In the ever-evolving landscape of technology, generative AI (GAI) stands out as a real groundbreaker. It will reshape the way we approach creativity, problem-solving, and information processing. As a powerful subset of artificial intelligence, generative AI has the unique ability to produce new and original content. That could be text and images or music and code.
This transformative technology is not just an auxiliary tool; it’s a catalyst for innovation. In this article, we’ll explore the top 10 generative AI applications and use cases. From revolutionizing content creation to transforming businesses, these examples highlight the benefits of generative AI in our daily lives and the future ahead.
AI Search Assistant
In the modern knowledge economy, the biggest challenge is not lack of information. It’s too much information. The amount of information on the Internet is growing at an exponential rate, doubling approximately every two years.
This explosion of data has created a paradox. While we have access to more knowledge than ever before, it is becoming increasingly difficult to find, filter, and make sense of it all.
Undoubtedly generative AI will be a part of the problem. It’s all too easy to enter a simple prompt into a tool like ChatGPT and get streams of text generation. It will only keep getting harder to pick out the truly useful information.
Even so, generative AI can also be a part of the solution. For example, one thing it’s great at is summarizing the key points from large amounts of information. It could become the ultimate search assistant—an AI secretary who makes sure only the important stuff reaches your desk.
AI Copy-Paster Software Developer
In software development, there’s a joke that programmers are basically professional copy-pasters. StackOverflow, a site that crowdsources answers to engineering questions, already has most of the code you’ll need.
In reality, that’s true more often than you might expect. Sure, many developers do work on innovative things. But there are often large parts of the app or software that don’t require a reinvented wheel. E.g. login, authentication, account management, billing, basic analytics—just to name a few.
Currently, developers use frameworks, boilerplate, and yes—StackOverflow—to speed up development of those commonplace features. Generative AI will be able to handle those types of features even faster, more comprehensively, and with fewer mistakes.
This generative ai application would free developers up to focus on the other stuff that distinguishes the software. Things like brand new code, domain-specific business logic, proprietary data, etc.
Personal Professor
The world is getting more and more complex. The average employee in the 1960’s might stay at one or two companies until retirement. But the average Millennial changes jobs every three years.
Part of this shift is certainly from cultural differences between generations. But a large part is also from sheer necessity. Technology has dramatically accelerated how fast companies (and even entire sectors) rise and fall.
All in all, today, more learning is necessary to stay competitive. The old model of learning from teachers in school is simply not enough. Instead, younger generations will increasingly need to seek more knowledge on their own, on an ongoing basis.
This is where generative AI can play a huge role. It could be the ultimate personal professor, providing 24/7 access to curated personalized instruction. It can bridge the gap between static educational content and the ever-changing demands of the modern workforce.
Corporate Librarian
Estimates say that the average knowledge worker spends 20% of their time just looking for internal information. Not doing work, not team bonding, not having meetings—just looking for information.
That could be digging through emails, trying to find that half-finished report from a former coworker before he dipped. Or it could be searching through intranet wikis, trying to locate vendor passwords. Regardless, 20% of the time for the average knowledge worker is spent like this.
This generative AI application could virtually eliminate this type of wasted time. This would immediately boost productivity by 25%. (Or even better, it could be used to make the argument for a 4-day work week!)
AI Game Master
Procedural generation has been a shiny object in gaming for a while. The idea behind procedural generation is that developers can create a bank of modular content. Then, an algorithm mixes and matches those modules to create “endless” content for the player.
This sounds good in theory, but it’s hard to pull off in practice. Games like No Man’s Sky or Starfield were famous for heavily using this technique. But those games also drew a lot of criticism. The big problem is that procedurally generated content tends to be lower quality, boring, and “samey” after a while.
With procedural generation, the algorithm simply mixes and matches content bites. This means that the content is often predictable and repetitive. It doesn’t truly generate “new” content.
However, generative AI could be the solution game studios are finally looking for. It could create entirely new assets—landscapes, textures, characters, and storylines. This could lead to a new era of games that are far more immersive, engaging, and replayable than anything we’ve seen before.
Customer Service “Agent”
If you’ve called your internet provider recently asking why your bill went up, you’ve probably run into the dreaded “automated agent.” Right now about half of all customer contacts in utilities and banking are handled by machines.
If you want to talk to a human, too bad. You’re stuck with a lifeless bot until you press a long sequence of numbers answering tedious questions.
“For English, press one. Para español, presione dos.”
Like it or not, this trend will probably continue. The cost savings are too attractive for companies to go back to staffing full human service. So why not make the bots at least a little bit more friendly, personalized, and helpful?
That’s the role of this generative AI application. Generative AI can be used to create chatbots that are more natural and engaging to interact with. These chatbots can understand the context of a conversation and answer you in a more “human-like” way.
Metaverse Construction Co.
To many, the idea of a metaverse has died before it could even take its first breath. Its biggest proponent, Meta (formerly Facebook), went through a huge attention grabbing rebrand in 2021. But since then, it has appeared to pivot away from the idea, slashing its investments in the space dramatically.
However, generative AI could breathe new life into the possibility of a metaverse. One of the biggest challenges was that it’s really hard to make fully fleshed out 3D worlds. Everything was low-res, simplistic, boring, and not very interactive.
This generative AI application could be the answer. GAI could help “populate” 3D metaverse worlds, making them more dynamic and immersive. For example, it could generate realistic textures, landscapes, and buildings.
Generative could also fill the world with lifelike NPCs (non-playable characters). Those characters would have their own routines, dialogue lines, motivations, and more. This would overcome the limitations of manual design and rendering.
AI Marketing Genie
The holy grail of marketing is personalization at scale. Take the example of email greetings. It’s quite overplayed at this point, but it works so pretty much every company still does it.
“Hey, <first name>!”
Advertising has followed the same trend of personalization. Can you run ads targeting a given zip code, women ages 35 to 45, married, no kids, and like shopping in Nordstrom? If so, then personalize the message to that “customer avatar” and your ad is going to do much better. It’s kind of creepy, but it really works.
Now what if companies could almost completely personalize each ad, video, or email? Rather than just a greeting, the entire email was written just for you.
It would obviously be good for advertisers. But if done ethically, while respecting user privacy preferences, it could also be great for users. It would lead to less spam and more relevant offers and products. That would be the goal of generative AI in marketing.
AI Financial Analyst
Finance and investing is another huge driver of innovation. Generative AI is poised to take many existing methods in finance to the next level.
For example, social media sentiment has been used as a signal in trading for many years already. Bots will crawl social media sites, scanning for mentions of a company. Then an algorithm calculates a single sentiment score for it.
Generative AI takes that entire process to the next level. Instead of boiling everything down to a single sentiment score, it could generate entire reports. It could summarize pros, cons, and common questions. It would be like having an analyst who works around the clock, at 1000 times the speed.
Another example would be market research and survey data. Surveys are currently used to get more nuanced feedback about a particular product.
But how can we expand that scope even further? What if we could expand it to earnings reports? SCC filings with hundreds of pages? Generative AI would be able to churn through all that information and condense it.
AI Content Creator
The most prolific creator of our time will not be a Mozart or a Stephen King. It will be a generative AI model, possibly even ChatGPT or Bard. This is perhaps the most intriguing and disruptive generative AI application, as it will affect the entire domain of creativity.
Right now, AI is already capable of all kinds of content generation. It can create academic writing. It can create scripts for movies, poems, songs, and more. And while the quality of the outputs are still hit or miss, these AI models are only getting better.
This shift in creative production has profound implications for the future of art and literature. On the one hand, it raises concerns about the potential for AI to replace human creators and diminish the value of human creativity. Some worry that AI-generated content will lack the emotional depth of human-created art.
Yet others view AI as a powerful tool that can augment and enhance human creativity. By automating many of the repetitive tasks involved in content creation, AI can free up human creators to focus on the more conceptual and creative aspects of their work. Additionally, AI can be used to generate new ideas and perspectives that humans might not have considered on our own.
Ultimately, the impact of generative AI on creativity will depend on how humans choose to use this technology. If we approach AI with fear and suspicion, it may indeed lead to a decline in human creativity. But if we embrace AI as a tool and collaborator, it has the potential to usher in a new era of creative expression.
