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AI Risks: Can Artificial Intelligence Affect Your Brand Equity?

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The author’s views are entirely their own (excluding the unlikely event of hypnosis) and may not always reflect the views of Moz.

Brand equity — that intangible asset that sets your brand apart and directly impacts its success, can either flourish or wither at the hands of artificial intelligence (AI).

Using artificial intelligence in your external communications can be a threat to any brand equity you’ve built up, but does this mean you shouldn’t use it at all?

In this article, we’ll explore the delicate dance between technology and human connection, exploring the AI risks when it comes to your brand equity.

What is brand equity?

Brand equity is the value gained from a consumer’s perception of a company, service, or product — beyond its functional attributes. It is the cumulative effect of various factors that contribute to how a brand is perceived, recognized, and differentiated from others within its industry.

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There are four main elements of brand equity:

  • Brand awareness: The recognition and familiarity consumers have with a brand. If a customer has strong brand awareness, they are more likely to think of it when making purchase decisions — this is the first step to building brand equity.

  • Brand associations: The characteristics, qualities, and attributes that consumers associate with a brand. This can be through previous experiences, recommendations, or even online perceptions.

  • Perceived quality: The consumer’s perception of the overall quality of the brand. This will differ from person to person and does not always reflect the actual quality, instead being based on parameters that are important to the individual.

  • Brand loyalty: When a consumer chooses to buy from a particular brand over others. This could be related to repeat purchases or recommendations for higher ticket items, such as mortgages.

Brand equity will have a significant impact on the company’s success. Stronger brand equity often means brands can justify higher prices, enjoy customer loyalty, and be protected against competitors.

How does brand equity relate to AI usage?

Like everything else in marketing, AI can affect brand equity. With AI tools widely available, the two elements of brand equity that could be impacted are brand awareness and brand associations, i.e. what they see of your brand before having their own experiences.

When AI is harnessed effectively, it can either boost or erode brand equity depending on whether it enhances authentic customer interactions or turns them into robotic, disconnected experiences. In essence, the smart use of AI can either reinforce your brand’s value or, if mishandled, risk damaging the trust and emotional connections you’ve worked so hard to build.

How the overuse of AI can affect your brand equity

Brand equity is the culmination of years of trust-building, consistent messaging, and positive customer interactions. It’s the intangible asset that sets your brand apart in the hearts and minds of your audience.

The right AI-driven experiences can drive awareness and solidify positive brand associations in the minds of your customers. But while the temptation is there to utilize AI-generated content to speed up output, it’s important to know when to use it and when to stop.

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Dangers of overusing AI for your customer communications

AI can be a valuable asset, but it can also be a potential liability in your marketing toolkit. It’s crucial to tread carefully and be mindful of the potential dangers lurking when AI-generated content is used within your communications.

A graphic showing five dangerous of overusing AI: loss of personal touch, privacy concerns, not understanding intent, loss of brand identity, and lack of human interaction.

Losing that personal touch

Your brand was made by humans, for humans. If your customers start to feel as if their interactions with your brand are too automated and lacking that vital human empathy, the emotional connection you’ve spent so much time building will begin to weaken. For example, you ask an AI tool to produce an article around a specific topic, and you upload that content straight to your site without fact-checking or personalizing it. That piece will stand out from the articles already on your website, either because of the change in tone of voice or mistakes and inaccuracies within it, leading the reader to question your branding, authority, and trustworthiness.

That loss of personal touch to content can not only affect what your customers feel about your brand but can also impact your site’s ability to rank. A recent AI vs. humans experiment carried out by Reboot found that pages created by copywriters outperformed AI-generated content in search engine result pages (SERPs).

Privacy concerns

Using AI tools to collect and analyze personal data can raise privacy concerns within your customer base. Because artificial intelligence is about always learning and improving, AI tools will store any information put into them, which includes any data. Allowing another party to store customer data opens up more opportunities for it to be viewed, copied, and even stolen by outside sources.

If your consumers believe their personal information is being misused by AI tools or their privacy is compromised, you can erode the trust in your brand and damage your overall brand equity.

To negate these privacy risks, some AI tools give you the option to opt out of this data storage. On ChatGPT, for example, there is a setting you can use to prevent it from saving your chat history.

Not understanding intent

Understanding and fulfilling intent is what helps your content to rank, and keeps your customers happy. AI content tools and recommendation systems might be unable to pinpoint customer intent or preferences. Continually missing the mark of what your customers want could negatively impact their perception of your brand’s competence.

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If you’re looking to combat this pitfall, you can try asking the AI tool to create a piece of content with a particular search intent in mind. As with all content produced by artificial intelligence, though, this will need to be thoroughly fact-checked and edited by a skilled copywriter.

Loss of brand identity

Your communications could lack consistency with your brand’s image if they are solely produced by AI tools or even a mix of AI and human-generated content. Recognizable features of your brand are watered down, which could lead to confusion among your customers and a dilution of the all-important brand image.

Not only this but how can you be sure your tone of voice stands out when your competitors have access to the same AI tools? You know your brand best, and it is in your best interest to ensure any information you put out there is accurate, relevant, and on-brand.

Lack of human interaction

For complex or emotionally sensitive issues, customers might prefer human interaction rather than AI. If you don’t offer this option or rely too much on AI for customer service by only offering chatbots or email assistance run by artificial intelligence tools, you may start to notice increased dissatisfaction and reduced loyalty.

Can AI tools recreate recognizable brand communications?

As mentioned before, AI will affect your customers’ awareness and perception of your brand, primarily if you use it in your communications. Can you trust AI-generated content to adopt your tone of voice accurately?

Brand tone of voice is a direct manifestation of its personality and values. It’s what drives brand perception and feeds into equity if you take away all of the visuals, logos, and videos.

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Let’s see how a popular AI tool, ChatGPT, deals with mimicking the tone of voice of a famous and instantly recognizable brand.

AI tackles Cards Against Humanity

Cards Against Humanity has one of the most identifiable brand voices out there, which feeds into customer perception. There are specific qualities and characteristics that those familiar with the brand would expect from its communications.

To test out the AI tool, we input the prompt:

Please write a 120-word ‘About Us’ section to be used on the Cards Against Humanity website. Make sure this copy is instantly recognizable to customers by matching the brand’s tone of voice and style of writing.

The word limit was to make sure the copy fits in line with the existing page the brand already has. For reference, this is the brand’s current About Us page on the site:

A screenshot of the About Us page on the Cards Against Humanity site in 2023.
Cards Against Humanity

It’s short, to the point, and has brand-specific humor; it doesn’t take itself too seriously. It’s a tone that anyone familiar with the brand would associate with their messaging. But how will an artificial intelligence tool compare?

Going off the prompt, this is what ChatGPT produced:

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A screenshot of ChatGPT's version of an About Us page for Cards Against Humanity.

While the finished products are dissimilar, you can pick out inspiration from the brand’s existing content. With phrases such as ‘renegades of irreverence’ and ‘inner misfit’, Cards Against Humanity’s somewhat overtly offensive branding comes through.

However, Cards Against Humanity thrives within the sarcasm, self-deprecating space, which is where the ChatGPT content misses out. It doesn’t quite have that tongue-in-cheek humor that is apparent from its existing About Us page.

How this could affect brand equity

Consistent branding is pivotal in constructing and upholding a positive brand perception. If you’ve built up a consumer base familiar with a particular tone of voice and personality but then start to move away from this, you’ll go against their perceptions and chip away at their brand awareness.

Even though Cards Against Humanity has already formed relatively strong brand equity through years of consistent messaging and good-quality products, that doesn’t mean it’s invincible. If the brand decides to go ahead with AI-generated content for its future communications, it risks going against its consumer perceptions and damaging its brand equity in the long run.

Striking the balance between automation and the human touch

AI isn’t the enemy of brand equity. But you do need to be careful when using it. Balancing creativity caution with AI is like finding the perfect blend in your morning coffee — too much AI can leave a bitter taste.

You should aim to avoid your AI-generated content coming across as robotic or inconsistent with your brand identity. By selecting the appropriate AI tool and always referring back to your brand’s unique voice, you still have the ability to craft captivating content that truly connects with your audience. Here’s how you do it:

A graphic showing the four steps of using AI content successfully.

1. Have a solid TOV guide

Why is having a tone of voice (TOV) guide a big deal?

It’s a roadmap for your messaging, ensuring your brand always sounds like, well, your brand!

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This consistency is crucial for brand recognition and recall. When your audience can easily identify your style and personality across different channels, it’s like having a familiar face in a crowd — feeding into brand awareness and perception.

A well-crafted TOV guide can even set you apart from competitors in a sea of voices, helping you stand tall in your niche.

How to create a TOV guide:

  • Start by digging deep into your brand’s purpose. What’s your mission? Who’s your audience? What values drive your business?

  • Once you’ve got those nailed down, pinpoint your brand’s personality traits. Are you fun and casual, or all about professionalism?

  • Lay down some ground rules. Decide on vocabulary preferences, sentence structures, and even whether to use emojis (yes, they can be part of your TOV!).

But it doesn’t stop there. The key to a good TOV guide is keeping it fresh. Revisit and update it as your brand evolves. Get your team on board, train them up, and keep the dialogue open for feedback and tweaks.

2. Train AI tools to recognize and use your TOV

You can train many AI-content tools to use your brand’s TOV as you would with any new starter. Start by feeding it some of your brand’s past content so it begins to understand how you structure your sentences, how informal your messaging is, and how you talk to your audience.

Then, using Natural Language Processing (NLP) and machine learning, AI recognizes patterns in your communications and starts to produce similar content. With time and ongoing pointers, amendments, and tweaks, most tools can begin to recognize and use your TOV.

But remember, it’s an ongoing practice. You have to continuously fine-tune and review its outputs to keep it singing in perfect harmony with your brand’s voice.

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3. Monitor AI content and edit

Even after you’ve trained your chosen AI tool to mimic your brand’s TOV, you still have to thoroughly check and edit the content it has created. Just as you would proofread and edit any work from a content writer.

Monitor the output and use your TOV guide to ensure it hits the brand’s values, tone, and messaging standards. AI tools occasionally throw out incorrect facts or statements without context. Publishing anything incorrect that can be disproven by your audience will alter brand associations and even perceived quality, so it’s important to have a rigorous fact-checking system in place.

4. Test and give feedback to the AI tool

    Think of the AI tool as an eager employee. If you want it to improve, you need to provide thought-out feedback.

    Start by conducting structured evaluations of its outputs against predefined criteria, measuring aspects like accuracy, relevance, and adherence to your brand’s tone of voice.

    Then, maintain a clear and consistent feedback loop, offering specific and constructive comments to help the AI tool learn and improve over time, ultimately aligning it more closely with your brand’s unique requirements.

    How to safely build brand equity with AI

    The good news is that by adopting a thoughtful approach to AI and making some adjustments, you can generate content for your brand that is entirely distinctive and tailored to your identity.

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    There are some ways you can use AI tools that will work to spot patterns in your analytics to inform your ongoing strategies, as well as improve customer experiences.

    A graphic showing two ways to build brand equity with AI: Spotting data patterns and improving customer experiences.

    Spotting data patterns and unearthing customer insights

    Analyze customer data

    Some AI tools can analyze large datasets, such as customer churn rates and sentiment analyses on social media, to identify patterns, trends, and correlations. This valuable insight into customer behavior can help to inform your brand to craft personalized marketing strategies and improved user experiences, ultimately leading to better decision-making and enhanced customer satisfaction.

    It’s worth keeping in mind the privacy concerns point from above, though, making sure the AI tool you use has the option to not store chat history for this.

    Stay in the loop with social media

    There are AI tools that can track brand mentions, sentiment analysis, and emerging trends on social media. This will allow your social media marketing team to spend more time elsewhere, crafting perfect campaigns to work with the AI’s findings.

    Do market research

    Artificial intelligence has reshaped the field of market research, providing tools that can dissect data and generate invaluable insights. This is a great way to save your team time that would otherwise be used to analyze this data.

    An example prompt to do so could be:

    Generate a report summarizing the current market trends and customer preferences for [specific product, service, or industry]. Include information on key businesses and any notable shifts in consumer behavior. Please provide statistics and insights from the past year.

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    Improving customer experiences

    Personalize content

    After you’ve already used AI to sift through customer datasets, you can use the findings to produce personalized content tailored to their needs and preferences. This can span from customized product suggestions to tailor-made marketing messages.

    24/7 chatbots

    24/7 AI chatbots enhance the customer experience by delivering quick and reliable service around the clock — chatbot conversions are also pretty powerful for your bottom line. You can provide instant, consistent, and cost-effective customer support, handling routine queries efficiently and freeing human agents for more complex issues.

    Automatic subtitles and image captions

    With video becoming one of the preferred methods of consuming content, AI-powered subtitle generators such as Kapwing and VEED’s tools are getting increasingly popular. This helps with accessibility, which can improve user experience and save your team time.

    How to avoid AI risks when it comes to your brand equity

    Safely building brand equity with AI involves a strategic approach to harnessing the technology while mitigating potential risks. Here’s how to do it:

    1. Define your brand’s AI strategy: Begin by setting clear objectives for AI integration in your branding efforts. How will you use it? Will you use the tools to generate content, automate processes, or gather insights? Ensure you have answers for these and the goals behind them. What are you hoping to achieve?

    2. Apply strict quality control: Establishing a robust review and approval process for AI-generated content will help to protect your brand awareness, associations, and perceived quality. Human oversight will always be needed to catch errors and maintain consistency in messaging.

    3. Remain transparent: Maintaining transparency with your audience about your AI use will help to build and keep their trust. If chatbots or automated systems are handling customer inquiries, make it clear that customers are interacting with AI. If a blog post has been produced using AI, add a disclaimer about it highlighting who the piece was checked by to make sure you’re still hitting ‘experience’ and ‘expertise’ in E-E-A-T.

    4. Focus on data privacy and security: Safeguard customer data rigorously. Comply with data protection regulations like GDPR or CCPA, and communicate your commitment to data privacy to enhance brand trust. Similar to the above, share any instances where personal data is handled by AI systems and the steps taken to make sure it remains confidential.

    5. Be prepared for a crisis: Even with the most watertight approval processes, some mistakes still slip through the net. This is no different when using AI. To safeguard the audience trust you’ve built, ensure you implement a plan to address potential AI-related crises, such as misinterpretations or mishandling of sensitive issues.

    Key takeaways

    There will always be AI risks if using it in customer-facing content, but this doesn’t mean your brand shouldn’t use it.

    To successfully integrate AI into your brand’s strategies while building brand equity, you should ensure all uses align with the brand’s values, messaging, and customer expectations.

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    Have solid processes in place for everything from proofreading and fact-checking to keeping all customer data confidential. This way, you’ll be able to protect your brand awareness, associations, perceived quality, and, ultimately, your brand equity.

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YouTube Ad Specs, Sizes, and Examples [2024 Update]

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YouTube Ad Specs, Sizes, and Examples

Introduction

With billions of users each month, YouTube is the world’s second largest search engine and top website for video content. This makes it a great place for advertising. To succeed, advertisers need to follow the correct YouTube ad specifications. These rules help your ad reach more viewers, increasing the chance of gaining new customers and boosting brand awareness.

Types of YouTube Ads

Video Ads

  • Description: These play before, during, or after a YouTube video on computers or mobile devices.
  • Types:
    • In-stream ads: Can be skippable or non-skippable.
    • Bumper ads: Non-skippable, short ads that play before, during, or after a video.

Display Ads

  • Description: These appear in different spots on YouTube and usually use text or static images.
  • Note: YouTube does not support display image ads directly on its app, but these can be targeted to YouTube.com through Google Display Network (GDN).

Companion Banners

  • Description: Appears to the right of the YouTube player on desktop.
  • Requirement: Must be purchased alongside In-stream ads, Bumper ads, or In-feed ads.

In-feed Ads

  • Description: Resemble videos with images, headlines, and text. They link to a public or unlisted YouTube video.

Outstream Ads

  • Description: Mobile-only video ads that play outside of YouTube, on websites and apps within the Google video partner network.

Masthead Ads

  • Description: Premium, high-visibility banner ads displayed at the top of the YouTube homepage for both desktop and mobile users.

YouTube Ad Specs by Type

Skippable In-stream Video Ads

  • Placement: Before, during, or after a YouTube video.
  • Resolution:
    • Horizontal: 1920 x 1080px
    • Vertical: 1080 x 1920px
    • Square: 1080 x 1080px
  • Aspect Ratio:
    • Horizontal: 16:9
    • Vertical: 9:16
    • Square: 1:1
  • Length:
    • Awareness: 15-20 seconds
    • Consideration: 2-3 minutes
    • Action: 15-20 seconds

Non-skippable In-stream Video Ads

  • Description: Must be watched completely before the main video.
  • Length: 15 seconds (or 20 seconds in certain markets).
  • Resolution:
    • Horizontal: 1920 x 1080px
    • Vertical: 1080 x 1920px
    • Square: 1080 x 1080px
  • Aspect Ratio:
    • Horizontal: 16:9
    • Vertical: 9:16
    • Square: 1:1

Bumper Ads

  • Length: Maximum 6 seconds.
  • File Format: MP4, Quicktime, AVI, ASF, Windows Media, or MPEG.
  • Resolution:
    • Horizontal: 640 x 360px
    • Vertical: 480 x 360px

In-feed Ads

  • Description: Show alongside YouTube content, like search results or the Home feed.
  • Resolution:
    • Horizontal: 1920 x 1080px
    • Vertical: 1080 x 1920px
    • Square: 1080 x 1080px
  • Aspect Ratio:
    • Horizontal: 16:9
    • Square: 1:1
  • Length:
    • Awareness: 15-20 seconds
    • Consideration: 2-3 minutes
  • Headline/Description:
    • Headline: Up to 2 lines, 40 characters per line
    • Description: Up to 2 lines, 35 characters per line

Display Ads

  • Description: Static images or animated media that appear on YouTube next to video suggestions, in search results, or on the homepage.
  • Image Size: 300×60 pixels.
  • File Type: GIF, JPG, PNG.
  • File Size: Max 150KB.
  • Max Animation Length: 30 seconds.

Outstream Ads

  • Description: Mobile-only video ads that appear on websites and apps within the Google video partner network, not on YouTube itself.
  • Logo Specs:
    • Square: 1:1 (200 x 200px).
    • File Type: JPG, GIF, PNG.
    • Max Size: 200KB.

Masthead Ads

  • Description: High-visibility ads at the top of the YouTube homepage.
  • Resolution: 1920 x 1080 or higher.
  • File Type: JPG or PNG (without transparency).

Conclusion

YouTube offers a variety of ad formats to reach audiences effectively in 2024. Whether you want to build brand awareness, drive conversions, or target specific demographics, YouTube provides a dynamic platform for your advertising needs. Always follow Google’s advertising policies and the technical ad specs to ensure your ads perform their best. Ready to start using YouTube ads? Contact us today to get started!

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Why We Are Always ‘Clicking to Buy’, According to Psychologists

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Why We Are Always 'Clicking to Buy', According to Psychologists

Amazon pillows.

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A deeper dive into data, personalization and Copilots

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A deeper dive into data, personalization and Copilots

Salesforce launched a collection of new, generative AI-related products at Connections in Chicago this week. They included new Einstein Copilots for marketers and merchants and Einstein Personalization.

To better understand, not only the potential impact of the new products, but the evolving Salesforce architecture, we sat down with Bobby Jania, CMO, Marketing Cloud.

Dig deeper: Salesforce piles on the Einstein Copilots

Salesforce’s evolving architecture

It’s hard to deny that Salesforce likes coming up with new names for platforms and products (what happened to Customer 360?) and this can sometimes make the observer wonder if something is brand new, or old but with a brand new name. In particular, what exactly is Einstein 1 and how is it related to Salesforce Data Cloud?

“Data Cloud is built on the Einstein 1 platform,” Jania explained. “The Einstein 1 platform is our entire Salesforce platform and that includes products like Sales Cloud, Service Cloud — that it includes the original idea of Salesforce not just being in the cloud, but being multi-tenancy.”

Data Cloud — not an acquisition, of course — was built natively on that platform. It was the first product built on Hyperforce, Salesforce’s new cloud infrastructure architecture. “Since Data Cloud was on what we now call the Einstein 1 platform from Day One, it has always natively connected to, and been able to read anything in Sales Cloud, Service Cloud [and so on]. On top of that, we can now bring in, not only structured but unstructured data.”

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That’s a significant progression from the position, several years ago, when Salesforce had stitched together a platform around various acquisitions (ExactTarget, for example) that didn’t necessarily talk to each other.

“At times, what we would do is have a kind of behind-the-scenes flow where data from one product could be moved into another product,” said Jania, “but in many of those cases the data would then be in both, whereas now the data is in Data Cloud. Tableau will run natively off Data Cloud; Commerce Cloud, Service Cloud, Marketing Cloud — they’re all going to the same operational customer profile.” They’re not copying the data from Data Cloud, Jania confirmed.

Another thing to know is tit’s possible for Salesforce customers to import their own datasets into Data Cloud. “We wanted to create a federated data model,” said Jania. “If you’re using Snowflake, for example, we more or less virtually sit on your data lake. The value we add is that we will look at all your data and help you form these operational customer profiles.”

Let’s learn more about Einstein Copilot

“Copilot means that I have an assistant with me in the tool where I need to be working that contextually knows what I am trying to do and helps me at every step of the process,” Jania said.

For marketers, this might begin with a campaign brief developed with Copilot’s assistance, the identification of an audience based on the brief, and then the development of email or other content. “What’s really cool is the idea of Einstein Studio where our customers will create actions [for Copilot] that we hadn’t even thought about.”

Here’s a key insight (back to nomenclature). We reported on Copilot for markets, Copilot for merchants, Copilot for shoppers. It turns out, however, that there is just one Copilot, Einstein Copilot, and these are use cases. “There’s just one Copilot, we just add these for a little clarity; we’re going to talk about marketing use cases, about shoppers’ use cases. These are actions for the marketing use cases we built out of the box; you can build your own.”

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It’s surely going to take a little time for marketers to learn to work easily with Copilot. “There’s always time for adoption,” Jania agreed. “What is directly connected with this is, this is my ninth Connections and this one has the most hands-on training that I’ve seen since 2014 — and a lot of that is getting people using Data Cloud, using these tools rather than just being given a demo.”

What’s new about Einstein Personalization

Salesforce Einstein has been around since 2016 and many of the use cases seem to have involved personalization in various forms. What’s new?

“Einstein Personalization is a real-time decision engine and it’s going to choose next-best-action, next-best-offer. What is new is that it’s a service now that runs natively on top of Data Cloud.” A lot of real-time decision engines need their own set of data that might actually be a subset of data. “Einstein Personalization is going to look holistically at a customer and recommend a next-best-action that could be natively surfaced in Service Cloud, Sales Cloud or Marketing Cloud.”

Finally, trust

One feature of the presentations at Connections was the reassurance that, although public LLMs like ChatGPT could be selected for application to customer data, none of that data would be retained by the LLMs. Is this just a matter of written agreements? No, not just that, said Jania.

“In the Einstein Trust Layer, all of the data, when it connects to an LLM, runs through our gateway. If there was a prompt that had personally identifiable information — a credit card number, an email address — at a mimum, all that is stripped out. The LLMs do not store the output; we store the output for auditing back in Salesforce. Any output that comes back through our gateway is logged in our system; it runs through a toxicity model; and only at the end do we put PII data back into the answer. There are real pieces beyond a handshake that this data is safe.”

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