If you are still using Artificial Intelligence primarily as a search engine or to write emails, it is probably time to rethink your strategy.
Sure, it can absolutely help you in those arenas. But AI is also capable of doing so much more. From creating YouTube videos you can monetize to using an IGLeads tool to help companies assemble a client list, the options are beginning to add up.
With this in mind, let’s now run through the most effective ways that you can currently use AI to boost your annual income.
Generating AI Written Content
Before you ask: No, this blog post was not written using AI. Opinion pieces never should be. But there are sites actively looking for writers who know how to implement AI-generated content.
Media companies are increasingly in the market for editors who can quickly prompt Large Language Models (LLMs) to churn out posts on basic news stories. On top of that, requests are on the rise for blog posts that are predominantly written by humans but incorporate AI-generated text.
To be sure, the vast majority of articles are still going to be primarily human-generated content. And that’s a good thing! For all AI can do, its content can often be too formulaic.
However, AI-generated text doesn’t only apply to long-form works. You can use it to hone copywriting tag lines, write social media posts, structure cookie-cutter pitches for sales companies and so much more.
All in all, writers and editors who know how to use AI to both create and enhance content are proving to be more valuable and in higher demand than those who do not.
Search Engine Optimization
Companies big and small are willing to pay semi-significant to actually big bucks for people who can increase their exposure in an oversaturated market place. With AI, this is something that can now be a lucrative side hustle.
Website traffic these days is largely at the behest of the almighty algorithms for search engines and social media platforms. On top of that, the method behind these algorithms is both opaque and ever-changing. It can be difficult to track.
Fortunately, LLMs are a wealth of information when it comes to monitoring the latest trends. You can use any one of them to build a tool that helps you assemble a checklist and database of criteria to maximize the exposure of an article headline, social media post, YouTube video, and so much more.
Let’s use the classic blog post as an example. Right now, Google Discover tends to reward headlines that make an emotional impact, include a curiosity gap, sound clear and conversational and are loaded with keywords and deliberate statements. In a matter of seconds, you can fire up a grading scale that allows you to plug in headlines and improve them according to that criteria. From there, you can track their performance, log it into your AI service and structure future headlines accordingly.
AI Data Scraping
This particular side hustle sounds a little intimidating on its face. In reality, it is actually very simple. As the folks over at Magical API explain:
“Essentially, it is applying artificial intelligence (AI) and machine learning (ML) to scrape data from websites. Think of it as a super smart robot that can surf the internet, know what a webpage is about, and extract the specific things you want it to extract without you doing anything. With regular web scrapers, if the website gets a facelift, the scrapers typically break, and you need to reprogram the scrapers. This is very time-consuming and inefficient.
“AI web scraping, on the contrary, works like a 4×4 vehicle that can change terrain. AI data scraping can change with the web changes. AI scrapers will use technologies like natural language processing (NLP) & computer vision, and interpret the web page just as a person does (context & structure of a webpage). AI scrapers can identify the data, extract what is wanted, and provide the data even if the website has changed. This ability to change makes the process of data extraction much more robust; it is also dramatically more accurate and efficient.”
This gig still suggests you need a background in coding, or even extensive knowledge of AI. You don’t. If you are doing it as a side hustle, you can simply pay for an IGLeads tool or another service that will do all the data-scraping for you. After that, you will have the ability to sort the information you extract based on pertinent details of the individuals. This includes valuable background intel such as their industry of employment, official job title, frequently visited websites, most searched for topics and more.
Once you have all this information, you can then sell each category of data to companies targeting a specific demographic.
AI-Generated Videos
The mass publication and monetization of AI-generated videos is becoming its own separate industry. Plenty of LLMs can create large swathes of dialogue off just a few prompts. Meanwhile, a bunch of different software products allow you to create AI-generated visuals in just a few minutes. And these videos can range anywhere from short form (60 seconds or less) to documentary-style length.
Financially capitalizing on these creations is more of a decentralized practice than the other highlighted areas. That’s not a bad thing. If you identify a niche or demographic and create videos specifically targeting them, it doesn’t take much to start monetizing.
Uploading these videos to YouTube is the most popular form of AI-generated video production. Their creator studio allows you to bookmark it as an AI product, and the number of users who consume YouTube like it’s cable television is on a meteoric rise. Use AI to help you write a killer headline and include the right hashtags, and it can take a matter of minutes to produce a video with viral potential that can rake in the advertising revenue dollars.
Identical logic can be applied to uploading videos on Facebook, Instagram, TikTok, etc. At the moment, though, YouTube has the broadest audience of the bunch–and more importantly, the most straightforward path to monetization, thanks to its ad-revenue model.