Our Thesis on the Future of Commerce 

The global e-commerce market is expected to reach $6.54 trillion by 2025 and will be further transformed by AI enabling frictionless trade and new experiences. Taking a look back at timelines, core milestones and generational companies built in the past, we see AI being the accelerant and catalyst towards interconnected trade and completely new ways of interacting with shopping and technology. 

Pre-2000s: Traditional Commerce & the Birth of the Internet

• The Internet and Early Foundations:  Before the advent of the internet, commerce was largely dominated by physical stores, direct trade, and catalog shopping. The World Wide Web was officially born in 1990, opening the door to online information exchange. The first ecommerce platforms began emerging in the 1990s, including eBay (1995), which became one of the first major online marketplaces, and Amazon (1995), which originally sold books before expanding into a massive online retailer. By the late 1990s, PayPal (1998) enabled digital transactions, setting the stage for secure online payments.

Commerce 1.0 (Late 90s – Early 2000s) Online Marketplaces & Retail Disruption

• Early E-Commerce & Marketplaces: The late 90s and early 2000s marked the birth of ecommerce where eBay and Amazon began to disrupt traditional retail. Amazon launched in 1995, changing how people bought products. Consumers could now shop for anything from anywhere, bypassing brick-and-mortar stores. The first wave of digital commerce was synonymous with online marketplaces where consumers could browse a variety of products from different sellers in one place.
• Challenges for Brands and Vendors: Building an independent online store was challenging during this phase. Vendors and brands faced the high overhead of creating, maintaining, and marketing their own websites. MercadoLibre (1999) took this model to Latin America, creating a dominant ecommerce platform in the region.
• Malls & Retail in Transition: Physical retail stores and malls were still dominant, but the rapid growth of online commerce started to encroach on their market share. Traditional retail began to face competition from the convenience of online shopping, leading to major retailer bankruptcies in the next decade.
• Early Niche Platforms: Specialized online marketplaces began to emerge. Etsy (2005) allowed artisans and small creators to sell handmade goods, democratizing the ability to access online retail for a wider group of people.

Commerce 2.0 (2000s – 2010s): Mobile Commerce, Infrastructure & Omnichannel Retail

• Rise of Mobile & Turnkey Ecommerce Solutions: By the late 2000s, mobile phones began to play a key role in commerce. The launch of the iPhone in 2007 triggered the development of mobile-first websites and applications. This period, known as Commerce 2.0, was characterized by the rapid adoption of smartphones and the need for retailers to build apps and mobile-optimized websites. Turnkey platforms like Shopify (founded in 2006) enabled anyone to set up their own online store with minimal tech expertise, making ecommerce accessible to millions of entrepreneurs.
• Google and Ads: In 2000, Google AdWords transformed how companies approached digital marketing, allowing businesses to target consumers based on search intent and location. Ads became a major revenue model for many online platforms, fueling ecommerce growth.
• Omnichannel Retail: Retailers realized they needed to integrate online and offline experiences. The concept of omnichannel retail emerged, where customers could shop seamlessly between physical stores and digital platforms. 
• Starting the Demand Economy: This was also the time when Uber (2009) emerged, laying the groundwork for mobile-driven, on-demand services in industries like transportation and food delivery.

Commerce 3.0 (2010s – 2020s): Social Media, Influencers & Payment Evolution

• The Rise of Social Commerce: As Instagram gained prominence in 2011, social media became an vital component of the ecommerce ecosystem. By the mid-2010s, TikTok (2018) and influencer-driven marketing exploded, with brands leveraging social media platforms to target consumers directly. Social commerce became a way to market and sell products through the influence of content creators, and TikTok in particular created new pathways for viral product discovery.
• On-Demand Economy: Ecommerce companies continued to scale, and by the end of this period, many major players like Instacart (2012) and Doordash (2013) had reshaped how consumers shopped for groceries, paid for goods, and accessed on-demand services. The emergence of Shein in the U.S. (2017) showcased the rise of fast fashion and data-driven product development, 
• Payment Innovations: The launch of Google Wallet (2011) and Apple Pay (2014) revolutionized how consumers paid for products. Meanwhile, Affirm (2012) introduced the idea of "buy now, pay later," offering consumers more flexible payment options. These innovations spurred a wider trend of fintech solutions that became integral to the ecommerce experience.
• SaaS Tools for Ecommerce: Intercom (2011), Klaviyo (2012), and Attentive (2016) emerged as key players providing infrastructure and tools for e-commerce brands. SaaS platforms became indispensable in powering customer communication, email marketing, and SMS campaigns. These core infrastructure providers began including machine learning algorithms and insights to drive improved marketing and conversion. 

Commerce 4.0 (2020 – 2030): Agent Orchestration of Autonomous Systems

• Pandemic-Driven Digital Transformation: The COVID-19 pandemic in 2020 was a pivotal moment for commerce, accelerating digital transformation across industries. Supply chains were disrupted, and businesses quickly adapted to new digital-first models. Consumers turned to ecommerce for everything from groceries to home entertainment, while retailers had to innovate to keep up with the surge in demand for online services. Many of the companies that benefited from a boom in work from home are still resilient businesses today, benefiting from hybrid work environments and altered consumer behavior. In addition, there still lasting effects on the younger generations' social and mental habits, including turning to online communities and virtual experiences for social engagements.
• Blockchain & Cryptocurrencies: In 2021, Bitcoin and other cryptocurrencies gained mainstream attention, signaling a shift toward decentralized financial systems and digital currencies. Brands and financial companies began experimenting with Web3 and ways blockchain technology can aid in transparency, payments, and security, driving global commerce and instant transactions.
• LLM Applications: ChatGPT was publicly launched in 2022 and pushed developer creativity into new AI driven applications. New companies are being started leveraging generative AI’s capabilities with first principles, tackling areas like content creation, personalized marketing, and improved knowledge work. In August 2022, Perplexity was launched, alongside its AI powered Shopping Product in 2024. Consumers have started to rely on foundation models and AI pwoered search providers for knowledge, recommendations, and peresonalized workflows.

Looking Forward to Opportunities We’re Excited About

Looking forward, we expect to see infrastructure-level companies reimaging how AI interacts with consumers and powers shopping decisions, alongside new AI-powered vertical commerce platforms. Two example companies and investments we've made in the space include Fermat Commerce, which provides dynamic and personalized shopping experiences across the customer lifecycle. Airial Travel is another recent investment that unbundles the traditional marketplace model, providing personalized trip planning for consumers and travel agencies. We imagine a world in which shopping experiences are powered by AI generated recommendations with agents who seamlessly research, plan, negotiate, and orchestrate the entire purchasing process. We expect new platforms and modes of interaction to arise, such as leveraging natural voice or employees and personal assistants that meet customers where they are. Below are a few categories of interest:

Hyperpersonalization Infrastructure

• Dynamic Personalization: Platforms that can optimize user context/knowledge against product catalogues and other data sources will enable the future of shopping agents. Examples include data sharing, identity, and comprehensive user profiles to enable the prediction of behaviors and preferences, allowing businesses to proactively tailor experiences, recommendations, and offers. This is especially relevant for enterprises that need to sift through their massive catalogue of data and predict the intention and motivation of anonymous users on their platforms, personalizing their UX and checkout flows. Other areas include moving from keyword to better semantic search, capturing the unique tastes, motivations, and psychology of consumers alongside evolving cultural trends.

Conversational Shopping Agents

• Full Stack Sales Assistants: Even across omnichannel platforms, sales assistants can better search, inspire, recommend, and explain various products/services to potential customers. Beyond traditional chatbots, shopping agents that have a unique windows into a person’s particular taste, needs, and personal life can complete unique shopping tasks (what meals should I make this week and what are the groceries I need?). As underlying infrastructure improves, we expect to see agents become more capable in reasoning, optimize thousands of variables, and fully execute multi-step workflows on behalf of clients.

New Era of Advertising and SEO

• The AI Marketer: As LLMs and agents become primary consumers of content on the web, we see the future of content-driven marketing and SEO becoming more programmatic and commoditized, especially with the help of automated marketing tools. Future marketing teams will allocate budget to platforms that can intelligently optimize ad spend across platforms according to organization’s goals. The AI Marketer will create the best strategy, execution, and delivery of campaigns, providing clear insight into ROI and bypassing traditional PR and advertising/growth agencies.
• LLM Risk Management: As underlying LLM providers like OpenAI and Perplexity launch shopping features, alongside vertical agents, large corporations and brands will need greater visibility into how foundation models are recommending certain products, services, and companies at scale. In addition to monitoring, we're interested in companies that can influence results at scale and demonstrate ROI on this new category of budget.

Supply Chain Optimization

• Intelligent Inventory management: On the demand side, AI analyzes vast amounts of data to predict shifts in consumer demand and trends, helping companies introduce new products and manage existing inventory. On the supply side, we take inspiration from the Shein model, having real-time insights into inventory and its suppliers and manufacturers. This allows Shein to produce small batches of around 100 items per product, analyzing customer feedback to determine which products to restock. This approach minimizes waste and allows for rapid response to consumer preferences. 
• Supply Chain Optimization: AI will optimize every aspect of the supply chain for aspects like route planning, energy efficiency, customs processing, and the prediction/mitigation of potential disruptions. Microsupply chains might also get created, localizing manufacturing hubs to replace traditional factories and enable on-demand production.

B2B Supplier Sourcing

• Procurement Agents: Discovering reliable vendors and service providers from anywhere in the world has never been easier. We're excited about agents who can sift through supplier databases, historical data, and market trends to recommend optimal procurement decisions that meet requirements and constraints. Such procurement agents can automate time-consuming workflows of requests for quotes, handling of negotiations, and optimization of suppliers. We see a big opportunity in mission-critical or highly technical industries that require massive amounts of research and supplier vetting. These products often involve complex supply chains, specialized manufacturing processes, and rigorous quality standards, making AI-driven sourcing tools particularly valuable in streamlining the procurement process.

Secondhand, Sharing, and Circular Economy

• Recommerce: The global market for second-hand goods is predicted to grow eleven times faster than the overall retail clothing industry, potentially reaching $77 billion by 2025. In the US alone, excess inventory is a $250B problem due to overstock issues by retailers and manufacturers and damaged products from returns. We’re interested in startups that help tap into the sharing economy, introduce novel ways to recycle and reuse materials that are previously untapped, and facilitate re-commerce from a cost to profit center. 

The Intersection of Fintech and Commerce

• Agentic Payments: As agents continue to execute transactions on behalf of customers, we expect secure and compliant solutions for human-to-agent, agent-to-agent, and agent-to-human payments. Current manifestations we're seeing include underlying wallets infrastructure that contain spending rulesets and leverage stablecoins and smart contracts to allow agents instantly make payments on a users' behalf.

Gamification for GenZ & Alphas

• Interactive Experiences: Younger generations continue to seek authentic connections and inspiring interactions in virtual communities and experiences. As AI continues to make headway into generating real-time interactive worlds and democratize use of the technology, we expect to see more adoption of 3D, VR/MX and interactive video penetrating games, film, creative assets, media, and advertisements. We're excited about new applications for interactive worlds, the infrastructure to democratize it, and underlying enabler of microtransactions via UGC.

If you are a founder building in any of these areas, please reach out to connie@montageventures.com!