Why brand perception matters in the age of AI

Generative AI tools are playing an increasingly prominent role in how information is created, curated and consumed online. Whether it’s a search engine or a chatbot, consumers are becoming reliant on AI-powered systems.

But how is AI affecting brand perception, and what can companies do to ensure they protect and enhance their online brand reputation? Are there strategies you can use to shape how your brand is perceived both by AI systems and the people who use them?

We’ll explore all of this and more below, with a detailed look at how AI systems interpret brand information and tips for strategically optimising your brand’s digital presence.

The influence of AI on brand perception and consumer decision-making

Consumers are no longer solely influenced by traditional media or word-of-mouth recommendations. Today’s marketing landscape is a very different and much more complex place than it used to be.

Over the last couple of years, AI-driven platforms have begun to heavily influence purchasing decisions. This happens in a number of ways, from algorithm-powered product suggestions to summarised answers in generative search results.

Whether it’s Google’s AI Overviews, Amazon’s product recommendations or ChatGPT’s summarised brand comparisons, AI is becoming a trusted advisor for users making decisions (whether or not the results can actually be trusted is a separate issue).

But AI doesn’t create opinions from scratch – or even have opinions, for that matter. It learns from data. That includes user reviews, social media sentiment, press coverage and technical SEO signals.

If your brand reputation is weak or inconsistent online, AI is likely to reflect that weakness in the results it generates.

Consumers often don’t question the neutrality of these tools, assuming the recommendations and summaries are both accurate and unbiased. This means that when working on strategies for building brand trust and credibility, you must keep both customers and AI systems in mind.

How do AI models assess brand credibility and sentiment?

AI systems use natural language processing (NLP), sentiment analysis and content ranking algorithms to evaluate brands. It’s important to note that these models don’t interpret content with the nuance that a human analyst or reader would. Instead, they rely on patterns in the data.

Some key factors AI uses to assess When it comes to brand reputation, AI uses key factors to assess credibility, including:

• Sentiment across reviews and social platforms
• Mentions in trusted publications or high-authority websites
• Consistency of brand messaging and tone
• Domain authority and the quality of backlinks
• Accuracy and completeness of information on owned assets (such as websites, for example).

So if you have poor or inconsistent brand coverage online, AI may not rate your brand as credible or trustworthy. And unfortunately, negative brand mentions found online can be amplified by AI models. They can sometimes appear in summaries or recommendations without context.

This could be very bad for business, as Click Consult’s recent research on consumer perception of AI in marketing revealed that around 40% of those familiar with AI would trust AI-generated information as much as human-generated content.

This means that whatever AI says about your brand can directly impact consumer trust and purchase behaviour. Whether you like it or not, AI trust and branding perception are interlinked.

5 strategies for building a positive brand identity in AI search

To perform well in an AI-driven ecosystem, brands need to strategically optimise their digital presence. There are two key goals – visibility and credibility.

Here are some strategies and actions to bear in mind:

1. Create authoritative, consistent content

Ensure your website and third-party listings communicate a clear, consistent brand message and tone across the board.

Remember that AI systems value clarity and authority, so make sure you regularly update old content, remove duplicate content and maintain relevance.

2. Optimise for structured data

Use schema markup to help AI understand your content in context. This includes product reviews, service offerings, FAQs and organisational information.

3. Encourage positive reviews

One of the best things you can do to boost your brand image is to actively encourage positive customer reviews. These are a prime source of data for AI when it comes to brand reputation, as well as one of the strongest trust signals it relies on.

Aim to develop review strategies across Google, Trustpilot, Yelp and other niche platforms that suit your brand and customer base.

Don’t leave this to chance though, hoping that customers who’ve had a good experience will leave a glowing review. You should be proactive, setting up a structured, user-friendly process for customers to give feedback – and make sure you respond professionally to both praise and criticism.

4. Get cited by reputable sources

Backlinks still matter – not just for SEO, but also for ticking some of generative AI’s trust and branding credibility boxes. Work on digital PR strategies that secure your brand mentions in authoritative publications, choosing ones that AI systems are likely to crawl and trust.

5. Align with E-E-A-T principles

Google’s AI models in particular are trained on data that values Experience, Expertise, Authoritativeness and Trustworthiness (EEAT). So for all your online content, you should be working closely to these principles, doing all you can to highlight real-world expertise and demonstrate your brand as an expert in its field.

How to manage negative brand mentions and misinformation in AI

You may be working hard on strategies to boost your brand credibility and perception with generative AI in mind. But what do you do about negative brand mentions online – or worse still, misinformation about your brand?

Once AI models ingest a negative article, bad review or customer complaint, it can live on in summarised answers, responses or suggestions. This can happen even if the original content is old or inaccurate.

The good news is that there are some ways to manage this:

• Monitor AI outputs for your brand regularly
• Set up alerts and media monitoring to detect negative brand mentions
• Respond publicly and factually to false or damaging claims
• Update and optimise your own content to ensure correct information dominates.

If misinformation persists, you might want to consider working with a reputation management expert.