In the last year, generative AI has taken the world by storm. Some people compare it to when Steve Jobs introduced us to the iPhone in 2007, a revolutionary technology that left people in awe and ultimately changed how we function in our day-to-day lives.

But is GenAI genuinely going to change the way the world works? Or is this a fad we will forget about in a couple of years, like Segways, cryptocurrency, the Metaverse, or Google+?  

Let’s walk through what we have learned in the last year about GenAI with our Chief Business Officer, Ivan Ostojić, and see if GenAI has truly reached its peak or is just getting started.  

The initial hype around generative AI was enormous. It was the main topic of conversation for everyone, from students raving about ChatGPT’s ability to generate essays, to major corporations rushing to release their generative AI technology – some succeeding and some flopping.  

At the same time, people were creating major buzz about the scary side of AI. Losing jobs to AI, deep fakes, and fraud attacks began to stir up fear. We questioned how powerful generative AI could be and if we were on the road to a full-on Matrix-style dystopia (if we aren’t already unknowingly living in one).  

But artificial intelligence is exactly that – artificial. It can’t think independently or grow consciousness that allows it to become as powerful as the hype made it sound.  

So, why the hype? 

With anything that’s hyped up by the public, there is an unwritten expectation for it to succeed. With the release of ChatGPT in November of 2022, everyone and their grandmother were jumping on the bandwagon of including generative AI into their business solution or creating their own solution.  

This set up a massive expectation for AI to magically fix customer pain points or use cases without really understanding what it could do and when it should be implemented. And with every brand racing to release their AI first, this led to a huge number of failures – from big tech brands to courier services.  

The million-dollar question – What is AI? It seems many brands have a different view of the answer. It starts to get messy when generative AI is confused with large language models, machine learning, neural networks, deep learning etc. All these topics are intertwined but are not the same thing. 

For example, if you train a chatbot on large language models, it doesn’t necessarily mean you have an AI-powered chatbot. Without a clear understanding of what exactly AI is and how it is used, it has quickly become a “buzzword” for brands to use to hype up their offerings.  

This all leads to AI washing. AI washing is when brands exaggerate their usage of AI. The idea is to make your products or services appear more appealing or impressive to your customers. And with a hazy definition and low public understanding of what AI is, this isn’t hard to do.  

But it’s not something brands should be doing. As we understand more about AI, and how it can be used, it is becoming clearer what constitutes an AI solution and what is being exaggerated. The U.S. Securities and Exchange Commission has started fining brands for AI washing to halt other brands from false advertising.  

Using basic automation or rule-based systems to power your solutions does not make them AI, neither does using AI to develop your solutions. These are the grey areas some brands have used to AI wash their products and solutions.

So, there is no doubt that the capabilities of GenAI were hyped up, but now that our excitement has started to fizzle, reality has kicked in, regulations have been put into place on how and when to use it. Is this something that will stick? Or are we ready to move on to the next best thing?

Despite all the bumps in the road, the GenAI boom led to some successful feats:  

Let’s take customer service chatbots as an example. If you are looking to book an appointment with your dentist over WhatsApp, would it be easier for you to click two buttons to choose a date and time from a simple chatbot or to have a back-and-forth texting conversation with a GenAI chatbot? Probably the former.

GenAI is not the immediate answer to every problem and every use case. But we are getting better at understanding when and how to use it to get the best results and experiences with solutions across the board.  

So, we’ve established that GenAI is here to stay, and with continuous development, we can start to predict how it will impact the future. Here are three categories in which we can see GenAI playing a significant role going forward:

Generative AI is drastically changing our approach to technology and how we code and program new tech. We are seeing the first glimpses of software 2.0, where applications can be created much faster through automated coding assistance. This AI will change how developers can create and scale their applications across different software platforms.   

GitHub’s copilot, for example, is a coding assistant that helps developers write code faster. In fact, in a survey conducted with 500 US-based developers, GitHub found that:  

Over the past two years, conversational experiences have been at the forefront of how businesses interact with customers. From conversational commerce, marketing, and support, brands are starting to grasp the importance of guiding customers through their journey comfortably and conversationally. 

Since GenAI can generate natural language, art, music, and other creative outlets that normally only humans could produce – the initial hype gave people reason to fear its impact on the workforce. But that didn’t necessarily happen. GenAI, as impressive as it is, is generally easy to identify. Much like in the GitHub copilot example, GenAI has become a tool that helps people complete work faster and more efficiently rather than replacing them entirely.

The GenAI hype brought about conversations about ethical concerns with the new technology. How safe is it to use? Is it ethical to use in all situations? Should stricter regulations govern how and when we can use GenAI?   

Co-creation plays a huge part in the development of ethical GenAI uses. At Infobip, we have spent a lot of time innovating with GenAI, collaborating with partners and customers, and adhering to government regulations to help keep our AI solutions ethical.  

The first step in figuring out an ethical approach to implementing GenAI is to understand the goal of the business, for example:

We can then co-create with partners like Microsoft and their Azure OpenAI Service to develop a GenAI solution for the use cases. But we must go further to ensure the solution is ethical. 

We must integrate quality controls in pre and post-processing development to prevent bias, AI hallucinations, and toxic answers. In some cases, we integrate other chatbot technologies like an intent-based chatbot because if we identify problematic responses from GenAI, the intent-based chatbot can provide a predefined answer, which minimizes the risk of unethical behavior.

GenAI can help businesses expand their reach to populations that don’t normally have access to such conversational solutions. For example, in one case, farmers in South Africa who use a specific slang English dialect would typically have trouble interacting with a regular chatbot. But we can now feed their answers through a GenAI translator, generate a response, and translate the response back to their preferred dialect. This is a great ethical use of GenAI to improve user experience in every part of the world.

These are examples of how we can increase access to this technology by introducing additional steps and co-creation when we understand the user and what the business is trying to achieve ethically.  

Some fantastic projects have emerged since the launch of ChatGPT, which put generative AI on everyone’s radar – worldwide. Check out two impressive examples of GenAI that offer conversational and ethical experiences, designed and launched thanks to co-creation and innovative thinkers.

LAQO is Croatia’s first fully digital insurance company, meaning conversational experiences are at the core of its success. By integrating a AI-powered customer support assistant, customers can quickly get their questions answered and submit insurance claims over WhatsApp. To date, the chatbot handles about 30% of all customer support inquiries. If it cannot help, the customer is easily transferred to a live agent to complete the conversation.  

Podravka, a European food and pharmaceutical provider, launched an AI-powered assistant on their culinary platform, Coolinarika. This engaging solution can interact and provide customers with healthy recipes and nutritional information to help encourage healthy eating. Podravka wanted to use AI to make a positive social impact on the growing problem of obesity in Croatia. After the chatbot launch, the platform saw a 40% increase in Millennial and Gen Z users and an 18% conversion rate to engaged users.