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AI Generated Content | Is it truly worth the risk?

AI generated content | Is it really worth the risk? Learn the pros, cons, and risks of using AI generated content for your business.

The rise of AI content generation tools promises faster, scalable content – but also comes with risks that many brands overlook. Buzzwords like GPT-4, 4.5 and AI writers promise to automate content creation and save humans hours of tedious writing. Sounds amazing, right?

Here’s our take on whether AI generated content is really worth it!!

AI Generated Content | Is It Really Worth the Risk?

Time to Automate | The Potential Benefits of AI Generated Content

  • Time savings: AI content tools can produce rough drafts, headlines, and social posts much faster than humans – sometimes in seconds. On the plus side, AI content can save a ton of time, especially for repetitive or “good enough” content.

    Our agency recently experimented with AI content writing models to generate rough drafts of 200-word social media posts and long form SEO content. It took an AI tool less than 5 seconds to produce a readable result, saving us up to 10 minutes per post.

  • Scale: With enough data and training, AI systems can theoretically generate an unlimited amount of content across topics – allowing for massive scale that’s difficult for human teams. 

    Brands with large content requirements like Buzzfeed and Forbes are experimenting with AI to generate thousands of new articles per month. While still requiring human editing, this model offers a potential workflow for hyperproductive content marketing.

  • Improving quality: The latest AI generation models, like GPT-4 and GPT-4.5, are getting better at producing fluent, grammatically correct text in many styles. In niche areas, AI content is becoming less distinguishable from human-authored pieces.

Blurred Lines | The Risks and Drawbacks of AI Generated Content

  • Lower quality overall: Despite improvements, AI generated content still averages 10-30%  error rates in our experience, which was a lot higher in previous AI LLM models. Issues include factual errors, generic writing, and lack of specificity.
  • Tone and bias issues: AI systems often reflect the biases in their training data, leading to insensitive, inappropriate or inaccurate content. Researchers have documented examples of toxicity, racism, and sexism.
  • Lack of trust: Legal, compliance, and internal stakeholders often hesitate to publish AI generated content without thorough human review and customization. And consumers are increasingly skeptical of “AI-generated” labels, demanding full transparency around the role technology played in content creation.
  • Less human value: Over Reliance on AI risks losing the creativity, authenticity, and insights that human writers provide. AI can supplement but not replace strategic thinking and narrative development.

Want to know how top companies use local service ads to generate leads in a cheaper way?

Balanced Approach | Integrating AI Assistants the Right Way

  • Start small: Pilot AI tools for lower-stakes content to test quality, bias, and tone before broader use.
  • Build custom models: Train AI systems specifically on your brand’s style, tone, and content needs to improve relevancy and minimize errors.
  • Audit and revise output: Implement human-in-the-loop processes to detect and correct issues in AI generated content before publishing.
  • Use AI as an assistant: Harness AI to generate initial drafts, variants, and edits but maintain humans as the final approvers and customizers of all published content.
  • Keep expectations calibrated: View AI as an amplifier of – not replacement for – human talent, insight, and creativity.

Want to know How AI is reshaping the future of advertising?

Our Closing Thoughts

For most brands, a thoughtful integration of AI assistants within a broader human-AI collaboration holds the most promise. Used wisely, AI generated content can:

  • Accelerate content production while maintaining (or even improving) quality through human oversight and customization.
  • Augment – not replace – human writers by generating drafts, variants, and ideas to spark creativity and speed workflows.
  • Amplify the impact of limited marketing resources through faster scaling and repetition of “good enough” content.
  • However, for truly strategic impactful content that builds your brand, human writers offering insight, judgment and originality will remain essential. The key is finding the right balance between automation and expertise, speed and substance. 

Get that blend right and AI could meaningfully accelerate – but never fully automate – your content marketing.

Buzzfeed – Uses AI tools to generate headlines, snippets and article drafts that are then edited and published by human writers. This has helped Buzzfeed scale their volume of articles while maintaining quality.

Forbes – Uses AI writing assistants to generate first drafts of articles for specific niches. Human writers then edit, revise and customize the content before publication. This has increased their writers’ productivity.

The New York Times – Uses AI tools to generate article suggestions and story ideas that are reviewed by editors and writers. The AI helps spark new ideas that may not have otherwise surfaced.

Adobe – Trained AI models specifically for their brand’s style, terminology and needs. They then use the AI to suggest variations, alternatives and edits for human reviewers to consider and integrate into marketing content as relevant.

Procter & Gamble – Deploys AI assistants to generate initial drafts of simple, lower stakes content like social media posts. But all AI output is reviewed, corrected if needed, and approved by human marketers before publication.

  • Train custom AI models: Rather than using general-purpose AI generators, you can train AI models specifically on your existing marketing materials, website copy, social posts, etc. This helps the AI “understand” the unique terminology, tone, and style of the brand.
  • Provide style guides and brand guidelines: You can develop detailed style guides that outline the specific vocabulary, tone of voice, and writing conventions you want the AI to emulate. These guides can then be used to train and evaluate the AI models.
  • Audit and revise AI output: You should implement human-in-the-loop review processes to catch any instances where the AI generated content does not properly align with your brand voice and style. The AI output can then be rewritten or retrained accordingly.
  • Do test run with lower stakes content: You should start by experimenting with simpler content types like social media posts or product descriptions to identify any gaps in brand voice alignment. This helps refine the AI models before deploying them for more critical marketing materials.
  • Retrain models over time: Your brand voices might evolve, in such cases you need to continuously update style guides, re-feed content to the AI models, and retrain them to ensure alignment with the most current brand standards.

The most important factors that determine how content performs in search are elements like usefulness, helpfulness, originality, expertise, experience and trustworthiness – collectively referred to as E-E-A-T (experience, expertise, authority, trustworthiness).

Whether content is generated by AI systems or human writers, if it satisfies these crucial aspects of E-E-A-T, it has a good chance of ranking well. But if the content lacks in these dimensions, it will likely struggle regardless of how it was created.

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