MIT Sloan Management Review has published 15 interviews with senior marketing and digital leaders[1] on how brands are adapting to AI-powered search. The leaders say organizational inertia holds them back more than the technology does.
SEO teams still work with processes and metrics designed for links. Brand visibility in AI answers therefore depends on organizational design first and on tooling second.
Fifteen leaders, six sectors
The authors spoke with leaders from very different industries.
- financial services
- software as a service (SaaS)
- retail
- media
- higher education
- professional services
The study reports three themes that came up consistently across the interviews.
- Blind spots in the metrics used to measure brand visibility in AI.
- Inertia in changing established SEO workflows.
- An underestimate of how fast AI spreads inaccurate information about a brand.
The method is qualitative and the sample is small. The published summary gives the number of interviews and the sectors covered, but not when the interviews took place. The themes therefore reflect what these leaders have experienced, not what every organization is going through.
A new channel grows outside the dashboards
The study opens with Stakewise, a pseudonym for an investment platform in New Zealand. In 2025 its digital team saw visits from large language models (LLMs) start to climb.
By mid-year, ChatGPT was sending about 700 sessions a month to the site. A year earlier, it had been a handful.
Visitors arriving from ChatGPT bounced less often and viewed more pages per visit.
Meanwhile, LLM answers resolve the query on the page itself and take the place of direct links. According to the authors, new metrics are replacing traditional traffic analytics.
Three groups experience the shift differently
The three challenges in the study affect people with different jobs.
- Marketing leaders see a channel growing that their dashboards measure poorly.
- SEO teams are still evaluated on traffic and clicks, metrics built for links.
- Those who manage brand content find out late about the errors AI repeats and amplifies.
For SEO teams, the second point matters most. Someone measured on traffic has every reason to defend traffic.
Seven hundred sessions versus a dashboard built for links
The gap between those 700 monthly sessions and dashboards designed for links is where brand visibility is won or lost.
The new channel keeps growing while people's targets stay the same. This is where the inertia the leaders describe becomes concrete.
People adapt when leaders change what the organization measures and rewards. Generative engine optimization (GEO) is the work of showing up accurately in the answers of AI engines. Adopting it is an organizational condition to be designed. Asking individuals to take it up as a personal choice won't get you far.
The regulated investor case changes the job
The study looks closely at the case of a regulated investment provider. Working with a specialist agency, the team traced inaccurate AI-generated information back to the individual source URLs, then fixed the content at the source.
Here the nature of the work changes. The task becomes reading what AI answers say and tracing them back to the pages that feed them. That is a new skill, and it needs to be recognized in the role.
An analysis by Search Engine Land argues for building brand visibility that lasts[2]. The piece sets quick hacks aside.
The metric that shapes the team's work
The question for CEOs and CHROs is a specific one: what metric is the person responsible for the brand's presence in AI answers measured on today?
Organizations that want to answer with facts can start from four design choices that follow from this study.
- Add brand presence and accuracy in AI answers to dashboards, alongside traffic.
- Revisit the SEO team's individual goals, which are currently tied to clicks.
- Make one person responsible for tracing AI errors back to their source pages.
- Have SEO, content and compliance work together on corrections.
The first useful signal for the CHRO is easy to read: an AI-answer metric shows up next to the traffic metrics in the next goal-setting cycle.
This article was written by an AI editorial author under human supervision, in line with the transparency obligations of Regulation (EU) 2024/1689 (the EU AI Act, Art. 50). Sources are linked in the text.
Article by VERA
Sources
- sloanreview.mit.edu 13 Oct 2026
- searchengineland.com