The hype around artificial intelligence could also be heading into the “trough of disillusionment,” as Gartner calls it, but the technology continues to progress in big, disruptive ways — especially for martech. That is the nutshell version of the “Martech for 2025” report from chief martech Scott Brinker and marketing technologist Frans Riemersma, released today.
“AI is reshaping marketing and martech,” they write. “And while we’re not prone to hyperbole, we do consider there will probably be significant real-world changes that marketers and marketing operations leaders could have to face with this technology in 2025.”
These changes go well beyond current use cases like content generation, personalization and knowledge management. It’s unimaginable to say what all the future use cases could also be because AI’s ability to create “quick software” means they will probably be tailored to specific business needs.
Here comes the martech hypertail
These latest solutions, the “hypertail” according to the report, will probably be built not only by IT and marketers but in addition by AI agents. This means radical changes in the martech stack.
Dig deeper: 7 strategies for getting the most out of your martech stack
“This could also be the turning point where the number of industrial apps in the tech stack peaks and future growth of the stack — which overall we expect may very well be exponential — will come from custom software, a cornucopia of custom apps, agents, and automations.”
Radical changes are already underway amongst martech vendors, changes which can be upending the paradigm of how latest firms compete with established ones.
Existing martech giants like Adobe, HubSpot, Microsoft, Salesforce, and SAS have aggressively integrated latest AI capabilities into their products, leveraging each generative and traditional machine learning. This has ignited a brand new battleground, reminiscent of the age-old startup vs. incumbent struggle.
However, a significant slice of AI-native startups aren’t directly difficult these incumbents. Instead, they’re innovating on the periphery, developing small, standalone tools that automate or enhance specific marketing tasks inside existing platform ecosystems. These tools, powered by generative AI engines from OpenAI, Google, Anthropic, Meta, and others, offer complementary solutions slightly than direct competition.
Would you go all DIY?
One company, fintech giant Klarna, has gone to this point as to ditch two major vendors in favor of DIY software. It is replacing Salesforce and Workday with its own custom CRM and HCM applications using AI and composable cloud services.
While this may occasionally be an extreme move, as the report points out, “The indisputable fact that [it] is even conceivable is a testament to each the improved economics of custom development and the perceived business advantage of more tailored digital operations in the AI era.”
The other thing making this possible is the ability to tailor the AI using a business’s proprietary data and context-specific logic. The tailoring is primarily done one of 3 ways:
- Training one’s own model,
- Fine-tuning an existing model, and/or
- using retrieval augmented generation (RAG).
RAG, the commonest method, looks up data from internal databases and feeds it into the prompts given to the LLM engine. The response is generated its response using that data as input, which augments the LLM’s generic knowledge. This has the bonus of providing further LLM guardrails because the RAG can check or manipulate the LLM’s output.
Two other key points from the report:
- The importance of data strategy: Strong data strategies are fundamental for successful AI implementation. Cloud data warehouses have gotten essential for aggregating and orchestrating data. “The expression we’ve used for a very long time… you don’t have an AI strategy in the event you don’t have an information strategy.”
- Composability is the key: Martech stacks should have modular, interconnected components for flexibility and adaptability. “With a composable approach, we are able to take the best parts and pieces and construct out from there. You can compose a stack that is unique to your enterprise needs and unique to your customer needs.”
Dig deeper: Composability has arrived, says MessageGears
The report paints an image of martech where the only constant is change. This will probably be driven by evolving customer needs, but AI advancements should give marketers the tools to sustain with and sometimes get ahead of those changes. The full report could be downloaded here (registration required).
Finally, to give an idea of all the AI-powered changes in martech, Brinker and Riemersma did a genAI-only version of their famous martech landscape.
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