The past two years have seen generative AI tools move from niche technology to widespread adoption, transforming how marketers, SEO professionals and businesses approach their work. These tools are now staples in many workflows, aiding with everything from content creation to customer and client interaction.
As generative AI becomes more embedded in daily operations, initial excitement is giving way to a more critical perspective across many industries. For marketers, this is an ideal moment to take stock of the benefits, limitations, and challenges of AI tools, ensuring that AI is used in a way that enhances rather than undermines strategies.
One key to understanding the strengths and limitations of generative AI is a rough understanding of the fundamental principle behind its startlingly ‘human’ seeming output. At the core of most generative AI tools is a large language model or LLM, a hugely complex statistical model which generates text by predicting the next word (or token) based on the context of what’s already been written. Trained on vast datasets, these models rely on probability rather than understanding, which makes them incredibly versatile but also prone to errors. For marketers, this means that while AI can assist in many ways, it must be utilised carefully and mindfully to avoid missteps and negative outcomes.
The good
Generative AI tools offer some clear benefits for marketing teams. Their ability to handle repetitive or time-intensive tasks can free up time to focus on strategy and execution. For example, initial basic research can often be conducted faster, with AI tools summarising vast amounts of information or providing quick answers to technical questions that can be followed up in more detail using traditional techniques when required.
AI also offers new ways to approach creative challenges. By using prompts to simulate brainstorming sessions or generate new perspectives, marketers can explore solutions that might not have been obvious. This makes AI especially valuable for smaller teams that may lack the resources for extended ideation processes.
For content creation, AI can efficiently draft pieces such as blog posts, product descriptions, or email campaigns. Although these outputs almost always require a skilled human writer to refine tone, check facts, and assess relevance, they provide a practical starting point that speeds up the production process. Beyond content writing, AI can streamline and improve workflows, whether that’s summarising meeting notes or designing educational resources for internal use.
The bad
Despite its strengths, generative AI comes with plenty of notable drawbacks. Over-reliance on these tools is one of the most pressing concerns. While AI can streamline certain tasks, it lacks the critical thinking and contextual understanding that human professionals bring. This is especially concerning when generative AI produces inaccurate answers or “hallucinates” information, a phenomenon where the AI confidently generates content that is factually incorrect or completely fabricated. These inaccuracies can lead to significant errors in decision-making, particularly in fields where precision is critical, such as healthcare, legal work, or finance.
Beyond hallucinations, LLMs can generate convincing outputs that may contain factual errors, outdated information, or subtle biases. For marketers, this can be problematic, as errors in campaign messaging or strategy documents can damage credibility and at worst erode client and customer trust. And while notetaking apps that depend on AI transcription are an enormous improvement over previous iterations of speech recognition technology, they are far from perfect. In particular, summaries from these applications must be checked carefully to avoid inaccuracies.
Another common issue with generative AI tools is their tendency to produce generic, formulaic writing. While this can be useful for quickly generating large volumes of text, it tends to come at the expense of originality and creativity. Content created by AI may lack the unique voice, tone, and personality that resonates with a brand’s target audiences. This generic output can dilute the distinctiveness that sets a brand apart from its competitors, or diminish trust, making content creation easier but making it more difficult for brands to establish a memorable identity or foster strong customer connections. In a crowded marketplace, heavy reliance on generic AI-generated content risks blending in rather than standing out, potentially weakening the brand’s overall impact and effectiveness.
The ugly
When used without oversight, generative AI has the potential to harm both internal operations and external perceptions of a brand. A newly-developing issue is the tone and style of unedited AI-generated communication. Certain turns of phrase (as well as a general impersonal feel and the risk of contextually inappropriate wording) can be glaringly obvious to recipients. While generative AI may have been a new and intimidating tool a year ago, many people are now highly familiar with its quirks and traits. Social norms and expectations are still evolving in this area, but it’s best to err on the side of caution. Whether it’s a cold outreach email, a LinkedIn ad, or a marketing message, generic or misaligned content sends a clear signal that effort and authenticity were not priorities. This problem extends to content strategies that rely heavily on AI-generated material that has not been carefully edited and proofread. Over time, this approach can erode trust, particularly if audiences begin to view a brand’s messaging as formulaic or disconnected.
A further risk lies in the perception of AI as a substitute for human expertise or direct research. This mentality can lead to short-term cost savings but at the expense of long-term growth and creativity. A strong team remains essential for interpreting AI-generated insights and aligning them with broader business goals.
What's next?
The limitations and risks of AI tools highlight the need for responsible implementation. As these tools become more sophisticated, it’s clear that marketers and businesses need clear boundaries and best practices for their use. AI is most effective when treated as an assistant that augments human capabilities, answers basic questions, and speeds up repetitive tasks while allowing professionals to focus on strategic decision-making and creativity.
With audiences increasingly aware of AI-generated content, brands have a unique opportunity to lead by demonstrating authenticity and accountability. At the same time, fostering a culture of media literacy will be crucial to navigate the challenges posed by misinformation and indistinguishable AI-generated material. The bottom line is that as in other industries, AI tools look set to become a key part of the mix, albeit in a much less dramatic way than some may have initially imagined.
Wondering how AI fits into your marketing strategy?
At SIXGUN, we’re committed to using AI tools thoughtfully and strategically. By combining the efficiency of these technologies with the expertise of our team, we deliver marketing campaigns that are effective, precise, and authentic.
If you’re ready to explore how we can enhance your marketing strategy’s efficiency without compromising quality, get in touch with us now to discuss solutions for your business and your audience.
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