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Banking in the Age of AI Answers

PRecious Communications: Connected brand narratives key to AI visibility and credibility

Brands need to align their messaging across owned content, earned media, and customer evidence to improve how they are represented in AI-generated answers, according to a new study by PRecious Communications.

The research, PRecious AI Authority Index: Southeast Asia Banking 2026, examined how artificial intelligence (AI) represents banks across six Southeast Asian markets: Singapore, Malaysia, Indonesia, the Philippines, Thailand, and Vietnam.

The study analysed 2,740 AI-generated responses across four question groups covering business, trust and choice, authorities and society, and consumers. Questions were tested in eight languages to examine how banks appeared across different markets, languages, and customer needs. The research is a point-in-time analysis from August to October 2026.

The findings suggest that brands need to identify information gaps and maintain a consistent, accurate narrative across owned content, earned media, and customer evidence to strengthen their visibility and credibility in AI-generated responses.

AI-generated answers vary across services

The study found that when two tested AI services answered the same question and both named a bank, different banks appeared first in 43 per cent of comparisons.

This suggests that a bank appearing first in one AI-generated answer may not receive the same prominence on another service, even when users ask the same question.

For brands, the findings highlight the importance of understanding the questions their target audiences are likely to ask across AI services, as well as identifying which competitors appear most prominently in the responses.

According to PRecious Communications, brands should match their products and services to their audiences and inform their website content, case studies, and media engagement, with the aim of improving visibility in relevant AI-generated answers.

Brand visibility differs across question types and AI models

The study found that the banks appeared differently across questions relating to consumers, businesses, trust, and public roles.

The findings suggest that appearing first in an AI-generated answer does not necessarily mean a brand is represented accurately or comprehensively.

Beyond visibility, brands need to consider whether AI-generated descriptions accurately explain their products and services and whether the information is supported by current, relevant sources.

The research also found that different large language models (LLMs) drew on different information sources.

PRecious Communications recommended that brands clearly explain their offerings through owned channels while providing journalists with access to customers, original research findings and relevant expertise.

Regular reviews of AI-generated answers, alongside maintaining accurate and accessible information on owned channels, were also identified as important considerations.

Language influences how banks appear in AI-generated answers

The research found that the language used in AI prompts could affect which banks appeared in responses and how many were mentioned.

For example, Thai-language responses showed the most frequent changes in which bank appeared first within a particular question group, while Malay-language responses recorded the largest average reduction in the number of banks named.

These findings suggest that reviewing AI-generated answers in English alone may overlook differences in brand visibility and the emphasis placed on particular organisations.

For communications professionals working across Southeast Asia, the results highlight the importance of assessing AI-generated responses in the languages their audiences use.

 

Local market context shapes AI visibility

The study also identified differences in how banks appeared across individual Southeast Asian markets.

Some banks were frequently mentioned first across all four question groups, including DBS Bank in Singapore and Maybank in Malaysia.

In other markets, the bank appearing first varied depending on the question, while the most frequently mentioned bank was not always the one appearing first.

The findings suggest that a single regional communications approach may not adequately reflect differences in customer needs, product offerings and languages across markets.

PRecious Communications recommended that brands assess local customer needs, relevant products and language preferences before determining their content and media priorities.

Applying the findings beyond banking

Although the research focused on the banking sector, PRecious Communications suggested that its approach could also inform communications planning in other industries.

The study emphasised the importance of understanding how brands appear alongside competitors in AI-generated answers and identifying where information may be incomplete, inconsistent, or inaccurate.

It also highlighted the value of connecting earned media, owned product content and customer evidence into a consistent brand narrative that can be adapted across different formats and markets.

What communications professionals need to know

The research suggests that AI visibility is not simply a matter of how often a brand appears in generated answers. The accuracy, relevance, and consistency of the information presented also matter.

For PR and communications professionals, the findings point to the importance of reviewing how AI platforms describe their organisations across different customer needs, languages and markets.

The study also highlights the role of earned media alongside owned content and customer evidence in supporting a credible and consistent brand narrative.

Rather than producing more disconnected content, communications teams may benefit from identifying information gaps, maintaining current and accessible sources, and aligning their messaging across channels.

These considerations could help organisations assess how effectively their existing communications support accurate brand representation in AI-generated answers.

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What AI thinks about your company matters more than where it ranks

In February 2024, Gartner published a prediction that sent a wave of anxiety through the communications and marketing industry. By 2026, the research firm estimated, search-engine volume would decline by 25 per cent as consumers shifted their questions to Gen AI tools, chatbots, and virtual assistants.

Warnings followed about the demise of traditional search, the disruption of Google's dominance, and the collapse of website traffic. Two years later, Gartner's predicted decline has not materialised. In fact, Google says search queries are at an all-time high, with more than five trillion searches conducted annually. Generative AI search is an increasingly significant part of that activity. According to Similarweb's July 2026 analysis, Google's AI Overviews appeared in more than 43 per cent of US searches and Google's AI Mode has surpassed one billion monthly users globally.

But for communications professionals, the preoccupation with generative AI search volumes and visibility has obscured a more consequential development. Generative AI is increasingly helping people find and interpret news, shaping how they understand organisations, and form opinions about them. In doing so, it is becoming an influential voice in its own right and one we have to manage.

Generative AI: The new battleground for corporate reputation

Communications teams have long recognised the importance of engaging with influential voices. Journalists, commentators, analysts, and social media personalities all occupy a central place in communications strategies because of their ability to shape public perceptions. Generative AI is becoming another vector of influence, with the potential to amplify an organisation's reputation across a vast audience that increasingly regards its answers as authoritative. Yet it remains far less integrated into communications plans.

Part of the problem lies in how generative engine optimisation, or GEO, is currently approached. Most GEO audits focus on rankings, citations, and visibility, treating AI much like another distribution channel. But unlike a search result, an AI-generated answer interprets sources, weighs competing claims, and presents its own characterisation of an organisation. Understanding how models "think", the assumptions and biases that shape their judgements, the evidence they favour, and the criticisms they consider credible, is critical to understanding how a company's reputation takes shape via AI responses.

Those assessments are not fixed. They can change as new information emerges, models are updated, and different questions are asked. A one-off audit provides a useful starting point, but communications teams need to monitor how AI's assessments evolve, just as they track changes in news coverage and public sentiment.

At Sequencr, we've been helping communications teams build that understanding, examining the reasoning and "thinking" behind models' assessments of their organisations and identifying the information that shapes them. Combined with ongoing monitoring, this intelligence can help shape earned media strategies that influence the answers and thinking of AI tools.

It also calls for a more discriminating approach to media relations. A story's value cannot be judged solely by the prominence of the publication or the size of its audience. A specialist article providing credible evidence about a company's safety record, for example, may prove more consequential to its reputation in AI-generated answers than a favourable profile that does little to address the underlying concerns.

And this is more than a theory. Recent studies illustrate just how much generative AI is changing the way people consume and evaluate news.

 

Four findings stand out:

1. Generative AI is becoming a new front page for news consumers

People are increasingly turning to AI for news. According to the Reuters Institute's 2026 Digital News Report, 10 per cent of respondents use AI for news each week, up from seven per cent in 2025.

What's more interesting is how they use it. Among those who access news through generative AI, 42 per cent ask follow-up questions and 35 per cent seek the latest news. For these audiences, AI is becoming part of the process through which they explore and make sense of events, giving its interpretation significant influence.

2. Generative AI is becoming an arbiter of authority

People are asking AI what to believe. According to the same Reuters research, 33 per cent of people who use AI for news ask the tools to assess the reliability of sources and the trustworthiness of the information.

Audiences are beginning to consult AI systems for judgements about credibility, giving the models a degree of authority that communications teams cannot afford to overlook.

3. AI is reshaping which stories and sources gain prominence

Generative AI selects which sources to use, which facts to emphasise, and which perspectives to include.

A 2026 study examining 14,212 queries across Google Search, Google's AI Overviews, and Gemini found remarkably little overlap in the sources presented. Source-overlap scores ranged from just 0.11 to 0.18, on a scale where 1 represents identical sets of sources.

The sources an AI system draws upon help determine the information and perspectives available to shape answers.

4. AI can help break through the filter bubble

A September 2026 study involving 37,561 readers of The Washington Post found that readers receiving AI-powered news were more likely to encounter information in common with others, while also consuming a wider range of topics themselves.

For communications teams, this raises an interesting possibility: AI could help organisations reach audiences who might never encounter their messages through the publications, commentators, or other sources they typically engage with.

Gartner's prediction focused attention on how much search traffic generative AI might displace. But the more consequential change for communications has little to do with search volumes.

Communications teams have long understood that reputation depends on what influential voices say about a company. The same principle now applies to generative AI. Where a company ranks or how often it is cited matters far less than how AI models "think" about it, and what informs those judgements.

It's time for generative AI monitoring and engagement to become as integral to corporate communications as media monitoring and social listening.

Matt Collette is CEO of Sequencr AI, a technology consultancy dedicated to unlocking the full potential of AI for marketing and communications teams. Before founding Sequencr, he was Head of Digital for Edelman Canada and later Global Head of Digital Growth, where he led efforts to embed generative AI across Edelman's global operations. Matt created the firm's AI task force, launched its first campaign powered by generative AI, and developed tools, prototypes, and training initiatives for clients and internal teams.

Read more from our columnists in The Earned View