The Truth About AI: Benefits, Risks, and a Simple Breakdown

Although you hear about new uses for AI every day, when you think about artificial intelligence, you’re probably picturing evil machines intent on destroying humanity. Entities dreamed up by Hollywood like HAL 9000 from 2001: A Space Odyssey, Agent Smith in The Matrix, and Skynet from Terminator have taught humans to be wary of AI. But even with the greatest advancements in science, these Hollywood scenarios are unlikely to materialize.

The AI available today is intended to make life easier by running everything from smart home devices, automated investing systems, robot vacuum cleaners, search engines, and so much more! AI isn’t limited to personal use, though, it can be helpful in professional settings as well. The caveat is to know how and when to use AI in your business.

What is AI, really?

When you read about new AI tools or advancements, what’s actually being discussed may be confusing. The technology is constantly evolving and can be difficult to explain and understand because AI isn’t one thing. Artificial intelligence describes a broad field of study that looks at how to make machines more capable of replicating human behavior. On a basic level, the overall study of artificial intelligence breaks down into three specific areas of science and engineering.

Machine learning

The foundation of AI is machine learning, a subset of artificial intelligence that uses specially designed algorithms to learn from data provided to it. In the case of machine learning, the algorithm analyzes large datasets and makes predictions. You probably interact with machine learning algorithms, and perhaps even use them in your business, on a regular basis. These types of algorithms are used for simple automated tasks like spam filters, basic customer service chatbots, predictive maintenance in manufacturing, and product recommendations.

Deep learning

Designed to work the same way as neurons in the human brain, deep learning is the next step in AI. This kind of AI mimics complex-decision making as a means of processing higher-level data and making better predictions. You likely come into contact with deep learning libraries every day, as well. Conversational chatbots, Google Lens, voice assistants, and self-driving cars are all examples of deep learning AI.

Generative AI

Generative AI is the next iteration of deep learning. This is a top-level of AI that is undeniably a huge step forward for humans and, depending on the task, can be helpful in business settings. Generative AI uses the Large Language Models (LLM) that support many of the applications business use. There are many AI tools, many of which are integrated into established software. Some examples of LLMs are:

• ChatGPT – used to generate text like emails, blog posts, or answers to questions.
• Adobe Firefly – can create or edit images and design elements.
• Meta AI – helps write or reply to messages on social media platforms.
• Gemini by Google – works across all Google products where it can perform tasks like generating summaries of search engine results, predicting words and phrases you might use in Google Docs, and suggesting formulas in Google Sheets.

This type of AI is called generative because it, well, generates. You provide input in the form of a question, idea, or topic and it provides an answer, further inspiration, or relevant text. The more detailed the information you provide, the better your results will be. This means generative AI can be a great source of content, but there are a few problems with relying on it too heavily.

Where AI can go wrong

Using AI to help with business tasks can be a tempting solution when you’re low on resources and time. Some applications, like those mentioned above, can certainly be helpful for customer service, ensuring efficiencies in workflow, or content inspiration. These are all valid uses of AI, but what’s often missing from the equation is the human touch. 

AI vs. Humans

As much as it seems like it is, the AI available to the public is not generating original content. The algorithm has scoured hundreds of thousands of sources and is simply rearranging, rephrasing, and reworking content created by humans. For businesses looking for marketing help, this means generic results that don’t reflect your expertise, voice, or branding.

For example, the previous sentence that was written by a human might sound like this when generated by an AI tool: Businesses receive generic search results through this method which fail to demonstrate their professional expertise and brand identity. Sounds a little robotic and lifeless, right? 

Using AI to produce images can also be a problem. A human being taking or drawing a picture knows what the person or item looks like in real life. AI doesn’t have that ability.

Aside from the terrifying smiles pasted onto the faces of the children on the left, the image just looks fake. Anyone, including your customers, will be able to discern which photo is AI and which is real. Often, this sends a message to your customers that your business lacks professionalism and competence. So, generating ideas for your graphic artist about what you want for your brochures or product profiles is a great way to use AI. Creating and using actual AI images in them is not!

Another problem? AI has no common sense. It pulls from existing data sets but has no method of determining whether that data is sound. AI can’t evaluate a source and conclude that the facts or figures are outdated, incorrect, or nonsensical. The results can be a mishmash of incorrect information and illogical phrases.

AI can disrupt SEO

Aside from the very real potential for inaccuracies, some of what AI generates can be penalized by search engines for being duplicative or low-value. Duplicate content is a common problem for search engines as there can be confusion over which content to rank. While your page won’t be automatically downranked for duplicate content, there can be consequences. 

For example, if Google determines the motivation behind the duplicate content is deceptive, your page will not show up in search results. But Google can make mistakes, and AI-generated content that is too similar to its source material can trigger a penalty for attempting to manipulate search results. Google has been clear that original, helpful, and high-quality content will always be prioritized.

What AI Gets Right

For all businesses, regardless of sector, regularly developing new content is a necessary, but time-consuming process. Potential customers expect to find product descriptions, profiles of your company and leadership, insight into your services, and demonstrations of your expertise on your website and in your marketing materials. And, just like Google, they expect that content to be interesting, easy to understand, and enlightening. Obviously, the best way to produce this content is with the help of a marketing company like K-Kom. At the same time, when used correctly, AI can be a convenient tool for content.

AI can help you get started

For text, tools like ChatGPT or Gemini can help with blog post ideas, basic outlines, research, and rewording. The suggestions AI can provide for social media posts, content summaries, or email marketing sequences are typically useful for getting started when your inspiration has run dry. You can even get some basic drafts of ad copy, video scripts, article headlines, or email subject lines based on what has been successful for other brands. Starting from the results AI provides can cut down on the time from project start to completion.

AI is always available

While humans are still the best source for creative solutions and unique approaches, AI can be used as a substitute when absolutely necessary. A practical use for AI is that, even when you have a team to help out, they’re never going to be available 24/7. When you’re looking for research or brainstorming ideas after hours or on the weekend, AI is always available.

AI can help you analyze data

The whole purpose of digital marketing is to send it out into the world to publicize your business, educate potential customers, and demonstrate your expertise. Once you share that content, your next most important step is figuring out if what you put together is effective. When you don’t know whether or not your marketing is working, you have no idea what or how to change. You end up wasting time and resources you don’t have.

AI is particularly good at analyzing large data sets, including the results of advertising campaigns and content performance. You can also use tools like SEMRush AI or Google ads to search for keywords that appeal to your ideal audience. This can help you make data-backed decisions that will undoubtedly improve your lead generation efforts and save you money.

How to use AI in your business

If you need to come up with ideas to kick off a project, try out different variations of ad copy, or collect some research for a blog post, AI can be of assistance. But creating actual content that you publish without a hard edit isn’t recommended. You will always need to add your business branding, including voice, tone, and style, inject your expertise, fact-check the data, and inject a little humanity.

To learn more about how the real humans at K-Kom can help with your marketing, talk with one of our experts today!