Corporations, startups, institutions, and everyday people – artificial intelligence began to change all of their lives this past year. Companies started heavily using generative AI tools and intelligent voicebots. There’s probably nobody left who hasn’t tried chatting with ChatGPT. The year that AI evolved at a shocking rate is already behind us. It’s time to look at how far it’s come in only a few months, what trends we are following in AI development, and how we can get the most out of it for our own businesses.
At first glance, it may appear that AI is only connected with progressively minded startups. However, the reality is that even large corporations use it to a great extent. Chatbots have primarily taken root with them, like at JPMorgan Chase, where chatbots assist financial advisors in communicating effectively. Consultants at Morgan Stanley then use them for educational purposes. In many companies today, they fill the roles of former work positions – at Brex, where they develop software for monitoring costs, they introduced a financially literate AI assistant specifically designed for financial directors and accountants.
The rapid pace of innovation
Last year, however, startups and product-oriented companies took it a step further, not limiting themselves to chatbots only. A good example is the company Salesforce, which is changing the world of CRM with the help of an intelligent system for planning meetings and personalising follow-ups. Also, last year, Adobe pushed the boundaries of creativity by filling and modifying images in Photoshop, while Notion completely changed how we work with a corporate knowledge base by summarising and generating texts. If you work in Notion, then you’ve surely noticed these functions. One such feature (a rather controversial one, if you ask me) is the “make longer” option, which artificially extends texts. On the one hand, we’re using AI in droves to summarise long texts so we don’t have to read them and simplify working with them, and on the other, tools are being made to artificially inflate them even more. In the future, I hope we choose to steer away from developing such products. Otherwise, we’ll go down the road of creating a world where one AI writes a text just so another AI can read it.
Investors are also expecting big things from generative AI. Its progress last year acted as an impulse for VISA, which launched a new capital fund. This fund amounted to 100 million dollars for startups that use generative AI. VISA will most likely use this money to strengthen autonomous agents as much as possible, connect systems, and help companies develop more valuable products. Although everything mainly revolves around “new” generative AI, it’s important to observe that investments in the sector are also pushing forward the classic AI methods, like predictions, data analysis, scheduling, and machine learning as a whole.
Greater independence and millions in annual savings
The predictions made by these giants are quite positive. One such perspective is offered by the consultation company McKinsey, for example. It estimates that AI could increase productivity next year in the financial sector by nearly 5%. That would equate to annual combined savings of hundreds of billions of dollars. I myself believe that generative AI’s full potential has yet to be achieved. If I were to liken this path to a hike up a mountain, then we’ve only taken a few steps from the base camp – today, we’re looking at ChatGPT the same way people looked at the first personal computers in 1991 when only a few people were actively using them. A long evolution awaits these tools, and we still have so much to discover.
This year, I expect AI to become something even more competent. It will solve its tasks more precisely, effectively, and, most importantly, independently. It’s quite likely that autonomous AI agents will turn our way of working on its head. I assume that at Applifting it will identify places in our budget where we can save money, overhaul our capacity, and even plan the annual Christmas party. While the tool takes over our hours-long daily routines, we can instead focus on the work we enjoy and directly generate income from. Plus, the best systems will create their own agents to fill partial roles. The tool Auto-GPT is a good example of this, given it has made incredible progress just this past year.
The constant cheapening of the APIs that help us use these AI tools is fundamental to this growth. We can also expect a rapid commoditisation of the market – it’s safe to say that soon it won’t matter if a task is performed by a product of OpenAI, Google, or another company. The price will decide.
The first hardware swallows
When it comes to generative AI, last year was in the spirit of applications. We’re still waiting for a similar boom in the area of hardware. Moreover, the mobile phone market is a massive yet undivided piece of the pie that is up for grabs for any company. And who knows? Maybe they’ll create a completely new one in the near future.
The first swallow flying in this direction was surely AI Pin, created in the workshop of the company hu.ma.ne. At first glance, it appeared quite promising – a small box you can pin to your jacket and receive answers to any questions you have. It sounded like a dream, which, unfortunately, couldn’t become a reality. The responses from AI Pin were too simple, some were even completely off-topic. The main problem, however, was that nobody, including the founders, managed to effectively explain what AI Pin is actually good at. And I won’t even speak to the absurd 700-dollar price tag.
After hu.ma.ne’s failure, other interested projects started to appear. For instance, the company Rabbit introduced the R1 device, which saw great market success from its very first week. It made a remarkable 10 million dollars just in pre-sales. Having paid attention, these founders prepared a powerful AI model as well as an overview of potential use cases. That’s why customers can use R1 for simultaneous translations and ordering food and taxis. There are also another 15 functions that Rabbit’s planning to add. Unlike AI Pin, R1 is more akin to the first push-button iPod, making it easier for users to use. And the more reasonable 200-dollar price is another bonus.
Maybe you’re thinking to yourself, “Where’s Apple?”. Despite having missed the boat a bit with its voice assistant Siri, it certainly isn’t behind in AI hardware development. In fact, we can expect big things from Apple (like usual) that would be outside other brands’ budgets – for example, I can picture Siri being able to control other applications on her own. We can further our assumptions by looking at Apple’s acquisitions in past years. While it’s purchased twenty startups focusing on AI development since 2017, Microsoft only has twelve at this point, Meta owns eleven, and Alphabet (Google) only eight. Whether we’re talking about software or hardware, I think it’ll be Apple with its finger on the pulse.
Innovation brings success
Is it even possible to secure a seat in such a fast-filling arena? I certainly believe so. You need to be able to see around the corner, however. Innovation doesn’t mean copying what others are doing. You need to develop whatever exceeds current possibilities and do it fast because, before you know it, your competitor will have the same idea.
But if you’re looking for tips on how to simplify your work today using AI, then learn to work with chatbots. There are so many to choose from, and thanks to OpenAI and the GPT Store, the list is ever-growing. Remember, there’s no time to waste. And if you already use generative AI in your company, continue to do so. But don’t rest on your laurels – keep up with the news, and don’t be afraid to experiment. Feel free to write to us if you’re unsure where to start with these tools. At Applifting, we work with AI daily, and we’d happily share our experience with you.
This article was originally written in Czech for "IT Systems" magazine.
