Firstly, it is possible to be excited and worried by something all at the same time.
The Romantic poets knew this is the sublime that things are beautiful and terrifying at the same time. William Wordsworth in ‘The Prelude’ captures these feelings from an early memory stealing a boat, rowing onto the lake and being aware of a towering cliff above him in the dark as he rowed.
I struck and struck again,
And growing still in stature the grim shape
Towered up between me and the stars, and still,
For so it seemed, with purpose of its own
And measured motion like a living thing,
Strode after me.
So, as with Romantic poetry and AI.
The Martech Map has been a consistently useful document in previous iterations. It is useful for tracing progress and trends in what they describe as marketing technology. Hence portmanteu martech.
I thought it would be an idea to run their 2025 report through Google Notebook with the instruction to summarise it for a comms and PR audience who were not familiar with the topic.
Treat this as a starter for 10 and if you’re interested head back to look at what you’ve got.
For me, this is useful and the stand-out here is the speed of change and that people will need to get a hold of their data. The information being put into the AI tool will influence what it comes up with.
20 Key Points About AI in Martech for PR and Comms Professionals
Here are 20 points summarising the impact of AI on marketing technology (martech). This summary prioritises clear, plain English to address the needs of PR and comms professionals with limited knowledge of the subject:
1. AI is rapidly transforming martech. The rate of change is much faster than with previous technological innovations.
2. The hype around AI, particularly Generative AI (GenAI), is real but the underlying technology is steadily advancing. As AI improves and finds new applications, its impact will continue to grow.
3. AI in martech isn’t just a single trend, but a multitude of interwoven trends at different stages of development. This complexity makes it challenging to make sweeping statements about AI’s overhype.
4. AI is creating five key segments within martech: Indie Tools, Challenger Platforms, Incumbent Platforms, Custom Apps, and Service-as-a-Software.
5. Indie Tools are small, specialised AI tools that excel in specific tasks. They offer a way to experiment with new AI capabilities quickly and inexpensively.
6. Challenger Platforms are AI-native companies aiming to disrupt existing platforms. They offer innovative approaches but face challenges in displacing established players.
7. Incumbent Platforms are dominant martech companies rapidly embedding AI into their products. They leverage their large user bases and resources to compete with startups.
8. Custom Apps, often built with no-code AI tools, are enabling businesses to create tailored solutions. This trend is expected to reshape tech stacks and potentially surpass commercial apps in quantity.
9. Service-as-a-Software is emerging where AI turns labour into software. This opens up a market potentially worth trillions of dollars.
10. A strong data strategy is essential for any successful AI strategy. Businesses need high-quality, well-governed data to fuel AI algorithms and achieve differentiation.
11. The modern data stack, with cloud data warehouses at its core, enables a universal data layer for martech. This provides marketers with richer customer insights by accessing data across departments.
12. A universal content layer is emerging to complement the data layer. GenAI can leverage diverse content sources to enable hyper-personalised customer engagement.
13. APIs are becoming crucial for AI agents to interact with software and achieve their goals. Martech products with strong API capabilities will be better positioned in the AI era.
14. Marketers are primarily using GenAI for content-related tasks, such as content ideation and production. Accelerating the content development pipeline is a key driver of GenAI adoption.
15. GenAI is also being used to enhance data analysis and consumption. Features like summarization and “chat with data” are empowering marketers to leverage data more effectively.
16. Governance and ethical considerations are paramount in AI adoption. Businesses need clear policies to address concerns around data privacy, security, and responsible AI usage.
17. Marketers should focus on practical use cases and resist the temptation of “AI for AI’s sake”. AI should solve real business problems and contribute to tangible outcomes.
18. Collaboration between marketing and IT is essential for successful AI implementation. Data teams can provide valuable expertise and support to marketing teams.
19. Experimentation and continuous learning are key to navigating the evolving AI landscape. Marketers should adopt an agile mindset and be willing to adapt to new developments.
20. Businesses should prioritise ownership and control over their data. This will enable them to leverage AI effectively and adapt to changing industry dynamics.
Head to martech.com for the more detailed document.