AI-driven Retail
Highlights
Top Insight
To succeed in an AI-driven retail landscape, brands and retailers need to embrace AI Agent Optimization to ensure they remain visible and attractive to AI-driven consumer searches. Instead of relying on traditional search engines or brand loyalty, AI agents will prioritize measurable factors such as price, availability, reliability, and service quality. This shift will benefit brands that offer distinct value through superior product quality, innovation, or customer service, while middle-tier retailers may struggle unless they differentiate themselves effectively. Generic products will face increasing pressure as AI agents streamline comparisons, making price and objective quality more influential than brand recognition alone. To thrive, companies must adapt by optimizing their offerings for AI agent decision-making, ensuring their unique advantages are clearly identifiable in AI-driven search and purchase processes.
(Source: Harvard Business Review)
Top News
1. Anthropic’s Claude 3.7 Sonnet allows users to control how long it “thinks” before responding, while OpenAI GPT-4.5 has enhanced contextual understanding and emotional intelligence.
2. Inception has introduced a diffusion-based large language model (DLM) that significantly outperforms traditional LLMs in speed and efficiency.
3. OpenAI is expanding access to its Deep Research tool to all paying ChatGPT users, while You.com has launched ARI, an AI research agent that generates professional-grade competitive insights in minutes.
4. Microsoft has made Copilot’s Voice and Think Deeper features free with unlimited use for all users.
5. Vevo Therapeutics has open-sourced Tahoe-100M, the world’s largest single-cell dataset mapping 60,000 drug-patient interactions.
Action Items
1. Assign AI and strategy teams to test and report on the newest AI models and tools (Claude 3.7, GPT-4.5, Inception DLM, ARI).
2. Test AI-driven competitive intelligence workflows using OpenAI’s Deep Research or You.com’s ARI.
3. Consider cost optimizations by transitioning to free AI features such as Microsoft Copilot’s unlimited use.
4. If in biotech or pharmaceuticals, explore the Tahoe-100M dataset for R&D.
5. Consider an AI Agent Optimization Strategy to ensure visibility and competitiveness in AI-driven consumer searches.
Additional Insights
1. Agentic transformation – using AI to embed AI (Board of Innovation)
Agentic transformation is a new approach to AI adoption where AI is not just integrated into business processes but actively drives and optimizes its own implementation. Unlike traditional AI rollouts that rely on static deployment plans, this method uses AI agents and digital twins to simulate, refine, and continuously improve workflows in real time. By embedding AI-driven feedback loops, companies can dynamically adjust AI models, ensuring they evolve with changing conditions rather than becoming obsolete. This approach enhances efficiency in various sectors, from sales forecasting to supply chain management, by allowing AI to monitor itself and refine processes proactively. As AI becomes central to business strategy, companies embracing agentic transformation will gain a lasting competitive edge by fostering an adaptable, self-improving system of intelligence.
2. How to use generative AI to augment your workforce (MIT Sloan)
To effectively integrate generative AI into the workforce, companies must define success, invest in data infrastructure, and incentivize employees to collaborate with AI rather than resist it. Proper AI training, similar to mentoring employees, is essential, and organizations must build structured data systems to provide clear examples of successful work. Pooling data across companies, particularly in areas like customer service and software engineering, can accelerate AI’s effectiveness, though smaller firms may struggle with access. Employees should be fairly compensated for their contributions to AI models, ensuring their expertise is valued rather than replaced. While AI will inevitably take over certain tasks, it also creates new roles, and businesses should strategically decide where AI should augment human work rather than completely replace jobs.
3. The critical role of strategic workforce planning in the age of AI (McKinsey)
Strategic workforce planning (SWP) is essential in the AI era, enabling organizations to proactively manage talent by anticipating future skill needs and aligning workforce capabilities with long-term business objectives. Companies that prioritize SWP gain agility, using AI-driven insights and dynamic workforce allocation to stay competitive amid rapid technological change, avoiding outdated “hire–fire” cycles. Investing in data-driven talent strategies, upskilling existing employees, and forecasting workforce trends through scenario planning ensures businesses remain resilient to automation and evolving market demands. By embedding SWP into daily operations, organizations can make informed decisions about hiring versus reskilling, optimizing talent deployment while fostering adaptability. As AI reshapes industries, companies that integrate SWP into their business models will secure a competitive edge, ensuring long-term sustainability and workforce readiness.
4. AI’s productivity paradox: how it might unfold more slowly than we think (Exponential View)
The article explores the potential for AI to disappoint in delivering productivity gains within a five-year period, despite its promise as a general-purpose technology (GPT). While AI is advancing rapidly and has seen impressive adoption in niche areas, broader economic impact may be hampered by slow integration into large firms, which drive most GDP growth. Key challenges include organizational inertia, regulatory constraints, and market overinvestment, which could lead to a financial bubble similar to past tech crashes. Additionally, even if AI delivers vast intelligence at lower costs, industries may struggle to absorb and effectively utilize it, delaying widespread productivity benefits. While AI is likely to reshape the economy over time, this analysis presents a plausible scenario where its impact unfolds more gradually than optimists anticipate.
Innovation Radar
1. AI Model Releases and Advancements
a. Anthropic’s new AI model, Claude 3.7 Sonnet, is the first hybrid reasoning AI that allows users to control how long it “thinks” before responding, offering both real-time and more deliberate answers, with improved accuracy, nuanced decision-making, and an integrated agentic coding tool (TechCrunch).
b. OpenAI has introduced GPT-4.5, its most advanced model yet, enhancing unsupervised learning, contextual understanding, and emotional intelligence, delivering faster, more accurate, and less hallucination-prone responses, while offering improved writing, coding, and problem-solving capabilities for ChatGPT Pro users and developers worldwide (OpenAI).
c. Tencent has launched Hunyuan Turbo S, an AI model that answers queries within a second, outperforming DeepSeek-R1 in speed while matching DeepSeek-V3 in knowledge, math, and reasoning, with significantly lower usage costs to stay competitive in China’s rapidly evolving AI market (Reuters).
d. Microsoft has introduced Phi-4-multimodal and Phi-4-mini, two advanced small language models designed for efficient AI applications, with Phi-4-multimodal integrating speech, vision, and text processing for multimodal interactions, and Phi-4-mini excelling in text-based reasoning and efficiency, both now available on Azure AI Foundry, Hugging Face, and NVIDIA API Catalog (Microsoft).
e. IBM has launched Granite 3.2, the latest in its AI model family, featuring multimodal capabilities, advanced reasoning, and improved safety mechanisms, optimized for enterprise efficiency with smaller, cost-effective models available on multiple platforms, including Hugging Face and IBM watsonx.ai (IBM).
f. Hume AI has launched Octave, the first LLM-powered text-to-speech model trained on both text and speech emotion tokens, enabling context-aware, emotionally expressive, and highly customizable voice generation for content creators, with pricing at half the cost of ElevenLabs and features like character voice consistency, granular emotion control, and upcoming voice cloning capabilities (VentureBeat).
g. Inception has introduced a diffusion-based large language model (DLM) that significantly outperforms traditional LLMs in speed and efficiency, offering up to 10x faster performance at 10x lower cost, with early adoption by Fortune 100 companies and a focus on reducing AI latency and GPU usage (TechCrunch).
h. ElevenLabs has launched Scribe v1, its most advanced speech-to-text model, achieving a record-high 96.7% accuracy in English and supporting 99 languages, with features like speaker diarization, word-level timestamps, and non-speech event detection, making it a powerful tool for enterprises needing high-accuracy transcription (VentureBeat).
2. AI Tools and Features
a. OpenAI is expanding access to its Deep Research tool, previously exclusive to $200/month Pro users, by allowing all paying ChatGPT users limited queries, alongside improvements like embedded image citations and enhanced document analysis, while also rolling out a free version of Advanced Voice Mode for real-time interactions (CNET).
b. Microsoft has made Copilot’s Voice and Think Deeper features free with unlimited use for all users, removing previous limits on OpenAI’s o1 reasoning model (The Verge).
c. Quora’s Poe has introduced Poe Apps, a new feature that allows users to create and share AI-powered web apps with custom visual interfaces, leveraging multiple AI models, with future plans for monetization and expanded platform support (TechCrunch).
d. You.com has launched ARI, an advanced AI research agent that generates professional-grade competitive insights in minutes by analyzing 400+ data sources simultaneously, offering verified citations, interactive visualizations, and real-time analysis (AI News).
3. AI in Consumer Technology
a. Amazon has unveiled Alexa+, a generative AI-powered voice assistant that enhances Alexa’s capabilities with advanced AI models, web navigation, and expanded service integrations, launching in late March for $19.99/month or free for Prime members (Axios).
b. Meta has unveiled Aria Gen 2, an advanced AI research headset featuring state-of-the-art sensors, on-device machine perception, and extended battery life, designed to push the boundaries of machine perception, contextual AI, robotics, and accessibility, building on the success of Project Aria to drive future computing innovations (Meta).
4. AI for Research and Social Impact
a. AI is being leveraged to combat poverty by analyzing satellite images and mobile-phone data to identify those in need more efficiently than traditional surveys, as demonstrated in Togo’s Novissi project, which provided direct cash transfers to impoverished villagers. While AI shows promise in improving aid distribution, concerns remain about biases, data accuracy, and the inability to capture multidimensional aspects of poverty, highlighting the need for a balance between AI-driven methods and conventional approaches (Nature).
b. Orakl Oncology leverages Meta’s open-source AI model, DINOv2, to enhance cancer drug discovery by analyzing organoid images with greater accuracy, significantly improving prediction of patient responses in clinical trials while streamlining research and eliminating time-consuming data analysis (Meta).
5. Other
a. Quantum computing
Amazon Web Services (AWS) has unveiled Ocelot, its first quantum computing chip developed with Caltech, aiming to reduce error-correction costs by 90% and advance practical, fault-tolerant quantum computing (TechCrunch).
b. Robots
Odense, Denmark, once a shipbuilding hub, has transformed into a leading robotics city with over 150 robotics companies, driven by academic partnerships, successful startups like Universal Robots, and a collaborative ecosystem that fosters innovation despite challenges in funding and talent acquisition (MIT Technology Review).
1X’s new humanoid robot, Neo Gamma, is designed to handle household chores and act as a voice companion (New Atlas).
c. Psychedelics
As the medical use of psychedelics gains traction, Scott Marshall, head of mycology at Optimi Health, is pioneering large-scale, pharmaceutical-grade psilocybin mushroom cultivation in Canada to meet future demand for legal therapeutic applications (MIT Technology Review).
d. Single-cell dataset
Vevo Therapeutics has open-sourced Tahoe-100M, the world’s largest single-cell dataset mapping 60,000 drug-patient interactions, as part of a collaboration with Arc Institute’s Virtual Cell Atlas, creating a publicly accessible 300-million-cell resource to advance AI-driven biological research (PR Newswire).
