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<\/a><\/figure>\nHappy New Year!<\/p>\n
Five years ago, Jason Baldwin and I published Martech 2030<\/strong><\/a> (ungated PDF), a report predicting five major trends that would shape marketing and martech through what we christened The Decade of the Augmented Marketer<\/em>.<\/p>\n We\u2019re now at halftime at the start of 2026.<\/p>\n How are those predictions holding up? I asked ChatGPT, Claude, and Gemini to grade them. Their assessments were pretty favorable \u2014 especially for our vision of \u201charmonizing humans & machines.\u201d (It\u2019s worth a chuckle that Claude and Gemini gave us A+\u2019s on that one. Very harmonious.)<\/p>\n But you should be the real judge. How do these line up with your lived reality?<\/p>\n Even in the previous decade, I was already bullish about \u201cno code\u201d platforms empowering marketers to self-service implementation of their digital ideas. Airtable, Webflow, Zapier were my go-to examples for databases, websites, and workflow automations respectively. Gartner called these users citizen creators. I\u2019ve called them \u201cmarketing makers,\u201d builders in the go-to-market realm. And I expected that we\u2019d see a lot more of them \u2014 with a lot more power at their fingertips.<\/p>\n In all modesty, we nailed this one. But largely due to a development that we didn\u2019t see coming: the generative AI explosion that started in late 2022.<\/p>\n No code used to be mostly drag-and-drop. With LLMs, suddenly you could simply describe what you wanted, and the AI would create it. At first, it was mostly for creating text and six-fingered images (paging Inigo Montoya<\/em>). But over the past two years, you could talk your way into building apps, agents, videos, infographics, workflows, campaigns, data analyses, PowerPoint decks, etc. It\u2019s still a jagged frontier, but the output for many of these is getting quite good.<\/p>\n As Andrej Karpathy said, \u201cThe hottest new programming language is English.\u201d<\/p>\n The vibe coding phenomenon of 2025 \u2014 a term coined by Karpathy \u2014 pushed this into hyperdrive. Bolt, Lovable, Replit, and Vercel made it insanely easy for non-engineers to create apps and agents. Granted, this worked best for relatively basic use cases. But those were exactly the kind of underserved opportunities that Clay Christensen had observed as the foundation of disruptive innovation. See my post on the Lemkin Scale of Vibe Coding<\/a> for a deeper dive on this.<\/p>\n In many ways, the major AI assistants such as ChatGPT, Claude, and Gemini are \u00fcber no code platforms, letting you create an ever-wider range of digital assets on demand. Teams who leaned into these capabilities have reaped the benefits of greater speed, bandwidth, creativity, and learning of decentralized self-service.<\/p>\n That said, governance and guardrails for citizen-created assets remain immature. Many organizations are still figuring out how to balance empowerment with brand consistency and compliance. We\u2019ll come back to this subject with Trend #4 about Big Ops\u2026<\/p>\n If prior decades were about firms optimizing linear chains \u2014 value chains, supply chains, distribution chains \u2014 we believed the structure and strategy of businesses would evolve to increasingly be driven by interconnected graphs and ecosystems via platforms, networks, and marketplaces.<\/p>\n In martech, platform ecosystems have now fully supplanted the old suite vs. best-of-breed<\/em> dichotomy. (I was delighted to contribute to this shift as VP platform ecosystem of HubSpot, a role I left this past September after 8 years of building the company\u2019s ISV program from the ground up.)<\/p>\n Two of the hottest platforms today are Databricks and Snowflake, which serve as unviersal data layers that integrate across heterogeneous tech stacks. Probably the most intriguing platforms headed into 2026 though are the major AI engines, with MCP connectors and the emerging concept of ChatGPT Apps.<\/p>\n Networks were already ubiquitous, but have grown even more so. Digital marketplaces have proliferated. I would say the most noteworthy ones in martech are the hyperscalers: AWS Marketplace, Google Cloud Marketplace, and Microsoft Marketplace now transact an estimated $45 billion in annual enterprise software sales. Adobe, HubSpot, and Salesforce now all offer products through this channel.<\/p>\n One seemingly paradoxical balancing act of platforms, networks, and marketplaces: it is through the centralized<\/em> control of standards and governance, when paired with technical and philosophical openness, that these ecosystem mechnisms drive decentralized<\/em> growth and innovation. You centralize to decentralize. It\u2019s a bit of a Zen koan for the digital age.<\/p>\n That\u2019s partly why this is only an A-\/B+ so far. Ecosystem dynamics are still new for many companies, who prefer the greater control they have \u2014\u00a0or at least the illusion of control \u2014 with more direct, linear go-to-market strategies. But those are old mental models from a previous era. I\u2019ll double down on my bet that ecosystems and the platforms, networks, and marketplaces that animate them will underpin marketing by the end of this decade.<\/p>\n When we wrote the Martech 2030 report, the 2020 martech landscape<\/a> had 8,000 solutions. As part of an annual tradition, most people assumed that was \u201cpeak martech.\u201d But here we are in 2025 with nearly twice as many: 15,384 commercial solutions on the map<\/a>.<\/p>\n Why hasn\u2019t this consolidated? Actually, it continually consolidates through competition and M&A. But because there are effectively no barriers to entry in software \u2014 a trend that AI has dialed up to 11 \u2014 new products continue to pour in at a faster rate than they drain out.<\/p>\n Ironically, it is the consolidation of hyperscaler cloud infrastructure and major app platforms that spurred the blossoming of thousands of specialist apps built on those foundations. (Centralize to decentralize.) These apps make up the long tail (the loooooooong, long tail) of the martech landscape: vertical market apps, regional apps, ecosystem apps, service provider apps, and an unending tide of startups aspiring to disrupt the incumbents.<\/p>\n But we predicted that The Great App Explosion would be even bigger. Not thousands of apps. Billions<\/em> of apps. The vast majority custom built by organizations, tailored to their own operations and customer experiences. While we expect the long tail of commercial martech will continue to grow, it will be dwarfed by the hypertail<\/em> of custom martech. (For more about the hypertail, download our State of Martech 2025<\/a> and Martech for 2026<\/a> reports from last spring and this past December.)<\/p>\n AI has delivered The Great App Explosion, and the hypertail is already thriving today. Five predictions we made within this trend are also materializing, including service-as-software (takeaway #3) and the rise of intelligent\/interactive marketing assets (takeaway #4):<\/p>\n We anticipated that the 2020\u2019s would be a decade of Big Ops. Analogous to wrangling the scale and complexity of Big Data, the mission of Big Ops would be to tackle and tame the scale and complexity of hundreds to thousands of parallel apps, agents, and automations operating on that sea of data within a company\u2019s operations.<\/p>\n We correctly called the problem \u2014 the chaos of uncoordinated \u201cNo Code\u201d Citizen Creators and The Great App Explosion \u2014 earning ourselves a solid B\/B+. Solutions, both technical and organizational, however, are still emerging. Almost every major platform in martech is focused on this problem\/opportunity right now, framed as \u201corchestration\u201d and \u201cdecisioning.\u201d<\/p>\n This is going to be the<\/em> platform battle for the rest of this decade. Grab your popcorn.<\/p>\n Data is a critical asset in Big Ops. But its value is only unlocked through its distillation and activation, which we described as data intelligence<\/em> and data relfexes<\/em>. One of my favorite metaphors from our report: data is not the new oil, it is the new oil paint. Big Ops is how we go from pigments on a palette to masterpieces on a canvas.<\/p>\n It\u2019s the entanglement of Big Data and Big Ops that positions Databricks and Snowflake \u2014 as well as the hyperscalers AWS, Google, and Microsoft \u2014 as serious contenders in the Orchestration Wars.<\/p>\n It will be a frenzy of coopetition between them and the public martechs (e.g., Adobe, Braze, HubSpot, Salesforce, Zeta), evolving CDPs (e.g., Hightouch, Tealium, Syncari, Treasure Data, Twilio), agent\/automation platforms (e.g., CrewAI, n8n, Make, Workato, Zapier), a wave of next-gen martech startups (e.g., GrowthLoop, iCustomer), and even the AI giants Anthropic and OpenAI.<\/p>\n Going to need more popcorn.<\/p>\n \u201cGreater automation and AI assistance will give marketers more time and new tools to focus on customers, creativity & innovation.\u201d If we made that prediction today, the reaction would be \u201cno duh.\u201d But five years ago, this was prescient. The graph we sketched below is pretty much exactly how this is playing out.<\/p>\n We noted that automation and human engagement aren\u2019t necessarily mutually exclusive, and when properly synthesized together can deliver magical experiences:<\/p>\n We also anticipated the rise of buyer-side AI, which emerged as a market force in 2025 with Agents of Customers<\/a>. What we envisioned in 2020 as a shift from SEO to BBO (Buyer Bot Optimization) is the phenomenon we\u2019ve come to know as SEO to AEO (AI Engine Optimization). What we predicted as Bot Commerce is now called Agentic Commerce.<\/p>\n The labels we\u2019ve landed on are cosmetically different, but the AI concepts we defined five years ago have crossed from theory into reality. I think we earned our A+\u2019s here, no?<\/p>\n What do you think? Did the ChatGPT, Claude, and Gemini grade us fairly?<\/p>\n Amara\u2019s Law states that we tend to overestimate the short-term impact of technologies but underestimate their long-term effects. The goal we had with our Martech 2030<\/a> paper was to think about that long-term arc. While these five trends are still evolving, it\u2019s remarkable how far they\u2019ve come in these past few years. The pace is quickening.<\/p>\n For better and worse, I don\u2019t think it will slow down in 2026.<\/p>\n Let\u2019s revisit this paper one more time in 2030 for final grades.<\/p>\n Join 42,000+ marketers and martech professionals who get my latest insights and analysis.<\/p>\n Trend #1: \u201cNo Code\u201d Citizen Creators<\/h2>\n
<\/a><\/figure>\n<\/a><\/figure>\nTrend #2: Platforms, Networks & Marketplaces<\/h2>\n
<\/a><\/figure>\n<\/a><\/figure>\nTrend #3: The Great App Explosion<\/h2>\n
<\/a><\/figure>\n<\/a><\/figure>\nTrend #4: From Big Data to Big Ops<\/h2>\n
<\/a><\/figure>\n<\/a><\/figure>\nTrend #5: Harmonizing Humans + Machines<\/h2>\n
<\/a><\/figure>\n<\/a><\/figure>\n<\/a><\/figure>\nConclusion<\/h2>\n
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