Harnessing AI's Potential: If, When, and How to Use It in Content Development

Can you tell which parts of this post were written by AI? Read first then click here to see if you were right!

Over the past year, the topic of artificial intelligence (AI) has displaced the hype of crypto and NFTs. At this point, you probably wouldn’t be shocked if AI was in the running for TIME magazine’s person of the year (is that even possible?). If you are a marketer, you are likely curious about AI's potential for writing, creating imagery, and other content forms and wondering whether it will reshape the writing, creative, and marketing industries as we know them. To be honest, we’re already full steam ahead as the world of content marketing and marketing in general quickly moves toward integrating Artificial Intelligence instead of relying solely on human efforts. In March of 2023, botco.ai surveyed 1,000 marketing professionals for their The State of GenAI Chatbots in Marketing report and discovered that 73% of marketers now use generative AI tools.

That’s a big chunk of marketers, but on the content and creative side, many are feeling anxiety and uncertainty rather than curiosity and excitement about potential uses of AI in their craft. 
You might worry about the diminishing role of talented human writers and marketers as AI emerges as a seemingly cost-effective alternative. Layoffs in the tech industry have added fuel to the fire, as companies took a hard look at where they invest their time and money, making the fears of being replaced a sad reality for many. 

A small but rising number of startup tech organizations have mentioned AI as a cause for cutting staff and reconsidering new recruits over the course of this year. A PR firm in France, replaced half of its staff with AI–a move that many others have taken in an effort to minimize costs and worries in the current state of the economy. 

What we can do, and what we have done at Beacon Digital, is experiment with any AI content tools we can get our hands on with the ultimate goal of creating better and more strategic content. The baseline for that is setting a process and mindset in place for understanding when to use AI versus when to use a human writer.

Spoiler alert: we don’t think it’s an either/or scenario. 

To put our thinking to the test, in this article we used three AI tools, Writer, Copy.ai, and ChatGPT, to create a seamless blend of content generation and the unique human experience through storytelling. As you read, see if you can discern what was written by a human and what was written by generative AI. Ultimately, AI lacks the ability to understand human emotion, brand guidelines, tone of voice — you know, the things that make content sing.

The growth of AI tools makes it easier for marketers to leverage this technology, specifically for content development.  For this article, we have found that relying on one tool was limiting in some areas of the creation process. The ideal approach when it comes to content creation or strategy involves a blend of AI tools with a modicum of finesse to craft engaging and original content. 

The tools we’ve used have been instrumental in crafting an outline and generating specific content segments while collaborating with a skilled human writer to ensure a harmonious and engaging narrative. This approach presents an example of how to blend AI technology and human creativity in content creation. (Please tell me you clocked this one as AI.)

The Evolution of AI in Content Development

To truly understand the role of AI in content creation, it's important to trace its evolution and existence in our lives to date. In its simplest form, AI can be considered a technology enabling computer systems to mimic human intelligence and behavior. The behavior is limited because of the nuanced emotions and capabilities that humans possess. 

AI has been around since the 1950s when Alan Turing first proposed his Turing Test to measure the level of intelligence exhibited by a computer. Since then, AI has made remarkable progress with applications for various tasks, such as natural language understanding and text generation.

As writers and marketers, you have been using tools with basic AI capabilities for years. A prime example is Grammarly. Grammarly employs a mix of machine learning, deep learning, natural language processing, rules, patterns, and artificial intelligence to enhance your writing.

One of the leaders in digital marketing, HubSpot, has been on an AI journey since 2015, with the development leading to the 2016 launch of their first experimental AI Chatbot – Growthbot. HubSpot Labs created this chatbot as a personal assistant for marketing and sales teams. Growthbot was only the beginning. From 2017 to 2019, they began to make several strategic acquisitions of AI companies to expand their AI portfolio. 

In 2017, after the acquisition of Kemvi, Bradford Coffey, HubSpot’s Chief Strategy Officer, stated, “At HubSpot, we’re incorporating machine learning and AI into the future of our marketing and sales tools. Using AI in the marketing and sales process creates a more tailored experience for the buyer and can help companies get found by more prospects, convert more leads, and close more customers.”

In 2020, HubSpot relaunched an updated version of their Marketing Hub Enterprise, offering advanced features, including AI-powered A/B testing, among other features that help to analyze website visitor behavior and preferences. All of which has been beneficial for marketing teams to understand their customer’s buyer journey better. 

Over the last few years, specialized Generative AI tools have become more common, broadening the availability and affordability for content creation and offering the potential to generate content for marketing purposes quickly. This ease of access has caused an influx of AI-generated content on the web and in search engine results. 

Generative AI is the behind-the-scenes magician of the tech world. It carefully studies data, whether text, images, or other media, and then, using what it has learned, crafts something new that feels right at home with the originals. It's trained to understand the essence of its input data and then use that understanding to produce fresh content. So, whether you're just getting acquainted or well-versed in the topic, Generative AI is an impressive blend of learning and creating. 

Quantity vs. Quality: Content Creation, Strategy, and Results

As AI technology advances, more tools are becoming available to marketers to generate content without a primary writer – making creating content quickly and cheaply easier. But quick and cheap does not guarantee the content’s accuracy and quality. A comparison between outputs from meticulously crafted and poorly designed AI prompts starkly highlights the quality variance, underscoring the importance of human intervention. 

Our team takes a human-in-the-loop approach, which  refers to using a human editor or writer to prompt, review, and curate AI-generated content before publication. Understanding that AI-generated content is prone to inaccurate information, errors, and a biased viewpoint is essential. 

Quality assurance is a critical step towards ensuring that the content will be accurate, checked for any editorial standards, and presents information that aligns with a brand’s voice, tone, and messaging. So while the process is sped up with the help of AI, the output maintains value and integrity and marketers and content creators have more time to consider the needs of your audience and research and to focus on strategy.

In September, we started experimenting with Adaptify to increase our content output on specific topics, mostly cybersecurity, and using AI to assist with SEO optimization. Our main goals were to maintain quality and test how a tool like Adaptify can help with our branded content. 

We have found that while we can generate more content quickly, we still need to integrate steps to ensure that all the content created meets our quality standards. The initial results have been fruitful. As you can see here, our article, Lead Generation Strategies for B2B Cybersecurity Companies, was published on September 6; after 1 month of publication, our article ranked for 16 keywords and position 9 for b2b cybersecurity. Since then, within 4 months, our article now ranks for 38 keywords, position 6 for cyber security lead generation, and position 10 for b2b cybersecurity. 

The rule of thumb is that content can take 3 to 6 months to rank for keywords, let alone the time it would take to break into the top 10 positions. With AI tools like Adaptify, we are looking at being able to do that in a shorter time frame. Google is changing how it looks at content ranking, so it's important to assess whether an increase in quantity output is the ideal outcome.    

SEO and the Future of Search

One of AI's main advantages is its ability to increase the amount of content for SEO benefits. The more content you have may sometimes be better, depending on the content you create. Producing and publishing content backed by a subject matter expert or providing new outlooks is still beneficial.

However, marketers must strike a balance between maintaining quality and creating a strategy that supports SEO growth. Over-relying on AI for content generation can lead to potential pitfalls, such as a lack of authenticity and relevance to the target audience's search intent. Not to mention poor content hygiene in tracking keyword SERP and when it may be time to optimize and update content. 

According to a survey conducted by Nigel Stevens of OGM, partnered with John Collins of Intercom and Ramp, they discovered a few interesting insights on how people view and search for content. The survey revealed that SaaS companies are ranked last in "trusted sources of information," and 55% of respondents agree that B2B content tends to have a uniform appearance. 

It's an issue that has existed long before AI-augmented content. Still, with the ability to mass produce content on a shorter timeline, the problem will worsen – posing a challenge to B2B companies to create unique content that sets them apart and resonates with searchers.  
 
Machine learning, often associated with AI development, can be summarized as "garbage in, garbage out," where the output quality depends on the input data quality. In this context, it's similar to the idea that in any system, such as a mathematical equation, the resulting output is unlikely to be accurate if the input is improperly specified. 

With many AI tools relying on the internet for data, a lot of poorly executed and inaccurate information is available. The result is poor data if left unchecked and recycled back into the systems it extracted from. Good output, while only as good as the data fed into the system, depends on "good" prompts written and provided to the AI tool. If you use a "poor" prompt, the result will be basic and likely not the outcome you sought. 

A well-crafted prompt provides the desired results and allows you to train the AI better to understand your brand, tone, and expectations. We used several prompts when using the AI tools for this article and even tested simplistic prompts with little guidance to compare results.

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Determining When to Leverage AI and Human Writers

As a marketer, knowing when to use AI-generated content is important. While it can help streamline content creation and strategy development, it's not a replacement for human creativity. Using AI-generated content should be seen as a supplement to human-generated content. For instance, marketers can use AI-generated content to generate ideas or curate content while relying on human writers to craft the content, which ensures accurate and engaging content with AI's help to speed up the process. 

An effective way you can use some AI tools is to search and parse data. For example, you can feed in details and information from past content to help formulate new concepts or ideas that support your current strategy. We have been exploring various scenarios where we can utilize AI effectively. Our experiments have focused on developing content strategies and outlines, scanning data to identify key points, and creating SEO-optimized content for some of our clients.

When deciding whether to use AI or human writers, consider content type, complexity, scalability, creativity, cost, efficiency, expertise, and ethics. Consider your goals, resources, and content nature when choosing between them.   

Ethical and Practical Implications of AI in Content Creation

As AI technology evolves, ethical considerations arise due to potential inaccuracies in AI-generated content. The most significant area of concern is plagiarism since it’s unclear the exact origins of the data gathered by AI. As marketers, we must ensure that AI-generated content is accurate, unique, and up-to-date, as this can directly impact the brand image and reputation. 

Best practices dictate, whether human or AI, to cite sources and appropriately attribute information or create original content. Only recently has ChatGPT enabled the 4.5 model to connect to the internet powered by Bing. Whereas other tools, like Google’s Bard, have had a direct link to their search engine. The internet is a vast, endless expanse of accurate, false, and fictitious information. 

Google is also becoming increasingly aware of AI-generated content and is taking steps to ensure that AI-generated content is accurately ranking in search engine results. Google has implemented a "content quality score" or Experience, Expertise, Authoritativeness, and Trustworthiness (EEAT) that takes into account the accuracy of the content, as well as the relevance of the content to the intended audience. 

In addition, Google has highlighted the ability of people to discern AI-generated content from human-written content. Google recently announced its stance and guidance on using AI-generated content, citing, "AI has the ability to power new levels of expression and creativity, and to serve as a critical tool to help people create great content for the web."

Conclusion 

AI's impact on content creation is undeniable. While it offers efficiency, marketers must balance quantity with quality. AI is a valuable supplement to human creativity, enabling streamlined content creation when used with human writers. Ethical concerns, like plagiarism and content accuracy, are critical considerations. Google's EEAT and guidance emphasize the need for responsible AI-generated content. 

The key is to discern when to use AI and when to rely on human writers, considering content type, complexity, creativity, cost, and ethics. AI and human creativity will shape content marketing's future. As we envision the future of AI and human collaboration in content development, it is crucial to advocate for AI's ethical and strategic utilization, ensuring that it serves as a complementary tool rather than a replacement for human expertise.

Learn more about our approach to Content Strategy and download our behind the scenes script to see how we created this article using AI and human-in-the-loop along with some of the prompts we crafted for each tool.  

Frequently Asked Questions

How can businesses ensure the originality of content generated by AI?

Ensuring the originality of AI-generated content starts with the foundation: choosing AI tools known for their advanced capabilities in producing unique content. It's about guiding the AI with unique prompts and company-specific insights, then layering human creativity atop AI suggestions to refine and personalize the output. Regularly using plagiarism checkers and encouraging content creators to infuse their personal flair and expertise ensures that even AI-assisted content reflects your brand's unique voice and values.

What are the ethical considerations when using AI in content creation?

Ethical considerations revolve around transparency, accuracy, and originality. It's important to be transparent with your audience about the use of AI in content creation when appropriate, ensuring the information remains accurate and reliable. Upholding ethical standards means using AI to augment human creativity, not replace it, and ensuring all content aligns with your brand's ethical guidelines and values.

How can B2B technology companies measure the effectiveness of AI-generated content?

Measuring the effectiveness involves tracking the same metrics as for human-generated content, such as engagement rates, conversion rates, and SEO performance. Additionally, conducting A/B testing to compare AI-generated content with human-created content can provide insights into areas where AI excels or needs improvement. Tools and analytics platforms that provide detailed reports on content performance are invaluable for these assessments.

What are the best practices for integrating AI into a human content team?

Best practices include starting with clear objectives for what you want AI to achieve within your content strategy, providing training for your team on how to use AI tools effectively, and establishing a workflow that allows for seamless collaboration between human creativity and AI efficiency. Encouraging a culture of innovation and open-mindedness towards AI among your team members can facilitate a productive integration of AI into content development processes.

Can AI help in understanding and targeting B2B buyer personas more effectively?

Absolutely. AI can analyze large volumes of data to identify patterns and insights about buyer behaviors and preferences that might take humans much longer to uncover. By leveraging AI for data analysis and buyer persona development, B2B companies can craft more targeted and personalized content strategies. AI tools can help refine buyer personas over time, ensuring content remains relevant and engaging as market dynamics and consumer behaviors evolve.