Surf’s Up! The Next Wave of Commerce is Here - Amplified and Shaped by AI
Issue №32 - By 2030 AI will have transformed Commerce - the customer experience, how businesses operate, and the technology that supports digital commerce. Let's wash that down with a classic Mai Tai.
This edition of the Cocktails & Commerce newsletter arrives just as many of you head out for an early summer break. A time to refresh and reflect - getting away and thinking about where we are at and where we are headed as we spend time with friends and family - or just get away for some quality down time. Maybe there is a cocktail in-hand as we turn to some summer reading - maybe something escapist, or maybe something that makes us think. The analysis in this issue is meant to contribute to that - looking forward to the massive wave about to hit commerce and commerce tech - amplified and shaped by Generative AI and the transformational nature of Agentic Commerce. Consider this a foundational piece looking to establish the footing from which further C&C research will follow. Now, don’t forget the sunscreen, make some orgeat syrup, and enjoy your Mai Tai while you school everyone on the history of the cocktail!
Cheers!
Cocktail: The Serendipity and Fiction of the Mai Tai
During the height of the tiki bar era - from the 1930’s to 1970’s - the most famous faux-Polynesian libation was the Zombie, with the Mai Tai a close second. While the Zombie faded together with the tiki-bar craze, the Mai Tai lived on to become an iconic cocktail served the world over.
While a classic, properly made Mai Tai is a great cocktail, the truth is that it really owes its longevity to its close association with Hawaii. More than a cocktail, it became a symbol of the islands - at least in the minds of the middle-class, American tourists flooding to the islands for sun, surf lessons, and luau’s. But the Mai Tai is neither authentically Hawaiian or even created there.
Victor “Trader Vic” Bergeron is generally acknowledged as the Mai Tai's inventor. In 1944, Bergeron went to work in the bar of his restaurant in Oakland, CA looking to add another tropical-inspired rum drink to the menus of his burgeoning chain of tiki-restaurants. He settled on a mix of dark, aged Jamaican rum, light Martinique rum, lime juice, curaçao, and orgeat syrup - a mixture of orgeat, sugar, orange and rose water - which he shook, poured into a double old-fashioned glass over shaved ice, and garnished with mint and a spent lime shell. Vic offered this new creation to a friend visiting from Tahiti and she proclaimed the drink “maita’i” - Tahitian for “good”.
The drink did not take off overnight. In fact, the Mai Tai was just an obscure cocktail only occasionally appearing on menus across the Trader Vic's mainland restaurant chain until early 1953. That’s when Bergeron included the drink on a menu he was asked to create for the iconic Royal Hawaiian Hotel on Honolulu’s Waikiki Beach. But even then, the drink was placed near the bottom of the menu, well below the Zombie and other drinks from the tiki-drink pantheon. Despite that, the drink soon became a favorite of the many travel writers who visited the hotel. The Mai Tai featured in many of their articles espousing the wonders of Hawaii to the rapidly growing middle-class on the American mainland craving a taste of the tropics.
Soon, the Matson Line - the Royal Hawaiian's owner - began featuring the Mai Tai on its steamer ships to Hawaii, and their many hotels throughout the islands. Rivals soon copied it and by the Mid-Fifties the drink had spread throughout the Hawaiian Islands and beyond - becoming a key symbol of Hawaiian and tropical vacations across the world - right there next to the palm trees, surf boards, and sun-oil.
Or, rather, the name had spread - not the actual drink. Since Vic's recipe was a trade secret, these rival hotels simply mixed low-cost rum with pineapple juice or orange juice, sweetened it with some grenadine, and called it a Mai Tai. So ironically, even though the Mai Tai had become an iconic drink of the 1970s - the only place making it properly was Trader Vic’s - turning a great drink into a sweet, terrible, cheap-to-make abomination.
With the revival of cocktailing and mixology, mixologists and bartenders have resuscitated the Mai Tai - embracing Vic’s original spec and concept - and returning the drink to the elegant, layered, timeless construct that it is. Just breathe in that salty air as you take a sip and contemplate the world.
Cheers!
Trader Vic’s Mai Tai Cocktail Spec
1 oz (~ 30 ml) - Amber Martinique rum
1 oz (~ 30 ml) - Aged Jamaican rum
1 oz (~ 30 ml) - Fresh lime juice
1/2 oz (~ 15 ml) - Orgeat syrup (see note)
1/2 oz (~ 15 ml) - Cointreau or Dry Curaçao
Garnish - mint, plus a lime twist or spent half of a lime
The process:
Add all ingredients to a cocktail shaker, except the garnishes. Shake vigorously for 30 seconds then strain into a rocks glass or large coupe filled with crushed ice. Garnish with fresh mint and the spent half of a lime if you fancy that. You can also float some dark rum on top of the cocktail for a little boozy addition.
Notes:
For an OG Mai Tai, orgeat syrup is a critical ingredient. Make your own from toasted blanched almonds, sugar, orange-flower water and almond extract or source from a leading provider such as Latitude 29’s Formula Orgeat or Liber & Co.
Analysis: Surf’s Up! Next-gen AI is powering a massive, transformational wave that will reshape commerce
It is fair to be skeptical about the impact of next-gen AI on commerce. Two and half years since ChatGPT dropped, and the impact of Generative AI on commerce has been relatively narrow and limited thus far - a handful of “co-pilot” use-cases here and there, paired with some early anxiety around a drop in web-search referral traffic. Adding to that, over the past decade we’ve been through multiple mini-hypecycles that have failed to have much of a material impact beyond cocktail chatter about Roblox and ski-goggles (VR headsets! “Meh-taverse”! NFTs! Oh my!).
But AI is different.
Only a few short years from now we can expect a commerce landscape and tech ecosystem that has been changed in multiple, profound ways. By 2030, it is likely that the fundamental nature of buyer-seller relationship and customer experience will have been redrawn. Business models will have been upended, changing the winning formula and shifting the balance across the retail, DTC, and B2B markets. As a result, the commerce technology landscape will also evolve markedly - with new architectures and approaches changing the very definition of the commerce platform while new point solutions emerge to address a new era of commerce experience and operations.
The good news? This will kick off a new era of innovation and investment - lighting a fire under what has become a commoditized and largely stagnant commerce tech and services market. Of course, for some this will be bad news, with incumbent solutions and approaches withering under the pressure to evolve or impacted by how these changes affect their customers - and thus demand for their solutions.
The who, what, where and how of commerce are all set to change. All of it caught up in a new wave of commerce fueled by context and powered by… tokens - the chunks of words, subwords, or characters that next-Gen AI models process and predict. These models and the agentic systems connected to them will transform commerce at a foundational level and impact every aspect of the commerce and marketing technology and services ecosystems - the players as well as the winners and losers.
A new wave of commerce is coming. It’s going to be epic, and it's going to be transformational.
Beyond the Tech - Three Epic Forces Stokein’ the Next Commerce Super-Swell
Beyond the rapid maturation of Generative-AI and agentic technology (which is well captured here if you need to be convinced), three key meta-factors are aligning to amplify the wave and drive this transformation in commerce:
Consumer behavior and expectations are undergoing a seismic shift - as search and browse give way to answers and conversations. Generative AI tools like ChatGPT and other “Answer Engines” now attract over 800 million weekly active users, making them the fastest adopted technology in human history. In the U.S., over one-third of adults now use these tools daily, with 10% reporting near-constant use. These solutions are no longer just for search or research - they’re becoming central to how people get things done, both at work and in their lives. Next: shopping. As these tools begin to guide decisions, make recommendations, and even transact, the very structure of the customer journey is changing - raising expectations for highly-accurate, relevant, personal and multi-modal, intelligent assistance. Onsite and off. Paired with (and perhaps intersecting with) the ongoing rise of social commerce, sellers will struggle to control and drive demand through their owned channels, accelerating the fragmentation of demand and the decreasing relevance of websites and today’s marketplaces.
AI investment demands a payoff - and the race to monetization is on. Generative AI is attracting unprecedented capital, with tech giants and VCs pouring over $200 billion into AI-related investments this year alone. That capital demands a return, and monetization is the next battleground. As usage skyrockets, these platforms must convert that attention into revenue. Beyond subscriptions, advertising and commerce are emerging as primary, likely paths to monetization - fueling a scramble to embed AI deeper into consumers’ routines, habits, decisions, and shopping journeys. The result? A high-stakes land grab for consumer attention where AI platforms, aggregators, marketplaces, retailers, brands and producers all collide; where the lines are drawn between utility, authority, trust, and convenience. In this new terrain, conversion becomes a collaboration between humans and intelligent agents - introducing the “AI Companion”, bot, or agent not just as a tool, but as a new kind of customer. Winning their business will require both a new playbook and new capabilities.
A thirst for efficiency and productivity will drive investment in enterprise AI-Agents and reshape how the work of commerce gets done. For operators, economic pressure and competitive intensity are driving a renewed hunger for efficiency, productivity, and scale. Commerce - across retail, DTC, and B2B - remains a complex, margin-sensitive business riddled with operational, labor-intensive, friction-filled workflows. From sourcing and merchandising to marketing, service, and fulfillment, these workflows have long been ripe for automation, but hamstrung by legacy tech, fragmented systems, and the practical limits of a human workforce. Up until now, we have seen relatively little in terms of the impact of generative AI in retail and commerce - limited to product attribute extraction/enrichment or basic customer service - but that is now set to change. As agentic systems and design-patterns mature - powered by AI tools (GPTs and LLMs) and enterprise-grade agents - we are entering a new phase of machine-augmented and automated operations. Static workflows will become dynamic, intelligent automations. Agentic solutions and agents will replace or enhance legacy platforms and point-soplutions - integrating across processes previously considered too manual, complex, or bespoke to automate. And the workforce itself will evolve - becoming a hybrid of human talent (management!) and intelligent agents, working side-by-side across the entire spectrum of jobs-to-be-done.
These mega-forces will combine to transform commerce. It's a confusing and anxious time in many ways, with the tech news cycle ramped to epic levels. There are a lot of terms being tossed about out there, many of which are not commonly defined. As a result most conversations about AI and its impact often come with lots of parenthetical definitions and confusing, overlapping terminology about what the fuck we are talking about. So…
Let’s Paddle Out, Line Up Some Lingo, and Drop Some Predictions
We have been thinking about this a lot, and had the opportunity to speak with many who are very close to these trends. So for your consideration, here are some commerce and commerce tech related definitions of concepts we will cover below and in the future - because you can be damned sure this is not the last article we will write about these. We even added some predictions within these curlers:
Answer Engines: An Answer Engine is an AI-powered system designed to respond to user questions with direct, contextually relevant, and often personalized answers - rather than links, pages, or traditional search results. Unlike Search Engines, Answer Engines aim to deliver answers and conclusions, and can engage in conversation-like refinement and exploration. Examples today include OpenAI’s ChatGPT, Anthropic’s Claude, Perplexity.ai, and Google’s Gemini + AI Overviews. By 2030, Answer Engines will replace traditional search as the dominant mode of digital information and product discovery - handling a majority of all product and information inquiries across both B2C and B2B. They will become trusted sources and advisors - reshaping how people find, evaluate, and decide. For brands and retailers, success will hinge on whether they can be indexed, trusted, and surfaced by an Answer Engine - perhaps with a boost in sponsored advertising or through participation in the Answer Engine’s marketplace or wallet.
AI Companion: The next level of Answer Engine - and a direction many of them have already explicitly signaled as a direction - AI Companions are persistent, context-aware AI agents designed to embed in their users life. These AI Companions will learn user preferences, habits, and goals over time through their deep connection to their users (and their data) over time - offering personalized support across tasks, flows, questions, decisions, and interactions. Unlike single-use chatbots or passive assistants, AI Companions build memory, adapt behavior, and often operate proactively. Meta and Google have already started marketing their AI in this way, with Meta’s Zuckerberg being very clear that - for better or worse - he wants everyone to have a Meta-powered AI-Companion. OpenAI acquired Jony Ivey’s company to pursue this very strategy, with some sort of mysterious hardware talisman yet to be conjured up. And of course, Apple - who has been criticized for being behind in AI - are clearly pursuing this strategy with SLMs (small language models) they will be able to embed in the devices their customers already trust with their data. By 2030, these AI Companions will have evolved into trusted, digital, personal co-pilots - involved in everything from shopping and scheduling to learning, leisure and entertainment - transforming nearly every aspect of life, society, culture, and the economy. (Dude, not saying I’m stoked about this, BTW.)
Agentic Commerce: Agentic Commerce refers to digital transactions initiated and executed by autonomous AI agents - such as Answer Engines, Social Networks (hello TikTok!), AI Companions, or other third-party buying agents. These agents will that act on behalf of users to discover, evaluate, recommend, negotiate, and increasingly transact. Context-rich, intent-driven interactions and simple replenishment journeys alike will be transacted by agents - replacing the clicks and inconveniences of commerce with zero-click journeys. While early phases will route transactions through brand sites or payment apps, by 2030 agents will handle end-to-end purchasing - becoming a key interface for B2C and B2B commerce and displacing traditional shopping journeys.
Autonomous Commerce: A fully automated form of digital commerce in which AI agents - not humans - initiate, negotiate, and complete transactions independently, based on pre-set goals, preferences, or real-time conditions. It goes beyond agent-assisted buying to enable continuous, decision-driven purchasing - such as replenishment, optimization, or arbitrage - without human intervention. Examples include programmatic B2B procurement, auto-reordering via IoT, or AI agents sourcing manufacturing and supply inputs dynamically across suppliers. By 2030, Autonomous Commerce will underpin large swaths of B2B trade, logistics, and replenishment - reshaping procurement, pricing, and supply chain dynamics across industries.
AI-Agent / Agentic systems: AI Agents / Agentic Systems are autonomous or semi-autonomous software entities embedded within organizations to perform tasks, make decisions, or interface with other agents - human or machine - across marketing, merchandising, operations, support, and commerce workflows. These systems will leverage Commerce domain-specific GPTs and LLMs together with agentic architectures to respond to inbound agent requests; personalize and contextualize customer experiences (human and agent); and assist, coordinate, drive, and optimize internal execution across a wide range of areas including marketing, inventory, fulfillment, and sourcing. Early forms include customer service bots, AI-generated campaigns, product content execution, or fulfillment optimization. By 2030, agentic systems will act as digital employees - scaling knowledge work, collaborating with external AI agents, and operating as the connective tissue of responsive, AI-native businesses.
Since the early days of eCommerce, through the rise of omnichannel and mobile commerce, we’ve witnessed a slow tide of digital transformation - each phase gradually and incrementally shifting how consumers discover, evaluate, and purchase products, and from whom.
But AI is different. It doesn’t extend the existing model. It reshapes it.
By 2030, the Commerce break’s gonna be pumpin’ - Shaped by Agentic rippers
The coming wave of AI-powered commerce - led by “Answer Engines,” agentic interfaces, and autonomous shopping agents - will accelerate and amplify the impact eCommerce has had on the economy. McKinsey estimates that by 2040, retail eCommerce in North America may grow to 50% of retail sales - turbocharged by AIs influence and dwarfing the impact of AI on other segments of the economy. (McKinsey forecasts European eCommerce growth to be a more modest 36% of retail sales, which is still huge.)
eCommerce is set to explode globally, turbocharged by Agentic cCommerce:
By 2030, most product discovery and consideration will be agent-mediated. As such, though the proverbial eCom pie will grow, there is a significant chance that - for better or worse - we will see a higher concentration of demand channels as Answer Engines and AI-Companions challenge to become a primary interface for shopping and product research - and much else.
As these systems become both deeply personal and transactional - integrating intimate knowledge of interests, intent, and personal details with wallets, payments, loyalty - these Answer Engines and AI-Companions won’t just redirect traffic from retailers and marketplaces, they may disintermediate their fundamental role and absorb their very business models. This will reshape market-share and distribution channels in a way that may dwarf the first quarter-century of digital commerce. And in case you think I forgot about Social Commerce - social networks will add agentic commerce as well - either through their own AI-Companions (Meta) or simply having Agents making purchases off the algorithm's generative influencer feeds easier (TikTok, since they likely won't be allowed to create a companion).
These Engines and Companions will redistribute power across the entire retail and commerce value chain. Living alongside and with consumers they will intercept intent, come to understand them and their evolving context, and will become woven deeply into their lives. Success will hinge on being reasoned and recommended by the Answer Engines and AI-Companions - not just ranked and recognized.
Many have speculated that these Answer Engines and AI Companions will somehow end up monetizing through ads. I am of the camp that the most likely outcome is a marketplace-like model. These Engines and Companions want to create intimacy, develop trust, and promise clarity and simplicity - and it is hard to imagine how ads fit in and do not “enshittify” the experience just like they did search (true for both on Google and Amazon).
Meanwhile, a marketplace model for commerce and services could easily work. Merchants will agree to the agentic solution’s terms (probably similar to Amazon’s 10-20%) and agree to accept their wallet payments (Bro, stablecoin is sooooo cool) and off you go. The Companions will argue that there is a higher degree of trust with “Trusted Merchants”, and therefore you are more likely to surface in a recommendation - all things considered. The battle won’t be for the search result or click - it’ll be for the AI Companion’s whisper or action.
Through all of this, meaningful consumer brands stand to benefit.
Brands have the margins to share in this marketplace model and are recognized and stand for something - though they will have to execute. Google long ago created a framework for SEO - which they call EEAT - and that applies now (apparently) to discoverability and surfacing of content by the Answer Engines. Brands that double down and demonstrate high quality experience, their expertise, authoritativeness, and trustworthiness - through content, storytelling, social proof, and evidence that they can be trusted will win. But that will be true for both humans and agents. The marketplace monetization model - plus wallets - will plug into the trust factor, creating incentives for brands and other businesses to participate. Luxury and lifestyle brands will continue to invest in physical stores as showrooms and destinations to reinforce their brand.
But even as we say that, the very factories that consumer brands and retailers leverage today may be the surprise winners in an agentic future. Tell your AI Companion or Answer Engine you want, “Top quality for the lowest price, and can wait a few extra days”, and it may well recommend you just buy this direct from a trusted source - the factory. Your AI Companion answers your prompt (or musing), “This factory in [fill in the blank] has been making the best [fill in the blank] for years - including for your favorite brand. It will take four extra-days but still cost less even with shipping and tariffs.” Ya, the LLM behind your companion of choice has digested Alibaba - and the rest of the global supply chain - and integrated that through the agentic commerce marketplace and stablecoin backed wallet. (It is certainly possible that regulation and tariffs will temper this, but don’t be surprised.)
All of this represents both opportunities and threats for everyone in the retail marketplace.
Amazon may face its first real credible threat from these new AI-powered marketplaces intercepting demand that may have started on Amazon in the past, or where they dominated. Amazon may well turn Alexa into a viable AI Companion or create a strategic tie-up - most likely with Perplexity, given Bezos’ investment there. This would bring their “everything store” (1P + 3P marketplace) to the table along with Amazon’s payments, Prime, fulfillment and logistics.
Meanwhile, Shopify and other platforms that cater to small brands may thrive for a short time as aggregators of brands, but overtime it is hard to see the value being in the website - what will be less and less valuable. The commerce platform is going to change in this new world, and payments alone may not be enough as the Engines and Companions promote their own wallets. The value in the platfrom will rest in data, orchestration, and enabling the agentic transformation.
Meanwhile, many retailers of perishables and consumables will benefit from agentic tie-ups that drive replenishment automation and where loyalty and proximity may play a role - most especially grocery. Mega-box retailers - Walmart, Costco, Kroger, Tesco, Ikea - will continue to compete using their market-power, private-label, ad-dollars, efficiency, and supply-chains to compete.
Perhaps predictably though, Agentic Commerce’s biggest losers will be those who are already struggling - multi-brand retailers such as drug-stores and department stores. It may sound a bit absolute, but their only hope lay in creating desirable private-label brands (which compete with brands), aggressive loyalty programs, or political lobbying. (Good luck with that! “AI Money-Bags” just left the Senator’s office!) In this new world, the mass-market, multi-brand retailer will be the hardest hit while brands (including vertically integrated retailers) have the best chance.
In B2B, the impacts of AI and agentic may be even more profound.
By 2030, co-pilots and all manner of AI will be infused into the workplace - using AI to support and drive workflows, design products, and automate maintenance - it will be natural for B2B buyers to leverage AI to research and source both products and services. A host of business applications, facilities, machines, robotics, and employees will tie into “Procurement Agents” which will use agentic approaches to connect to external suppliers. By 2030, these B2B Autonomous Commerce agents will drive large swaths of B2B trade, logistics, and replenishment - reshaping procurement, configuration, negotiation, pricing, service, and supply chain dynamics across industries. (But alas, let's leave further exploration of B2B and Autonomous Commerce for a future article - this damn thing is already too long!)
For ‘Commerce Crews’, the skills needed to shred are evolving fast.
Five years in this market may seem like a long time from now, but if you are as old as we are you realize it will be here before we know it. (So, yes, take that trip with your kids now!) Nearly every aspect of the commerce tech stack will be impacted as funnels turn to flows, search and discovery becomes context and conversations, composable becomes cognitive, and the static and manual become dynamic and agentic.
We wanted to explore the conceptual ways in which commerce capabilities will evolve with the changing experiences, new agentic customers, and with a reasonable expectation of technology change. Though not even a complete list, it is already long. The take-away seems clear: the implications for enabling commerce tech and operations are significant, broad and meaningful.
A wide range of commerce capabilities will be transformed by Agentic and AI:
All of these evolved capabilities, requirements, needs, and opportunities will drive a new generation of commerce technology investment. This will be akin to the investment waves driven by omnichannel and mobile commerce, but also very different. Incumbent and legacy commerce tech solutions and platforms will race to adapt - adding agentic wrappers around their APIs; making their solutions into resources and tools for agents; and building out their own agents that can communicate and collaborate with other agents. Not all will be successful, victims of some combination of tech-debt, install-base, the proverbial ‘innovator’s dilemma’, lack of vision, or poor marketing.
The wave that is coming is not just another trend-wave passing by as you sit in the lineup. It is the wave that will upend the market and create a whole new flood of opportunity.
Ridin' the Big Wave: Reshaping the board from Composable to Cognitive Commerce
It's arguable that the enterprise commerce technology landscape is about to undergo its most profound transformation since the very birth of eCommerce. Over the next five years, generative AI, agentic systems, and domain-specific LLMs will reshape how commerce happens - and what technology is required to power it. This will go beyond an incremental evolution, to a wholesale rewiring and reconfiguration of the commerce and marketing stack and ushering in a new era of commerce solutions - the Cognitive Commerce era.
As this new era takes hold we will see today’s Composable Commerce solutions will evolve into Agents.
By 2030, the hundreds of SaaS “best-of-breed” point-solutions that today plug into commerce stacks - search, CMS, PIM, CDP, marketing, testing, loyalty, tax, fraud, service, OO/OMS, etc. - will evolve from integrated SaaS applications into AI Agents, invoked on demand by platforms or other agents. Phase one will be simple “wrappers” around existing APIs using MCP; phase two sees these wrappers gain reasoning, and their own AI-enabled intelligence (guaranteed to be on every 2026 roadmap); phase three turns them into self-optimizing, multi-agent solutions directed at specific business goals and which collaborate with the many other agents in the commerce stack. Building and deploying these agents is already faster and cheaper than SaaS applications of old, opening up the competitive landscape to small, nimble, vibe-coded players who can rapidly build capability-rich agents - competing with multi-agent SaaS providers. Also competing with these productized best-of-breed Agents will be the host of bespoke Agents developed by consultancies and integrators - to complement and extend key emerging AI platforms and solutions; seek to retrofit and extend legacy environments; meet data security requirements; or support unique business processes or differentiation objectives. Integration moves from API calls to Agent-to-Agent, semantic, event-driven agent interactions.
A renewed mission for the MACH Alliance
All of this rapid and fundamental change - with the need for interoperability - begs for commerce tech and services industry collaboration. If only there were an organization set up to take on that role… (Oh wait! Hold on…) This is exactly what the MACH Alliance should focus on. A bit provocative perhaps, but maybe the Alliance should trade out the meaning behind the acronym and consider…. M = “MCP”, A = “Agentic”, C = “Cognitive”, H = “Holy Shit!”. In truth, the Alliance has been slow to embrace AI and to talk about what all of this means - despite both the implications for the ecosystem and how well the founding principals of MACH lend themselves to the agentic future of commerce.
The Alliance now has the opportunity to help the industry transition to this future - defining the standards and protocols important to commerce and ensuring members and operators alike are set up for the Agent-to-Agent, interoperable future that success in this next wave of commerce will require. Agents could be certified, a marketplace born, a mission refreshed. Perhaps the Alliance could become a bulwark against the potential for dramatic consolidation of demand - and thus power - toward the Answer Engines and AI-Companions. The Alliance could advocate for open standards, and for both business and technology conditions to support competition and an open, vibrant ecosystem.
The audience the Alliance is meant to serve - brands, retailers, B2Bs, and so on - would benefit from this shift in focus to agentic commerce and systems. I would go so far as to say a continued focus on the architectures and approaches are exactly what is actually needed - staying true to the founding purpose of the Alliance - versus the focus on the business value that the MACH Alliance has tried to emphasize. To be effective and serve this mission, the Alliance will also need to open-up and encompass the entire commerce ecosystem and make a range of other changes we have written about before.
Whoa there, bro - Are we droppin’ into the hype too early?
My career - like many of yours - has ridden the wave of eCommerce from the early days. I was fortunate to go through the early, exciting, experimental years - facing the dot-bomb doubters. We rode the wave as eCommerce became “omnichannel”, and a critical and foundational capability for every business. But that wave has in a sense already crested and crashed - becoming what a surfer might call the “inside section”. The whitewater and broken waves are still coming in - chaotic but ridable if you’ve got the finesse. A few are still hanging-ten while everyone else is coming up for air or already on the beach.
But turn around. There is a new wave coming, and it is massive. Time to paddle back out if you dare. The energy in this wave is massive, and the conditions are perfect.
The penetration of digital commerce and the influence of digital experiences is going to reach profound, new heights. New customers, new experiences and expectations, new technology and architectures will all contribute to a very different ride. Some who rode the last wave will ride this next one too. Some of them will ride it well - adapting and evolving - but not all. Surfers we have never seen are in the line-up, with new equipment and new skills - skills needed to ride the big one. As such, we have plenty of work to do as we research what all this means for the commerce platform (or if it will exist at all), the ways in which LLMs and GPTs will support commerce use-cases and deliver critical commerce context, and how the ecosystem will evolve. (And to stay on brand - this will be done with a cocktail in hand! Zero-proof and boozy, bitter wonders alike!)
I am not saying all these coming changes will be good. I am deeply concerned about the impact AI may have on our lives - quite likely impacting every aspect of our society, culture, and economy. But for a host of reasons, the change is coming and little seems to be in its way.
I am also fully aware that some will accuse me of succumbing to AI hype, but what’s my incentive? I’m just on the beach sipping my Mai Tai, tossing a few pointers out to those paddling out.
Cheers, hang loose, and crush that lip!
If you are looking for Brian online, you can find him here, here, and here. And find Bill here and here.
Be well, be safe, and here is to good business! Cheers! - Brian
Cocktails & Commerce™ is a wholly owned subsidiary of StrategyēM, LLC.
Great article Brian! I haven't been this excited about tech since those early days. I'm definitely paddling out to catch this wave.