How To Enhance Your AI-Generated Content
AI has solved one of the most significant business challenges — generating diverse types of content quickly for marketing and brand awareness. The recent research by Deloitte confirms that the demand for B2B marketing content increased by 1.5x in 2023, and to meet this ever-expanding demand, one out of 4 organizations have implemented generative AI for content creation & marketing. The AI content generation tools allow businesses to:
- Speed up content creation
- Overcome writer’s block
- Adjust content tone and writing style
- Improve operational efficiency
- Save time and resources
These benefits solidify AI’s role in content generation. But, is the content created by generative AI meeting the quality standards and modern SEO requirements? While AI excels in speed, human expertise remains paramount for quality and impact. Google’s E-E-A-T guidelines prioritize human-like accuracy, creativity, and deep understanding — areas where AI currently falls short. To unlock the full potential of AI-generated content, it is crucial to enhance its quality and overcome its shortcomings. How? By following the best practices for AI content editing mentioned in this guide.
Why you cannot solely rely on AI-generated content?
While advanced AI and LLM models like GPT-4, Gemini, and Claude 2 have revolutionized content creation with their ability to generate accurate and creative copies, their potential comes nestled alongside certain limitations, such as:
- Inconsistent tone
The biggest shortcoming of AI content generation tools is that they struggle with maintaining a consistent tone or style. When using multiple prompts to generate a single content piece, the voice or content style can change significantly (from casual to professional), leading to an unpleasant reading experience. Such content requires careful audit and enhancement to ensure it aligns with the brand tone and resonates with your target audience.
- Factual inaccuracies and biases
Have you heard about AI hallucinations? This term is used to represent a condition where generative AI tools provide factually inaccurate or nonsensical information. Usually, when you ask LLM or AI models about the concepts they are unaware of (or not trained upon), they provide you with incorrect information by presenting invalid facts as true, references, and stats.
AI hallucinations are common to witness in content generated by LLM models. Incorporating such unreliable information into your website content, articles, or marketing materials can significantly undermine your credibility and reputation as a subject matter expert.
Example of AI hallucinations:
- Grammatical errors
Grammatical mistakes and poor readability issues are common to witness in AI-written content. While the generative AI models are evolving, they are not flawless and thus the content generated by them requires meticulous editing and refinement.
- Lack of creativity and originality
AI algorithms usually lack original ideas and perspectives to make your content unique and appealing, unlike human writers. They thrive on existing web data to curate content based on your prompts. While efficient, this reliance on readily available information can make the outputs predictable, even robotic and monotonous.
Imagine feeding an AI tool the prompt “Write a captivating product description for my new line of handcrafted soaps.” The output might be factually accurate and informative, but it’s likely to sound eerily similar to dozens of other soap descriptions you have encountered online. On the other side, human writers can utilize their creative ideas and fresh perspectives to bring uniqueness to product descriptions. This is one of the reasons why human-written product copies are preferred over AI-written text.
- Limited contextual understanding
Despite getting trained on large and diverse datasets, AI algorithms often struggle with understanding actual context. As a result, they make faulty assumptions and generate content having irrelevant information that doesn’t align with your intended goal. Enhancement of such content is required by human editors to ensure it aligns perfectly with your desired message and objective.
Effective ways to enhance the quality of AI-generated content for better rankings and outcomes
To counter the limitations mentioned above, editing AI-generated content is essential. Here are some practical and effective ways to do it:
- Review and revision of AI-generated content by human experts
A thorough content audit by human editors is crucial to identify and fix errors, inconsistencies, and irrelevance in the AI-generated text for improved accuracy and quality. Human feedback can also help train AI models to better understand user preferences and generate content that resonates.
Imagine a publication house using AI to generate blogs and articles. Without human editors, these pieces might lose reader interest. However, with editor feedback, AI models can understand what type of content targeted users like or interact with the most and improve their future content generation.
Businesses can leverage this synergy to achieve optimal results. They can automate content creation with AI and then refine it through human expertise. This keeps costs down while ensuring high-quality content. Those who lack the required expertise or resources in-house can consider outsourcing AI content editing services to a reliable third-party provider that utilizes advanced tools and a human-in-the-loop approach for content enhancement.
- Refine tone and structure
It is also crucial to ensure that the content follows a consistent tone and structure, which is a common issue to fix with AI-generated text. Arrange and refine the content in a way that follows a natural and logical flow without a shift in tone or abrupt sentence breaks. Utilize headings and sub-headings appropriately, and consider bullet points or numbered lists where possible to improve the overall content structure and readability.
- Fact-check and verify
To keep your content reliable and free from factual errors, always verify the information provided by AI-based content generation tools. Pay close attention to details, dates, statistics, and any claims that seem unusual or potentially inaccurate. Verify information using reputable websites, academic publications, or expert opinions. Check facts against multiple sources to ensure consistency and accuracy. For complex topics, consider involving subject matter experts to review and refine the content. Their insight can add invaluable nuance and accuracy.
- Incorporate a unique perspective
Add human creativity and fresh perspectives to the AI-generated content to break the monotony and repetitiveness. Instead of simply iterating information, add your unique insights, interpretations, quotes, and even humor. Use storytelling techniques and engaging narratives to make the content attention-grabbing and interesting for users.
- Optimize for search engines
To make AI-generated content more effective on search engines and improve its chances of ranking on relevant queries, it is crucial to optimize it with appropriate keywords. You can use AI tools to generate engaging meta titles and descriptions, but to optimize these tags, human oversight is required.
Search for topic-related relevant keywords and strategically incorporate them in the title, headings, sub-headings, and content body for improved search visibility and reach. Remember, quality over quantity; avoid keyword stuffing, which can penalize your rankings. Keep your content informative, helpful, and engaging, to rank better in search results.
- Add compelling visuals and multimedia
Make your content more appealing and engaging for readers by adding relevant images, videos, infographics, charts, etc. These elements not only help to break up the dense paragraphs and boost engagement but also provide better clarity about a topic or specific section to readers.
- Train AI models with high-quality training data
Enhancing AI-generated content through experienced human editors is one way to improve its quality and accuracy. But, if you wish to get better outcomes from AI-based content generation tools, you need to self-train LLM models on a vast amount of high-quality training data.
Provide high-quality content samples to AI models to train them better on your requirements for complex or niche topics. The more information you feed the model, the better it understands your needs and generates outputs that are both accurate and impactful.
- Refine AI prompts for improved accuracy
Another effective way to improve the accuracy of the outcomes generated by automated content creation tools is “prompt engineering”. In simple terms, it refers to improving the structure of your prompts to get more accurate and relevant outcomes. Imagine prompts like blueprints for AI content generation tools.
The more refined and concise your prompt is, the more relevant and accurate information generative AI will produce. Provide clear instructions to language models and keep experimenting with prompt styles to figure out which one is working in your favor on a particular content generation tool.
Follow these five basic principles of prompt engineering:
Key Takeaway
The speed and efficiency of AI models in generating content are undeniable. However, it excels as a partner, not a replacement, for human creativity and expertise. To unlock the full potential of AI-written content, adopting a balanced approach is required.
By employing strategies like human review and refinement, careful prompt engineering, and model training on high-quality data (as explained in this blog), we can empower Generative AI to produce content that is not just fast, but accurate, effective, and truly impactful. This synergy between human and artificial intelligence paves the way for a future where content creation is not just quicker, but fundamentally better.
