“The announcements and developments in [the generative AI] space keep on coming,” consultant Neil Perkin commented in the latest edition of Econsultancy’s quarterly trends series Digital Shift.
The Q1 2025 Digital Shift packed in insights about a raft of developments in the world of GenAI, from the intersection of large language models (LLMs) and search to the AI-enhanced martech landscape, to how marketers are adapting to an industry increasingly shaped by these new technologies.
Over the course of the session, Perkin answered questions on these themes, addressing the skills needed for new marketers entering the industry and the thorny problem of optimising for brand visibility in AI models as well as how brands can evaluate the suitability of AI-enhanced martech offerings.
New marketers entering the industry today are facing a unique challenge, as many of the tasks they would have tackled as a junior marketer working in lower-level roles are being automated and handled by AI.
At the same time, the need to develop the right skillsets to compete and stand out in the industry is as pressing as ever. Sixty-four percent of marketers who responded to Econsultancy’s latest Future of Marketing survey expected ‘Having the right skills and talent in place’ to increase in importance over the coming two years, while a need for skills and training was identified as one of the biggest challenges in making full use of generative AI – highlighted by 30% of respondents.
Perkin observed that “The fundamental marketing skills are more relevant than ever” in an AI-dominated marketing industry, specifically “the fundamentals of marketing theory, and how you apply marketing.”
He recommended steering clear of “more task-oriented things that can easily be automated” and instead focusing on more creative and strategic skills such as critical thinking, intuition and creativity – as well as the ability to get the most from AI. “If you understand AI, [and] can show that you, as a human, can work well with AI tools – that’s going to be a real benefit in the future.”
In sum, drawing on a point first made by PHD’s Rohan Tambyrajah, he said, “What can’t be automated should be elevated.”
The introduction of LLMs to search has continued to accelerate in recent months with the likes of Google and OpenAI vying to show they can offer the most useful answers to complex queries.
Open AI announced the formal launch of ChatGPT search, previously known as SearchGPT, in October 2024; while Google recently announced testing of a dedicated ‘AI mode’ in response to requests from “power users” to receive “AI responses for even more of their searches”. In addition to this, AI assistants such as Meta AI are being positioned as aids for supplying information and inspiration, which may involve surfacing and recommending brands. How those brands get selected though, is still murky.
Marketers who were once confident that they had a firm grasp on visibility in search may feel understandably unsettled by this new paradigm. How can they position their content and brand for the best chance of exposure?
Discussing this in the Digital Shift morning session, Perkin acknowledged that optimising for AI models is a relatively unknown area but added that “all the research seems to be showing that good SEO practice for Google is ultimately going to stand you in a good position to benefit from AI agents as well.
“…It’s interesting that a lot of the AI agents seem to be drawing a lot of their inputs from high-ranking Google results, which would suggest really that [AI agents have] a sort of similar way of understanding what the kind of authoritative content is out there,” he explained.
A new metric, ‘share of model’, has also gained attention as a means of understanding how and why LLMs will surface a brand, enabling marketers to adapt accordingly. Perkin noted that a metric like share of model may produce different results to search and SEO tools, which is not a bad thing – instead, share of model can “augment what you’re doing [with SEO] and … plug any gaps”, while helping to “identify where you’re strong and where you’re weak in a way that you can’t do with traditional SEO tools”.
“[So,] use those models as well, would be my recommendation,” he concluded.
Generative AI-enhanced martech promises marketers game-changing (as well as resource- and time-saving) innovations, but in a landscape that changes so rapidly, it can be difficult to identify the most effective or appropriate solutions.
Perkin advised organisations who are unsure where to start in a sea of AI-enhanced martech to, “Look for quick wins and easy wins as a way into the whole topic area.”
[The data] suggests that a lot of benefit is coming from quite executional stuff right now…”
He pointed to data from Econsultancy’s ‘Future of Marketing’ report, which found that for the majority of marketers using GenAI tools in various use cases, the tools had either lived up to or exceeded expectations, particularly in the realms of data processing and interrogation, personal productivity, and consumer insight.
“[The data] suggests that a lot of benefit is coming from quite executional stuff right now,” Perkin said. “I would start there, because they’re the obvious place to start to actually just learn a bit more about the value that [AI tools] can bring.”
“And then I would expand into more complex use cases, and maybe looking at a task-based approach,” Perkin recommended. “If you map out processes and workflows, and understand the different tasks and the flow of those different tasks, you can look for opportunities to introduce different generative AI tools – appropriately, of course – at different stages through processes and workflows to help augment efficiency.”
If you are a capability leader looking at ways for marketers to prepare themselves for this new landscape, join Econsultancy at the Marketing Capability Leaders’ Forum on 12th June – where an expert panel will discuss how capability programmes can build resilience amid rising pressures.