Chapter 7. AI Risks and Challenges
In Chapter 2, we discussed the limitations of generative AI. This chapter will go over the risks and challenges that derive from those limitations. It’s important to understand that limitations and risks are two separate but related concepts. Limitations explain what AI can’t do. For example, generative AI can only provide insights using previously published data; it doesn’t “know” anything without first ingesting the data that gives it the information it needs.
The limitations of AI are what lead to risks, and these can be devastating to your SEO, brand, and revenue. Various risks can result in revenue-impacting consequences, including litigation, loss of search engine rank, brand damage, and potential penalties. However, many of the risks of AI can be mitigated by careful human reviews. As much as AI reduces overhead and time to perform repeatable SEO tasks, it cannot function well without the critical thinking of human reviewers.
In this chapter, we’ll cover some of the common pitfalls you may encounter when using AI and how you can overcome them. If you recall the Gartner Hype Cycle from Chapter 2 (Figure 2-3), one of the phases is disillusionment. Many of AI’s pitfalls can contribute to disillusionment, but these challenges can be managed with the right strategies, which we will also discuss in this chapter.
The Ultimate Risk: Low-Quality Content
The core of an SEO practitioner’s job is to produce a site that adds value to the internet ...
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