The Brand Marketer's All-inclusive Guide to Generative AI

Generative AI is all the buzz, but what is it, and how can marketers harness its potential to create and scale relevant, personalized, and data-driven content experiences?

In November 2022, ChatGPT, an artificial intelligence chatbot and the fastest-growing app in human history, took the marketing world by storm—introducing new possibilities for content creation, optimization, and distribution.

Since then, countless new tools leveraging GPT and other large language models (LLMs) have promised to improve efficiency and effectiveness at every step of the content creation process.

But generative AI isn't a magic button you can press to put your content strategy on autopilot. It's a powerful tool that, when applied correctly, can expand the reach and relevance of your content marketing through a wide range of use cases.

Whether you're a c-suite executive weighing generative AI's risks and benefits or a seasoned marketer considering how to leverage AI to give your overtaxed team some relief, this guide will provide valuable insights, best practices, and real-world examples to inform your approach. Let's get started!

Understanding Generative AI

Generative AI: Pros and Cons

Generative AI and Search

The Skyword Difference

Understanding Generative AI

What is Generative AI?

Generative AI is a subset of artificial intelligence. It's a type of machine learning in which algorithms "learn" from existing content (text, images, audio, etc.) and use those learnings to create new content autonomously.

More advanced generative AI models, such as Open.ai's GPT and Google's Imagen, have been designed to produce written text, images, audio, and other types of content based on text-based directives (aka prompts) from users. With the right training data and the right prompts, the creativity and coherence of these models' outputs rival those of human creators.

How can marketers leverage generative AI?

There are many ways to use AI in marketing. Some use cases include:

Content planning

Generative AI can analyze text from source material, such as blog posts, books, social media posts, or conversations, to identify common or related themes and topics. The model can then be prompted to suggest possible directions or ideas for content development.

Examples:

Brainstorming - Take an interview transcript and use AI to generate a list of topics to explore in content pieces based on the interview.

Outlines - Take an identified topic and use AI to outline subtopics or points to address in a piece of content.

Market research - Take audience survey research and ask AI to identify common patterns or themes. Use the information to inform your content strategy.

Creator enablement

Generative AI can synthesize text and understand different style and editorial prompts. That makes it a powerful tool for organizing unstructured ideas or outlines into meaningful text, quickly generating and iterating on drafts, and ensuring the final copy is grammatically correct and fluid.

Examples:

Rough drafts - Take notes or topic ideas and use AI to generate sentences for the foundation of your article. Edit and revise the generated text to create a more polished piece.

Editing - Take existing copy and prompt AI to improve it by suggesting synonyms or asking content to be rephrased in a certain way.

Optimizing and scaling output

Because generative AI models can differentiate between content formats, interpret personas, and mimic a wide range of writing styles, they can help quickly reformat content for cross-channel promotion or generate new content for rote copywriting tasks.

Examples:

Personalization - Take a piece of content and use AI to incorporate language or topics relevant to a described audience.

Iterative assets - Ask AI to generate a tweet to promote an article or summarize the most important points of a whitepaper for its corresponding landing page.

Copywriting for promotions, ads, and CTAs - Ask AI to read specific text or a text-data combination and generate ad copy, promotional copy, or CTA suggestions based on the source material.

Optimization - Take an existing article and use AI to incorporate specific keywords or facts provided by you. Prompt AI to revise or fine-tune language to improve readability, engagement, and conversions.

Globalize content - Create a piece of content and use AI to translate it into multiple languages to reach a wider audience and speed time to market.

Branding and design

Some generative AI models can play a significant role in branding and design by offering creative assistance, generating novel ideas, and streamlining the design process.

Examples:

A/B testing - Automate the creation of design variations for landing pages, email templates, or website layouts. Test multiple options simultaneously, collect data on user interactions, and leverage the most effective design elements.

Image generation and selection - Take an article and use AI to select an image or images from a specific database to accompany the copy.

Logo and visual identity creation - Input your desired parameters or style preferences into an AI model to generate a range of logo designs, color palettes, typography options, and other visual elements that align with your brand identity.

Tone of voice - Train AI models on extensive datasets of existing brand communications and textual content to ensure they learn and replicate your brand's preferred tone, style, and language to create consistent and on-brand copy for every channel.

Will generative AI replace my human content creators?

Generative AI, as it exists today, is not reliable enough or capable of the critical and creative thinking required to replace human creators completely. To efficiently scale while maintaining the quality your customers expect, you'll need to deploy AI in a structured environment and have a combination of human insight and oversight involved in the process.

"Generative AI can augment existing human creative capabilities in content marketing and significantly impact tech marketers' productivity. It works best when used as a content enablement tool that's regulated by human oversight, helping to create, classify, share, or optimize your content."

(Source: Gartner, How Tech Marketing Teams are Capitalizing on Generative AI to Improve Content Marketing, 2023)

Human experts add invaluable specialized knowledge and perspective to content. AI models don't have the same ability to develop unique patterns and insights, reflect on complex topics, uncover new facts, or integrate authentic personal experiences. Because of this, brands should use AI to enhance human creativity—not replace it.

However, with the right AI-powered toolkit, you can save your team and creators time on tasks like summarization, iteration, and customization, enabling them to produce and release high-quality content faster.

How will generative AI impact customer behavior?

If you're concerned about the potential impact of AI-generated content on brand trust, you're not alone. Based on historical evidence, there are some likely outcomes as more AI-generated content becomes prevalent:

Trust in brand marketing may decline as the amount of online low-quality 'bot' content increases and browsers and platforms incorporate AI detection and warning tools to prevent misuse and the spread of misinformation.
Consumers will expect even more relevant, customized, and convenient content experiences. Experience quality will play a more significant role in purchase decisions as buyers become accustomed to having hyper-relevant information at their fingertips.
Buyers could rely more on human recommendations, stories, and customer testimonials. Some may even turn away from conventional digital platforms and seek out 'verified human' sources that have emerged in response to consumer mistrust.
Consumers will become more reliant on the convenience of conversational AI as it's embedded into more platforms and devices, spending less effort on independent, cross-platform research.

As such, focusing on how AI can enhance quality and customization at scale is essential rather than viewing the technology as a cost/volume play.

Seek vendors knowledgeable about the technology and your use case who can apply it effectively and responsibly and manage and mitigate any risks on your behalf. This approach will help you maintain high-quality content standards while incorporating AI as a helpful tool in your content creation process.

Generative AI: Pros and Cons

With ChatGPT's public release, interest in generative AI has skyrocketed. But before using the technology, marketers must understand the risks and limitations that come with using AI for content creation.

What are the benefits of AI-generated content?

AI models offer an efficient and cost-effective way to scale content creation.

More than half of marketers (62%) say they've invested in the power of artificial intelligence (AI). - Salesforce State of Marketing, 8th Edition, 2023

AI writing tools can personalize content tailored to different audiences, generate content in multiple languages, and create initial drafts or outlines in seconds, freeing human writers to focus on more complex and creative tasks, such as editing and refining.

And that's just the tip of the iceberg.

What are the risks associated with generative AI?

LLMs like GPT which powers ChatGPT, have fundamental limitations that can introduce significant security and reputational risks if left unaddressed. Here's why:

They make up facts and present them as confident truths. Because models have limited training data to draw from in creating new content, they're known to fabricate information or "hallucinate"— answering questions with plausible but untrue assertions. Similarly, inherent biases and inaccuracies in training data can lead to models reinforcing bias, prejudice, and misinformation. Spreading misinformation, even inadvertently through the negligent use of AI, can have disastrous consequences for your brand. That is especially true for those in highly regulated industries, such as healthcare or finance, where regulatory bodies can impose public censures and fines.
They present intellectual property (IP) risks. AI content generators don't cite sources. Publishing the information they generate whole cloth can expose you to copyright, trademark, or patent infringements. Also, feeding your brand's IP or sensitive data into openly hosted applications can expose that information to other users and be stored in the AI's training data.
The algorithm can not apply critical thinking, empathy, and real-life experience like humans. Therefore, it is not a reliable source for predictions, advice, or recommendations. Predictive AI models exist, but they involve a different type of machine learning.
From a cyber security standpoint, AI tools are vulnerable to hacking and misuse. It only took one security researcher a few hours to break GPT-4. He designed prompts to bypass OpenAI's security and quickly trained the model to create phishing emails and other inappropriate things. Safeguarding AI systems against this type of malicious exploitation is an ongoing challenge.
Your proprietary information isn't safe by default. When you feed private information into a generative AI technology, you open that knowledge to the public domain. Improper handling or unauthorized access to sensitive data used by AI systems can result in privacy breaches and misuse of personal information.

Generative AI and Search

When it comes to understanding the influence generative AI will have on Search Engine Optimization (SEO), there are two aspects to consider. First, what are the consequences of employing generative AI for content creation? Secondly, what happens when search engine algorithms and search engine results pages (SERPs) incorporate generative AI?

In this section, I'll unpack both.

Are search engines penalizing AI-generated content?

At the surface level, no. Google and Bing have explicitly stated that whether or not AI generates content is not a factor in rankings.

Search algorithms do continue to prioritize high-quality content catered to user needs while devaluing low-quality, keyword-focused content written for SERPs. And material generated solely by AI often falls into the low-quality category, with hallucinated facts, unoriginal ideas, and an often repetitive, robotic writing style.

The volume of AI-generated content online will also raise standards for what it takes to rank on SERPs.

All factors considered, it's best to prioritize creating expert, original, and user-focused content to differentiate your brand from the vast amount of similar-sounding information indexed alongside it.

Continuing to follow Google's E-E-A-T search quality rater guidelines will help you improve page quality scores and rankings:

Source: fatjoe.

Is AI-generated content bad for SEO overall?

As noted above, even though creating content with AI won't directly impact your search rankings, using AI tools to create content from scratch could put quality rankings at risk.

There are a few reasons for this, including:

AI systems often produce generic, inaccurate content. The information AI models have to draw from is limited to the data they have been trained on. As a result, they are prone to fabricating facts and regurgitating commonly available advice. Given these limitations, it is crucial to use human editorial oversight and extensive fact-checking when publishing AI-generated content.
As generative AI gains in popularity, the risk of duplicate content grows. Ask ChatGPT or Bard to answer the same question several times, and you'll notice the algorithms begin to produce similar-sounding text each time. Amplify that by thousands of people submitting similar queries and publishing the text in their online content, and you have a recipe for disaster. Search engines will detect the similarity in content across URLs and categorize it as unoriginal, negatively impacting your search rankings.
Pure AI-generated content can not be copyrighted. But content created by humans and edited or optimized by AI can. You can reference the most recent guidance from the US Copyright Office to learn more.

Will my rankings suffer now that competitors can more easily publish content with AI?

According to Gartner, 30% of outbound marketing messages from large organizations will be AI-generated and human-augmented by 2025. That's up from less than 2% in 2022.

The growing prevalence of AI-generated content will inevitably intensify the competition to rank in search results. To improve your search visibility, you must differentiate your brand from the competition with content that checks the boxes for expertise, originality, usefulness, depth, and breadth of coverage, plus a superior user experience and metadata structure.

Which search engines use generative AI?

Currently, Google and Bing leverage generative AI in their algorithms and in conversational search models on their SERPs.

Searchers can access Google's beta Search Generative Experience (SGE) through Google Search Labs. It is powered by a variety of LLMs, including LaMDA (Language Model for Dialogue Applications) and PaLM 2 (Pathways Language Model 2) — the same core language models powering Bard, the company's new conversational chat service.

Anyone can use Bing's new generative AI-enabled search experience through the Microsoft Edge browser. It runs on a variety of AI models from Microsoft and Open.ai. The Bing chat module available on its SERPs is powered by GPT.

How will generative AI-powered search affect my content rankings and search CTR?

Google and Bing, the most popular search platforms, have introduced four new search features that will majorly impact SERPs and CTRs moving forward. These include:

1. Snapshot carousels with subject matter expert (SME) content - "Position Zero" has been replaced with an AI-generated answer and carousel of sources with the most organic clicks based on the current construction of the AI-powered SERP in Google's SGE. Those sources are served to the right of the answer, as in the example here:
  
  With position zero overtaken by AI, brands can expect CTRs from featured snippets to decrease. With position zero no longer ownable by a single source, your goal should be to become a frequently referenced source, showing up in the SME carousel and as much as possible elsewhere on the SERP.
  
  The tips for adapting your content strategy for new AI-powered search experiences below can help you accomplish that.
2. More prescriptive content suggestions - Google and Bing have also revamped the section below position zero to keep users engaged on their search platforms longer. This area now features more prescriptive content recommendations, including pages that address popular follow-up questions, pages covering related topics, and other deep-dive suggestions. The new layout creates more opportunities for brands to secure valuable SERP real estate than the previous list view. To make the most of it, strategically cluster your content into long-form pillar pages that extensively cover topics with related sub-topic content that dives deeper into spinoff questions and advice. For a leg up, use topics where you've already established authority and dedicate ample time to understanding the specific query language used by your target audience to explore those topics further.
3. Embedded conversational interfaces - Both Google and Bing have introduced a conversational interface directly on the SERP, enabling users to engage in a continuous conversation without generating new searches or navigating between different SERPs in their browsers. This interactive format allows users to ask follow-up questions, explore results, and seamlessly obtain information via a more conversational experience. This change increases the likelihood of users obtaining information directly on the search platform versus from your content written and optimized to answer their specific queries. But because the SERP and conversational interface will continue to suggest related web link options, it also gives your brand more opportunities to appear in search results, even within a single session.
4. Emphasis on entities - Entities are categories advanced search algorithms employ to group things with similar attributes. Think of people, places, objects, etc. While search engines previously relied on keyword density and proximity to gauge content relevance, modern search experiences analyze entities to understand the connections between different web pages and domains and deliver more accurate and intent-aware results. Consider the following:

Search for "oven cleaner" and "how do I clean my oven" on Google, and you get very different results. That's because the different ways users phrase queries signal their intent. In this scenario, the user googling "oven cleaner" is looking to purchase something, whereas the user querying "how do I clean my oven" is looking for information.

To rank well on SERPs from now on, you need to shift your strategy from keywords to identifying and understanding the intent behind the query and creating content that addresses what your target audience is looking to accomplish. Adapting your content strategy now, before the mass adoption of AI-powered search, will ensure you can improve SERP visibility in the new Google and Bing search experiences.

How can I optimize my content for the new search experiences in Google and Bing?

Follow these best practices to set your brand up for success:

Adopt a content cluster strategy - Focus on core topics, sub-topics, and follow-up questions to build a network of interrelated content. Doing so will signal greater topic authority to search engines and allow you to earn more positions on the new SERPs.
Optimize your content for engagement - Improve performance metrics such as time on site and pages visited to elevate your search rankings. You can do this by ensuring content is compelling enough to keep visitors on your website.
Scale SME content - Create evergreen SME content like webinars, podcasts, and demo videos. Repurpose it into blogs, checklists, and explainer videos to amplify your message. Tap into outside SMEs to fuel even more SEO gains.
Uplevel your user experience - Pay attention to page load speed, mobile responsiveness, and the performance of your multi-format embedded content to outrank competitors.
Create accessible, multi-format content - Incorporate a variety of content formats to engage a wider audience and boost visibility across Google and Bing's image, shopping, and video platforms.
Focus on long-tail, conversational search - Use natural language and target specific user intent vs. broad keywords.
Shift from keyword-focused to entity-aware - Identify, categorize, and align relevant entities on your web pages with search engine algorithms to rank higher in search results.

The Skyword Difference

As a content marketing company focused on helping brands fuel growth using expert talent and cutting-edge tech, Skyword is uniquely positioned to help clients safely and effectively incorporate generative AI into their content marketing programs. That's why we've introduced ATOMM™—Atomization for Targeted, Original, Multi-channel Marketing.

In this section, I'll dive into what our new AI-powered content marketing engine does, how it benefits marketers, and why it mitigates the risks associated with mainstream generative AI tools like ChatGPT.

How does Skyword use AI technology to improve content creation efficiency without compromising brand quality or integrity?

ATOMM™, powered by the latest GPT models, can efficiently analyze and atomize content created by our network of subject matter experts into an assortment of 'new' content assets customized for each of your target personas and channels.

From blog articles to social media posts to infographics and localized translations, Skyword's content atomization tool creates the assets you need to deliver personalized and on-brand content experiences at scale.

How does ATOMM™ work?

ATOMM™ leverages a vast library of templates created for specific content marketing use cases such as email, blog, and newsletter creation. These templates are calibrated to your brand's distinct voice, audience, and format requirements—requiring no front-end user prompts. With ATOMM™, your brand can strategically adapt one piece of content into multiple versions for different channels and audiences to instantly increase the reach and relevance of your messaging.

The content atomization process in Skyword360 takes just three steps:

Select your personas - Store details about the audiences your brand targets in Skyword360, and ATOMM™ will automatically adjust context and style based on each audience's unique descriptors.
Create a content package - Identify the original, human-created asset you want to be adapted, the audience you want it adapted for, and the content types you want generated.
Generate new content - ATOMM™ automatically analyzes your source content and generates the new customized assets, ready for human review, in seconds—not days or weeks.

What are the benefits?

Marketers who leverage ATOMM™ in Skyword360:

Save time and money on content creation - Quickly generate more assets from one piece of content and speed time to market in the process.
Meet search engine standards for quality content - Adapt original, human-generated content using cutting-edge AI written for your target persona and reviewed by expert editors.
Effortlessly scale the delivery of customized experiences - Customize content for various audiences at the click of a button and distribute the assets across different channels to instantly boost your reach and relevance.

What is content atomization?

Content atomization refers to breaking an anchor piece of content down into smaller, more focused assets, often in different formats, to reach a wider audience and maximize its impact.

Imagine taking a webinar, for example, and extracting and repurposing the key ideas and information to create multiple standalone assets such as a checklist, short video snippets for social, and a blog post.

Marketers who prioritize content atomization recognize that different individuals have varying preferences for how they consume information. Atomization allows you to cater to these preferences while efficiently scaling content production across multiple channels and personas.

The benefits include:

Expanded reach - Repurposing content into different formats and distributing it across various channels allows you to reach a wider audience and improve brand visibility.
Improved engagement - Catering to different personas, preferences, and consumption habits drives user engagement.
Time and resource efficiency - Instead of creating new content from scratch, atomization allows you to leverage existing content and adapt it for different formats, saving valuable time on creating, reviewing, and coordinating derivative assets.
Quality search rankings - Atomizing content allows you to target more long-tail queries on the same topic to improve authority, enhance your user experience with content formats that cater to user preferences, and interlink assets to help search engines better understand the relationships between your content pieces and improve search positions.
Consistent, on-brand messaging - Content atomization provides an opportunity to reinforce key messages and maintain a consistent brand voice across different assets, channels, and touchpoints.

How does Skyword's ATOMM™ differ from ChatGPT?

ChatGPT is an openly hosted AI application that users can interface with directly to generate content from scratch via text-based prompts. This unstructured environment allows users to leverage the GPT model for a wide range of text generation use cases.

Conversely, ATOMM™, Skyword's AI-powered content marketing engine, is a tool integrated into Skyword's secure enterprise-grade platform, Skyword360. ATOMM™ efficiently scales original, human-generated content by adapting it for different audiences, formats, and channels, leveraging a library of brand-customized content templates. Content is generated with no prompt writing required.

ChatGPT leverages a limited set of training data to generate content, does not cite sources, and is known to fabricate facts, stats, and quotes in its output. Without extensive fact-checking and human oversight—which undermines efficiency—there's no way for brands to ensure the quality and accuracy of content generated with the application.

ATOMM's outputs originate from original, high-quality source material and are reviewed by human editors. For this reason, our AI-generated content retains the originality, depth, and accuracy required to meet competitive brand and customer standards. Brands get all the benefits of AI scalability without the reputational risk.

Open applications, like ChatGPT, can store any information shared in the interface and leverage it as ongoing training data. Because ATOMM™ taps into AI models through a secure API, brand data is not saved, ingested, or used to train its LLMs.

How does Skyword mitigate risks associated with generative AI?

Every piece of content atomized by ATOMM™ undergoes automated checks for grammar, style, and plagiarized text. Next, Skyword completes an in-house editorial review to save your team time while safeguarding your brand's reputation. Lastly, our secure API guarantees your brand's data remains confidential—it's never stored, exposed, or used in AI training models.

Furthermore, according to the latest guidance from the US Copyright Office, content generated primarily by AI is not copyrightable. In contrast, content generated primarily by humans and adapted by AI is eligible for copyright. Because ATOMM™ adapts human-generated content for different audiences and channels, any content generated by the tool is legally 'ownable' by your brand.

Modern marketers must responsibly harness the power of generative AI to scale content creation and stay competitive. By using AI as an enablement tool in conjunction with human creativity, brands can drive exceptional results and differentiate themselves in the evolving landscape of AI-powered content marketing. Subscribe to our blog, The Content Standard, for the latest generative AI and content marketing updates delivered to your inbox.

Author

Jodi Cachey

Jodi Cachey is a dynamic content marketer with a talent for creating captivating stories that engage audiences and drive results. Throughout her decade-plus of experience in B2B tech, she has excelled in diverse roles, including business development, sales, content marketing, and product marketing. Jodi received her Bachelor of Science in Media Studies from the University of Illinois at Urbana-Champaign.

The Brand Marketer’s All-Inclusive Guide to Generative AI

Table of Contents