Although some may feel that AI only came about in the last year, its predecessor, machine learning, has been with us for years. Machine learning and AI have already upended companies and job markets, and they are guaranteed to continue doing so for some time yet. The key is not to think of AI as something from a sci-fi movie, but as a tool much like the computer once was. And like the computer, it’s time to adapt or die.
The computer did away with entire industries and jobs. Calculators used to be people who did calculations for a living. Thousands of typists and typewriter repairmen were laid off with the advent of word processing on computers. So, too, will it be with AI. Any job that can be automated will be automated, and the trend cannot be stopped.
But for every job lost, two more will take its place. We no longer have paid calculators, but we have a plethora of computer programmers instead. It will be the same with AI. Those who can use the tools to their fullest will reap the greatest rewards in the changing job market. Companies will have to position themselves for the coming revolution also — there’s no money in typewriter repair anymore.
But for those who can adapt, the rewards will be immense indeed. The salaries of Silicon Valley could have only been dreamed of by calculators and typists. So, for those with an eye for the future, here are three ways automation will change the job market.
Easier Communication
Once upon a time, if you wanted to share ideas with someone you had to see them face to face. Phones can send words and paper messages can send pictures, but the two together usually require a face-to-face interaction. With the advent of technologies such as Microsoft (NASDAQ:MSFT) PowerPoint, that is less necessary — but even here there is room for improvement.
Alphabet (NASDAQ:GOOG; NASDAQ:GOOGL), for instance, has unveiled an AI that can search through documents and emails to create a presentation all by itself. That frees workers to concentrate more on the ideas presented rather than the process of creating itself. And it is well known that many people are terrible communicators. But many large language models (LLMs), OpenAI’s ChatGPT is just one, can improve communications by just going over the rough draft. By ironing out mistakes and clearing up gibberish and blather, LLMs promise to increase clarity and conciseness when used correctly.
Because not everyone is good at getting to the point, AIs can be trained to do that for us. Then, workers can focus on making sure the point is actually coherent and let the AI focus on the words and pictures that help get it across to readers. The worker is happier because they can focus on what matters. The audience is happier because the point is now well-presented. And everyone can focus on the actual idea or information instead of how to communicate the information.
More Demand for Data
Big Data is already a powerful tool for those who have it. But in the future, everyone will need it. AIs like ChatGPT are good for many tasks. But can they capture the precise syntax needed for your drug to get approved? Can they capture the youthful syntax of the advertising campaign you want to launch?
Fine-tuning is a process of making an AI model mold itself better to the specific task you demand. It’s just like hiring a new computer programmer and teaching them how your company’s legacy code works. Without that teaching phase, programmers might not know that minor changes can break something important. And AIs might not know you’re looking for a specific syntax in your words or images. OpenAI already offers fine-tuning as a service. But that requires a lot of data to teach the AI what you want it to know.
And it isn’t just language models that require fine-tuning. AI art will also look out of place if it doesn’t fit with a company’s pre-existing style and dynamics. Gaming companies are already jumping on the AI art bandwagon. And Adobe (NASDAQ:ADBE) is the premier AI art company offering fine-tuning of its flagship Firefly AI to suit companies’ needs.
But fine-tuning requires data — and lots of it. You need to give the AI many examples of exactly what you want until you teach it to produce what you need. Curated language datasets with just the right syntax or image datasets built off a company’s pre-existing art style are the currency of fine-tuning. These datasets need workers to curate and feed them to the AI, testing many models until the AI learns what it needs to know. And those workers will be some of the biggest winners of the AI revolution.
More Demand for Cloud
The biggest winners of the past decade have been cloud companies and programmers who work with cloud computing. They will likely win in the next decade as well. AI requires an incredible amount of data and processing power. Those will come from large amounts of cloud storage and cloud processing. Maintaining the cloud, accessing it, securing it and deploying it will be highly in-demand jobs as more and more companies move to AI.
We’ve already seen this in the stock market. Big cloud companies like Amazon (NASDAQ:AMZN), Microsoft and Google have bucked the general market trend. They continue to grow strongly while the broader S&P 500 is flat or down. But this demand will also translate to the job market, as far more openings are coming for work in cloud computing.
That’s because the sheer volume of data and processing power needed to make a good AI is immense. And with hundreds of companies now rushing to develop or fine-tune their own AIs, they’ll need more cloud space to store data and run their models. That means more people need to run the cloud, build out the cloud and service the cloud when things inevitably go wrong.
That also means more work is needed on cloud security. Think about it: Getting data is expensive, but stealing it is cheap. The fact is, it’s very difficult to prove that any specific piece of data was used in the construction of an AI model. So, protection is far better than prosecution. Overall, the future looks very bright for the cloud and anyone who wants to work in cloud computing.
On the date of publication, John Blankenhorn held long positions in GOOGL, MSFT, ADBE and AMZN. The opinions expressed in this article are those of the writer, subject to the InvestorPlace.com Publishing Guidelines.
