. The next generation of fashion brands will scale through personalization, fit precision, intelligent curation, and habit-forming UX Fashion will live at the intersection of fast-moving infrastructure and intelligent systems. This wont change how we buy. It will change what gets made.

The Upwork Research Institute teamed up with our Analytics team to conduct a year-long study across all categories of work on our platform to better understand the transformative effects of #GenerativeAI on freelancers' work opportunities and earnings. Meticulously designed to isolate the causal impact of generative AI, the study yielded some fascinating results! 🤖 Generative AI's impact showcases the dynamic interplay of replacement and reinstatement effects (more on these in the whitepaper), where emergent technology creates new work opportunities and increases earnings over time. Contrary to fears of job displacement, generative AI is an overall net-positive trend for the Upwork marketplace and the independent talent and clients we serve. Growth in high-value contracts on Upwork due to generative AI more than offsets the decline we’ve seen in low-value contracts.   📊 Our research highlights nuanced impacts across different work categories. While some categories like Data Science & Analytics see immediate gains in demand and earnings due to reinstatement and new work opportunities, others like Writing & Translation show mixed effects, but ultimately reflect a rise in demand for high-value contracts and earnings due to generative AI. This underscores the importance for professionals to leverage skilling and educational programs, including opportunities offered by Upwork Academy’s AI Education Library, Education Marketplace and partnerships with @Coursera and @Udemy.   🚀 As we navigate this era of technological advancement, this study underscores the tremendous opportunities that we see for Generative AI to empower humans rather than replace them. At Upwork, we're committed to fostering an ecosystem where talent thrives, innovation flourishes, and human-centered AI drives progress and unlocks our potential. Resources like our AI Services hub and access to AI tools from leading providers, as well as platform features like Upwork Chat Pro empower talent on Upwork to become the world’s most AI-enabled independent professionals.   I'm proud to lead a company leaning into human-centered AI innovation, constantly seeking to understand and adapt to the evolving technological shifts in our economy and the world of work.    I invite you to delve deeper into our research findings and explore the full whitepaper, available via our blog post: https://lnkd.in/ghgF49PA    #FutureOfWork #AI #AIInnovation 

Let’s talk about some real potential of Generative AI. Here are 9 Use cases a business leader should know to understand how to extract real value out of Gen AI. 𝟭. 𝗔𝘀𝘀𝗲𝘁 𝗠𝗮𝗶𝗻𝘁𝗲𝗻𝗮𝗻𝗰𝗲 𝗣𝗹𝗮𝗻𝗻𝗶𝗻𝗴 ↳ Optimize and Simulate maintenance schedules using historical use and performance data. ↳ Benefits - Cost Improvements - Better Health & Safety - Increased throughput 𝟮. 𝗢𝗽𝘁𝗶𝗺𝗶𝘇𝗶𝗻𝗴 𝘁𝗿𝗮𝗱𝗲 𝗽𝗿𝗼𝗺𝗼𝘁𝗶𝗼𝗻𝘀 ↳ Prepare negotiation decks and analyze vast amounts of historic unstructured data to support the negotiation process ↳ Benefits - Efficient trade promo process - Better allocation of resources - Data-driven decision making 𝟯. 𝗣𝗿𝗼𝗱𝘂𝗰𝘁 𝗗𝗲𝘃𝗲𝗹𝗼𝗽𝗺𝗲𝗻𝘁 ↳Fast design iterations using design software (Creative Assistant). Add insights from historical market data. ↳Benefits - Faster Speed-to-market - ‘More Creative Bandwidth’ - Curtailing market research time 𝟰. 𝗕𝘂𝘀𝗶𝗻𝗲𝘀𝘀 𝗶𝗻𝘁𝗲𝗹𝗹𝗶𝗴𝗲𝗻𝗰𝗲 ↳Locally fine-tuned models enable faster access to information through human-like interaction. ↳Benefits - Data-driven decision making - Analyze previously inaccessible unstructured data 𝟱. 𝗗𝗶𝗴𝗶𝘁𝗮𝗹 𝗧𝗿𝗮𝗻𝘀𝗳𝗼𝗿𝗺𝗮𝘁𝗶𝗼𝗻 ↳Faster migration to advanced analytics through assisting code development ↳Benefits - Short software dev lifecycle - Access to a wider knowledge base for SMEs 𝟲. 𝗧𝗲𝘀𝘁 𝗗𝗮𝘁𝗮 𝗚𝗲𝗻𝗲𝗿𝗮𝘁𝗶𝗼𝗻 ↳ Generate synthetic data for testing and simulating scenarios previously unknown. ↳ Benefits - Faster AI Model deployment - Rigorous testing using scores of data 𝟳. 𝗖𝘂𝘀𝘁𝗼𝗺𝗲𝗿 𝗿𝗲𝗽𝗿𝗲𝘀𝗲𝗻𝘁𝗮𝘁𝗶𝘃𝗲𝘀 ↳ Using NLP, Speech-to-text deploys 24-hour Customer support. ↳ Benefits - Better customer experience - Increased human Customer Representative’s efficiency 𝟴. 𝗣𝘂𝗯𝗹𝗶𝗰 𝗦𝗲𝗰𝘁𝗼𝗿 𝗨𝗿𝗯𝗮𝗻 𝗣𝗹𝗮𝗻𝗻𝗶𝗻𝗴 ↳ Support Governments to simulate scenarios of various infrastructure decisions. Generate 3D models for master planning. ↳ Benefits - Super-charge creativity - Better decision-making Faster ideas generation 𝟵. 𝗟𝗮𝗻𝗴𝘂𝗮𝗴𝗲 𝗧𝗿𝗮𝗻𝘀𝗹𝗮𝘁𝗶𝗼𝗻 ↳Multi-national corporations get access to huge in-house content and best practices previously in different languages ↳ Benefits Better Customer experience Best-practice sharing Standardized processes Share what else you can add. If you like the post, share it with someone who can benefit from it. --- I am Tariq Munir...My mission is to create a Tech-enabled Humanistic future for all through my talks, writings, and content. Follow me to be part of this mission and learn more about Digital Transformation, Data, and AI.