Gela Fridman

🌍 While Instacart revolutionizes grocery shopping in America with AI agents, what does this mean for Africa's retail future? Instacart just launched AI solutions that turn grocery shopping into simple conversations. Major retailers like Kroger and Sprouts are already onboard, letting customers build baskets, get meal suggestions, and complete purchases through natural dialogue with AI agents. This "prompt economy" shift is fascinating for Africa's context. We're leapfrogging traditional e-commerce infrastructure in many regions. Imagine AI-powered shopping agents adapted for local markets - helping customers navigate seasonal produce availability, suggesting recipes with indigenous ingredients, or facilitating group buying for rural communities. In Uganda, Kenya, and Nigeria, we're already seeing mobile-first commerce solutions. Adding conversational AI could democratize access to quality groceries, especially in areas where traditional retail infrastructure is limited. The real opportunity? Building AI shopping solutions that understand African contexts - local languages, cultural food preferences, and community buying patterns. 💬 How do you see conversational AI transforming retail across Africa? What challenges and opportunities do you foresee? #ArtificialIntelligence #AfricaTech #AIForGood #FutureOfRetail #DigitalAfrica

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AI pilots are everywhere. ROI is not. 95% of pilot investments fail. Businesses are getting impatient. Real value comes from connecting AI to trusted data, workflows and people. That’s the Agentic Enterprise. We’re seeing it at ANZ Bank, Xero, Australia Post, Flight Centre Travel Group, Zurich Insurance, and many more organisations crossing the last mile to measurable impact. Proud to share my thoughts in today’s AFR 👇 https://bit.ly/3N234x6

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AI-driven disruption is not uniform across industries. To explore this, Moloco and Boston Consulting Group (BCG) partnered to publish the AI Disruption Index: https://lnkd.in/gdfJRSCB The report provides a real-time pulse check on industries being reshaped by AI and highlights emerging opportunities. The research indicates that while AI is transforming how people discover products and services, customer relationships remain paramount. Take Pizza Hut, for example. Their Senior Director of Media shared their approach: 1. Investing in their app as a way to build direct relationships 2. Using their first-party data to create experiences AI can't copy 3. Diversifying their budget from traditional discovery channels into in-app advertising Innovative brands that are winning aren't trying to fight AI—they're just getting better at building direct connections with their customers. For more insights, you can watch the Brand Innovators backstage interview with Pizza Hut here: https://lnkd.in/gYcBjpJG.

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I'm proud of what Fortune highlighted about the Amazon Web Services (AWS) Gen AI Innovation Center (#GenAIIC), but what they captured goes beyond our production rate; it's about fundamentally changing how enterprises approach AI transformation. Two and a half years ago, we launched with a hypothesis: customers don't need more POCs. They need partners who can take AI from concept to production, at scale, while building their internal capabilities to sustain it. What we've learned from working with 1,000+ customers from Formula 1 to Nasdaq, GoDaddy to Cox Automotive Inc. is that production success comes down to two critical shifts: First, engagement models matter. We deploy Forward Deployed Engineering (FDE) teams for strategic depth, which is embedding multi-disciplinary builders through full implementation cycles - building, deploying, and teaching customers to operate AI-powered solutions. For rapid scale, we mechanized "Live in 45," which is leveraging velocity and rapid building using solution accelerators and reusable assets to deliver outcomes within 45 days. Second, platform focus accelerates everything. We're driving three AWS platforms at scale: Nova Forge for model customization, Bedrock AgentCore for agentic AI, and Quick Suite for workforce transformation. But here's what excites me most: we scale through ecosystem leverage. Our partners have shifted from execution support to demand originators, now the predominant source of opportunities, and platform partnerships with emerging startups are generating multi-fold ARR returns. Fortune asked what we've learned. Here it is: Production at scale isn't about better pilots; it's about better partnerships, reusable patterns, and relentless focus on customer outcomes. Link to Fortune article: https://lnkd.in/gfD_ChJE Francessca Vasquez, Joel Sider, Amanda Cohen, Jaime Wilde (Rice), Randi Larson, Jackie Vendetti, Sri Elaprolu, Sarah Cooper, Shaun Collett, Anila Joshi, Pouria Mortazavian, Atanu Roy, Mohamed (Mo) Ahmed, Ph.D., Diego Socolinsky, Rafael Fernandes, Kate Zimmerman, Marta Milejska, Yaniv Ehrlich #GenerativeAI #AWS #Innovation #LiveIn45

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The Strategic Value of Micro Roles: Building Profitability with Focused, Fractional Expertise Revenue Magazine article I wrote. https://lnkd.in/eBC-Q2-F TLDL: Build Your Fractional Network Now To stay competitive, start lining up the right micro-role experts today. Look for consultants who excel in revenue operations, CRM optimization, and top-of-the-funnel strategy. These partners should be ready to deliver measurable results, paving the way for long-term profitability and growth. By investing in fractional expertise, your business can target precise growth strategies without unnecessary costs. Stay lean, agile, and ready for rapid growth, bringing in top-tier specialists for the exact skills you need when you need them—leaving your full-time resources free to execute on long-term growth. With this approach, companies can turn micro roles into massive gains, shaping a winning team one project at a time. In a world where speed and efficiency win, micro roles are the play that drives profitable, focused results.

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Had such a great chat with Vivien Lin! She brought so much wisdom and vivid insights to the conversation: 1. We're trying to work with our users, when they make money we make money. We try not to stand on the opposite. 2. From the start we decided to exit China market. We never touched US users. It's all because we are quite self-disciplined and self-regulated. 3. We consider whether this product or whether a feature can truly solve the problem for the user. 4. From 2018, 2019 is always put our top priority to think about how we bring more new user to the crypto industry. It's not like competing the existing user with other exchange. 5. Ideally, the final product should be you don't need to worry about what functions sit in what page. You just go to the AI or the AI assistant to tell him what you want. 6. The difference in the roadmap between crypto and traditional finance is rooted in how the industry got originated. For traditional finance, banking and payment that's naturally where finance comes from than lending than trading. At crypto, the very first need where the industry originated is mining. 7. I think, we are still in a very precious time window especially for exchange it to become a sort of mega platform in near future. 8. My suggestion is always be open minded - open minded to the technology, business model and even all those new ideas. 9. My suggestion to everyone, even if you are a legal, you are a product manager or you are in the operation team, is to study programming, learn how to code. 10. The slides always tell the good stories but you need to get down to the details to understand what's happening. 11. Before all those regulations put into place there has to be someone familiar with how possible the regulation is going to be implemented in the future and we can get prepared beforehand. 12. Without one major hack exchange cannot be a mature exchange. 13. If I know what they are doing I can read their code, I can get a very direct sense about the quality of the project instead of really looking at the powerpoint. Watch the full session here: https://lnkd.in/dGhbXdwr BingX

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This Amazon story seems to be one proof point of many: it’s harder to transform an existing enterprise to AI-first than to build from scratch. The stories of startups being wholly, mostly, or partially staffed by AI agents might not be exaggerated. But they are not the bar against which we can measure existing entities. Turning the ship around takes time, planning, learning, testing, implementing, and fixing along the way. https://lnkd.in/e8kdB6ZS

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I’ve spent most of my career in the startup world. When you’re in a small team, the mission is oxygen. You act like the money is yours, because if the company fails, there’s no safety net. Whenever I’ve stepped into the world of large corporations, I’ve felt that immediate shift. The "red tape" starts to drag. Processes designed to prevent mistakes end up preventing action. People show up to do their "daily job," but they often lose sight of the "why." This memo from Amazon CEO Andy Jassy (link below) really resonated with me. He talks about making Amazon the "world’s largest startup." It’s an ambitious vision, but let’s be real about the context: Amazon is currently navigating the departure of 16,000 employees. It is impossible to talk about "efficiency" and "returning to startup roots" without acknowledging the very real human cost of that transition. My heart goes out to those affected; talent leaving a company is never just a metric on a spreadsheet. However, I believe Jassy’s diagnosis of the "corporate disease" is spot on. As companies grow, they naturally create entropy. They add layers. They prioritize bureaucracy over builders. They stop acting like owners and start acting like administrators. For a company of Amazon’s scale to admit that they’ve allowed too much "red tape" to creep in is a necessary wake-up call for the rest of the industry. The goal shouldn't be just to grow big—it should be to stay "small" enough to care, to move fast, and to keep that ownership mindset alive, no matter how many zeros are at the end of the headcount. You can be a giant, but the moment you stop thinking like a founder, you start the slow walk toward irrelevance. What do you think? Can a company ever truly maintain a "startup culture" once it reaches 1M+ employees? Or is entropy inevitable? https://lnkd.in/eeEv2Ryu

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A BEST CASE SCENARIO FOR AI? David Sacks offers an optimistic AI outlook, countering doomer predictions of a rapid AGI takeoff. With 2025 model releases, top U.S. firms like OpenAI and xAI show competitive clustering and specialization, not monopolies. This decentralized race boosts innovation, supports human-AI collaboration (boosting productivity 20-30%, per MIT), and mitigates centralized control risks. Open-source models and vertical applications further fuel growth, suggesting a dynamic, balanced AI future—less Oppenheimer, more Goldilocks. Stay tuned as this evolves! https://lnkd.in/eRJc8YyK

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Retail just crossed a threshold. Walmart's partnership with OpenAI brings us into the era where conversation replaces navigation. Shoppers will no longer browse, they’ll describe their intent, and an AI agent will curate, compare, and complete the purchase in seconds. That means the front line of commerce has changed: it’s not your website, it’s the algorithm interpreting your offer. The new question isn’t “how do we convert customers?” but “how do we convince AI agents?” Pricing, product data, and positioning now compete in machine logic. Win that, and you win the customer, human or AI. #AI #Ecommerce #Retail #Pricing #AgenticCommerce https://lnkd.in/eKHaAviW

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