What you need to know

• AI is a complex landscape in the midst of multiple Hype Cycles as platforms, features and functions go through different maturity stages, according to Scott Brinker and Frans Riemersma's Martech 2025 report.
• Generative AI in particular is a significant part of this landscape, and the beneficiary of advances in the foundation models developed by major tech companies like OpenAI and Google.
• Ethan Mollick, author of Co-Intelligence suggests even if AI development halts, the integration of current capabilities into organisations will continue to evolve for the next 5-10 years.
• The martech landscape has seen a significant increase in tools, with a 27.8% rise from 11,038 to 14,108 tools reported.
• AI-powered specialist tools are driving growth in the long tail of the market, with key use cases including content marketing, sales automation and chatbots.
• Companies are increasingly addressing data silos and orchestration challenges to maximise ROI on SaaS applications, aided by Customer Data Platforms (CDPs).
• The new AI era is shifting focus from managing big data to managing "big ops", emphasising the complexity of interconnected apps and automations.

Stop thinking about AI as a single technology on a linear maturity curve, say Scott Brinker and Frans Riemersma. Instead, brace yourself to deal with a far more complicated reality: "AI is not really a single Hype Cycle, but a multitude of them, all at different stages, many entangled with each other."

In their recently released Martech 2025 report, the pair say generative AI in particular, is "a massively large field with different use cases all at different stages of maturity. All of them inherit advances in the rapidly improving foundation models from OpenAI, Anthropic, Google, Meta."

Messy enough for you? There's more. "They each have their own technology innovations wrapped around them."

"And generative AI itself is just one part of a larger AI universe, where the myriad of machine learning (ML) techniques and applications have been advancing for years," they write.

All of this is happening in the context of huge developments in AI and machine learning over the last decade, most of which went unheralded before ChatGPT 3 burst into public consciousness in late 2022.

"We do believe there will be significant real-world changes that marketers and marketing operations leaders will have to face with this technology in 2025," the report authors continue.

A key subtext of Martech 2025 is that the rate of change is accelerating.

As Ethan Mollick, who has emerged as one of the most accessible and informative voices on AI, wrote on LinkedIn earlier this year, "We are absolutely at a place where, if AI development completely stopped, we would still have 5-10 years of rapid change absorbing the capabilities of current models and integrating them into organisations and social systems.

"I don't think development is going to stop, though."

Exploding and consolidating

Brinker has famously tracked the growth of the martech landscape since 2011, and earlier this year revealed what he described as "a whopping" 27.8 per cent increased in martech tools from 11,038 to 14,108. But in fact, the growth in actual tools is higher than that, since those figures represent a net increase.

Expect the growth to continue. Indeed a year ago, Brinker told Mi3 the point would come when the number of tools would cease to have any meaning. That point was reinforced in this year's report which talks about "instant software" that basically blinks into existence as required.

Most of the growth, according to Martech 2025, is the result of an explosion in AI-powered specialist tools in the “long tail” of the market.

As to the use cases behind the growth, Brinker and Riemersma are tracking 14 categories with the top five being content marketing, sales automation enablement and intelligence, video marketing, business/customer intelligence and data science, and live chat and chatbots.

Data, data everywhere. Have a drink

One of the choke points on growth during previous waves of martech evolution such as the rise of software-as-a-service (SaaS), and the expansion of cloud computing was the complicated, distributed and highly siloed nature of corporate data. While that remains an issue, and likely always will, brands have invested huge amounts of time and treasure into addressing the problem for a variety of reasons. These include the need to extract maximum ROI from all those SaaS apps, the rise of CDPs which has eased the problem of data orchestration, and the increasingly hostile regulatory environment around the world around how that data is used.

But the upside is the work required to usher in the age of data-driven marketing also laid the foundations for the AI era.

According to Brinker and Riemersma, "Because we’re utilising our data in more ways, we extract more value from it. And now, more and more use cases for that data are delivered with AI – whether embedded in existing apps, new stand-alone tools, custom 'software' that we create ourselves, or service-as-a-software solutions from outsourced providers."

Of course, in the endless game of Martech Whackamole, there's always another challenge just around the corner. Modern data stacks have largely focused on customer data and business operations data, they note. However, the components of those stacks – a veritable alphabet soup of tech acronyms from DAMs to CMSs to PIMs and to DXPs - are not well integrated.

According to Martech 2025, "They’re often connected in a fragile point-to-point fashion to serve specific use cases. We only connect them to customer data in the late stages of campaigns or customer experiences to deliver limited personalisation.

"Managing this broader data ecosystem and all of the apps and ops activities that are interacting with it has become a challenge of its own. Whereas a previous decade wrestled with big data, we believe the mission of this new AI-powered era is to wrangle 'big ops' – taming the scale and complexity of all the apps, agents, and automations interacting with this data."