8 Insights Your Portco Must Know About AI and Content Creation

Robert GammonPractice Leader, Revenue Operations

June 5, 2024 in Revenue and Market Intelligence, Revenue Operations

Understanding the myth and reality about AI and content creation will help portfolio companies optimize Go-to-Market content production. 

(This blog post is Part 2 in a two-part series on achieving optimal results from emerging AI technologies. Read Part 1 here.)

Many businesses jumped on the generative AI bandwagon and began producing high volumes of content. But should they? Maybe not, according to multiple industry reports. 

Large-language models and generative AI can pump out dozens of emails, blog posts, reports, and more in minutes versus weeks. Companies should practice restraint with these new tools. In particular, they should understand the risks and limitations. These include which types of content are appropriate for AI production and which are not. 

Buried in the hype are many pitfalls of AI-generated content production. These include originality issues, inaccuracies, and lack of depth. All these concerns can be summed up in one sentence posted on Reddit: “It’s ironic how everyone wants to use AI to create content, but no one wants to read content made by AI.”

What You Need to Know About AI and Content Creation

Cortado Group’s Revenue Operations Practice Leader, Robert Gammon, guides multiple portfolio company leaders to leverage AI. This begins with greater intelligence and revenue potential from their data. He has seen an increase of companies relegating their content creation to AI tools, but not always achieving the outcomes they desired.  

“Not all content is created equal, and AI is not always the right process for creating all types of content,” according to Gammon. “AI tools should not completely replace human content creators. Instead, they should be used where they’ll have the greatest impact in the content creation workflow.”

Here are eight points Gammon wishes every portco understood about AI and content. Study these before embracing the technology for wholesale content creation of unremarkable content that disappoints. Instead, embrace the technology with your eyes wide open to its strengths and weaknesses to create remarkable content.

1–Great speed does not mean great content 

All companies today have a need for speed. There’s never enough time to do everything, including feeding the insatiable marketing content monster. 

To stay relevant and competitive, businesses need to produce a never-ending supply of content — from blog posts to reports to emails. When large-language models appeared on the scene, the temptation to relegate all content creation to the generative AI tools was an overreach. 

Who wouldn’t like a 2,000-word blog post produced in just minutes versus days? But high-speed content production does not equate with high-quality content production. According to a study by Authority Hacker, “85.1% of AI users use the tools for article writing and content creation,” and “AI technology increases business productivity by 40%.”

Here are a couple things you risk losing when you rely too heavily on AI-generated content. The lack of originality and expert-level insights. And there are a few things you risk gaining, like errors and claims of plagiarism.

In one cautionary tale, CNET’s in-house AI model made mistakes, like transposing numbers, misspelling company names, and plagiarizing without proper citation. Competitors put the company on blast, and its reputation suffered.

The value of content has already been dropping since the glut during the pandemic. According to Edelman, 71% of decision-makers say that half or less of the thought-leadership content they read or watch gives them any sort of valuable insights. 

While you may have created a blog post or report in minutes, ask yourself these questions before sending it out into the world:

  •       Is it interesting and original?
  •       Does it accurately represent our company’s expertise and quality? 
  •       Will anyone want to read it? 

2—AI is the right tool for only some types of content 

Despite the risks, more AI-generated content is flooding the marketplace every day. However, that flood may turn into a drip as soon as the next wave of AI content review tools hits the market. Blocking tools, detection algorithms, and data-use regulations can stop AI content in its tracks. Experts expect them to help rebalance the scales toward quality content and their demand for authentic, high-quality content. But why wait?

Take a proactive approach now to leverage AI in the right ways. Produce content in a way that works with AI’s strengths. To know what content fits well, we can look to where it’s been used the most: corporate earning summaries, sports score aggregation, and natural disaster statistics reporting. For example: 

  • The Los Angeles Times: Uses AI to gather data and report on natural disasters, like earthquakes.
  • The Washington Post: Uses AI to generate sports event coverage, election reports, and alerts.
  • Forbes: Uses AI to create rough drafts and story templates for articles.

These types of content creation share a similar characteristic: they tend to be dry facts. Naturally, a machine is a great tool to gather this type of information rapidly. 

The types of content that are least suitable to be produced by AI algorithms are those that require creativity, originality, and personal experiences. Content such as thought leadership articles, consultative reports, and first-hand reports from the field require a dose of human writing or editing. 

One retail marketing study found that using generative AI for social media content creation diminishes perceived brand authenticity. This is because while generative AI is good at mimicking human-written content, it’s not actually capable of it. Top-tier content still requires deep research, critical thinking, real-life experience, specialized knowledge, and creativity — and that still requires talented human beings. 

3—Prompt engineering is an essential content creation skill

It wasn’t until 2023 when the term “prompt engineering” entered the vernacular. McKinsey reported that almost immediately, 7% of respondents to a survey said they were hiring for roles in prompt engineering.

Prompt engineering is the art of writing directions or prompts (input) to get a specific response (output) from a large-language AI model. It’s crucial to know how to create prompts that will unlock insights, generate ideas, and solve problems. A bad prompt will deliver a weak or useless response. A good prompt will deliver a response that is valuable. 

Prompt engineering best practices include: 

  • Be specific: Specificity will minimize ambiguity. Include context, format, length, detail level, tone, and style.
  • Provide examples: This can help the AI models understand what you’re aiming for.
  • Specify your desired output: State the format and structure you want, for example, a summary, detailed report, or narrative format.

 4—Vigilantly check for plagiarism in AI-generated content

Plagiarism detectors aren’t new. Companies have been using them for years to ensure their content isn’t plagiarized. The tools search content, looking for exact matches in keywords, phrases, entire sentences. or even paraphrased copy. 

Since the release of ChatGPT in 2023, checking for plagiarism has become even more relevant. The risk is that while AI-generated content may not copy chunks of text word for word, it can paraphrase content on which it’s been trained. If your content does contain plagiarism, you would be held responsible, not the AI tool you’re using. 

To play it safe, your company should also double- or triple-check AI-generated content using plagiarism tools, such as:

The plagiarism detection tools are particularly important in light of a study at Northwestern University that found that human content reviewers find it difficult to detect AI content. Human reviewers were only able to recognize ChatGPT-generated research papers 68% of the time, and they erroneously identified 14% of real documents as counterfeits.

5—Use AI to analyze data and personalize content

Delivering high-quality, personalized customer experiences is table stakes today. Without them, buyers are likely to move on to the next vendor. Delivering more personalized experiences is the right path for staying relevant and being a thought leader in your sector. In fact, three out of four business leaders believe that personalization is critical to their company’s success.

Personalized experiences in the B2B world include factors such as customized content, personalized messaging along the buyer’s journey, and tailored sales experiences. To have an impact, personalized components need to consider exactly where each potential buyer is in their journey toward a purchase. This is an area where generative AI can give you a significant advantage.

Here are some of the ways AI models can help you deliver more personalization: 

  • Complexity: AI-powered personalization uses sophisticated machine-learning algorithms that have greater capacity and are more nuanced. They can analyze complex data sets, detect subtle preferences, and deliver precise guidance.
  • Real-time: Instead of operating on a set schedule, AI-driven personalization can deliver up-to-the-minute insights on consumer interactions, so companies can respond fast.
  • Predictive: Along with reacting in real-time to customers, AI models can also anticipate consumers’ individual behaviors, needs, and wants.

6—Use AI to optimize content for SEO

Search engine optimization is an essential function for any business with a website — and that’s everyone. It’s the most fundamental way to drive relevant organic traffic to your website. When SEO is optimized, companies can be rewarded with a high ranking on search pages. If SEO isn’t optimized, companies risk falling below others. But doing SEO well is time-consuming. Enter AI. 

Like content creation itself, AI can also speed up content-related tasks, like SEO. This is not a new capability. Google has been employing AI for SEO in nine ways over the past two decades. 

How can AI relieve you of manual, time-consuming SEO tasks and help you strengthen your SEO with AI? Here are two leading ways: 

Keyword research: AI can improve your keyword search capabilities and suggest keywords that improve your search results in three key ways:  

  • Finding search terms your buyer personas use
  • Analyzing search results in ways that help you understand your target audience better
  • Apply keywords to your content strategy to garner greater impact

Content optimization: This is all about making sure your content is positioned to generate the best possible search result outcome. Doing this manually can be very time-consuming. But AI can speed up the process significantly and return better results. In a study, Semrush found that over 53% of marketers saw engagement increase after they optimized their content. Also, 49% said their rankings and traffic had improved. They achieved those outcomes by letting AI writing assistant tools find exactly how to boost the quality of the content. 

7—Prioritize data along your buyer’s journey

Marketers understand the need to create content strategically to appeal to buyers at every stage of the purchase journey. But this mission can be easier said than done. It requires a deep and actionable understanding of buyers’ challenges and needs at every stop on the journey. It can be a struggle that eats up vast amounts of time. 

This is one area where AI can make a huge impact by helping you speed up the process of repurposing your content. For example, AI can take a generic blog post and transform it into three completely different blog posts that resonate with the three leading phases of the journey — awareness, consideration, and decision. 

The benefits of enlisting AI to help repurpose content include: 

  • Accelerate efficiency: Humans don’t have to spend hours or weeks researching and writing original content for multiple pieces of content. They can write one version and let the algorithms take over.
  • Improved audience targeting: AI can help tailor your message to resonate with your ideal customers’ needs and challenges at each stage.
  • Enhanced content performance: Because you’re able to produce more content that speaks to each journey stage, you’re likely to drive greater success. Buyer-centered content will garner more attention, boost buyer engagement, and drive conversions along the entire buyer journey.
  • Frees up time: This gives marketing leaders more time for strategy development.
  • Low consumer AI bias: An MIT study found that readers won’t care that content was produced by AI. But if they know it was produced by humans, they will perceive it more favorably.

8—Employ a human content expert to ensure quality 

Despite the hype, AI is not yet at a point where it can take over full responsibility for content marketing. Human oversight and guidance are critical. In a way, the new role for marketers is to become a content orchestrator.

Many content marketing professionals are quickly adapting to the new world of AI and are embracing the human-AI collaboration. A Content Marketing Institute study in late 2023 reported that 72% of content marketing professionals said they were already using generative AI tools. They’re figuring out how to work well with AI and blending its capabilities with their own skills — versus working against it. 

Every company needs marketing professionals who understand the benefits of AI, including: 

  • View AI as a content enablement tool rather than a raw content creator.
  • Ensure all content created in AI is authoritative and informative versus being generic. 
  • Infuse content with creativity and personalization versus bland content that feels like it came from a machine.
  • Understand the art and science of prompt writing to extract the best possible content.

Maximize your content strategy

Today’s marketers must learn how to work with AI, not against it. AI is reimagining possibilities and disrupting content marketing. It has created a new paradigm where human and AI expertise are not mutually exclusive. Instead, they can become partners. The bottom line is that the potential productivity gains are too great with generative AI. 

If you missed part one of our series on AI and data literacy, be sure to read it to gain foundational insights that complement the strategies discussed here.

For personalized guidance from Robert Gammon on optimizing AI-driven content creation, schedule a coffee chat with Cortado. Discuss your specific needs with Robert and learn how to produce compelling, effective content that supports your go-to-market strategy.

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