Transformation beyond digital

It is not new that interacting with machines or robots is a reality in people's lives. However, the way we communicate with technology has changed a lot in recent years. In particular, we have the use of Artificial Intelligence, especially Generative AI (IAG)

Now, some scenes from old “futuristic” films are part of people’s daily lives. With a simple voice command, you can make requests to virtual assistants, such as Alexa, Bixby and Ok Google. 

The idea of ​​living in science fiction may sound attractive to some or disturbing to others, but the reality is that we are still taking our first steps with AI. And even so, the impacts of this technology can now be felt in all sectors, especially in companies. 

Professions are transforming, positions are ending and new ways of working are emerging. Like any change, it presents some challenges. But, overall, the scenario tends to be more optimistic for the coming years.

According to the report Global Tech 2023, published by KPMG, organizations consider AI and machine learning (or machine learning) as being the most important technologies for achieving your short-term ambitions. According to the research, through the implementation of AI and automation, 63% of companies had a gain in profitability ou performance.

Furthermore, 57% of corporations believe that Artificial Intelligence and machine learning, including generative AI, will help them achieve their business goals over the next three years. However, it takes time and human knowledge to extract the full potential of AI in a responsible, reliable and safe way.

In this report, Guilherme de Assis Brasil, CTO at Softplan, brings his keen eye on the challenges and benefits of Generative AI and talks a little about what to expect from this technology in the coming years. Check it out below.

Generative AI: what it is and how it impacts business models

One of the most promising areas of artificial intelligence – generative AI, allows creating new content such as images, music and text from models trained on existing data. It is a format that feeds on a set of specific data to, through machine learning, predict and produce results.

One of the most notable Generative AIs on the market in the last year was ChatGPT, a language model created by OpenAI capable of “answering follow-up questions, contesting incorrect information, rejecting inappropriate requests and even admitting its mistakes”, according to the website from the company.

In addition to it, Bing was recently one of the language models that gained users' attention. In image creation, DALL-E and Midjourney stood out the most. In September 2022, an AI-generated image even won an art competition in the USA, sparking debates about the future of photography and digital art.

However, more than knowing what is generative AI, it is important to understand how your applications can really affect the day-to-day life of organizations. Also according to the KPMG report, 45% of companies say they are prioritizing AI and machine learning because they believe that market leaders have already adopted this type of technology. But, when explaining the thought process behind their selections, the most common reason given for investing in technologies was to “copy competitors”.

And this is where the research highlights that attention needs to be paid, especially in an era where resources cannot be wasted and budgets are tight. It’s not enough to just “follow the herd”. It is necessary to have strategy and intentionality, to prevent projects from straying aimlessly and the momentum of digital transformation can be put to good use.

The SaaS business model and the use of Generative AI

Companies that operate under the SaaS (Software as a Service) business model deal with a large volume of data daily: exactly what a generative AI needs to evolve. And the technical side effect of a SaaS operation brings several positive elements to IAG, as one ends up feeding back on the other.

“The more data you have in the SaaS model, the more companies are able to train good generative AI models. The tendency here is for this partnership to function as a two-way street.”, explains Brasil. 

At the same time that generative AI benefits from the SaaS model, it also benefits. Through machine learning, Generative AI enables software to make decisions based on data, which can help SaaS companies to prevent fraud and system intrusion attempts, detecting suspicious or criminal activities.

Building an assertive interaction is the main challenge

Even amidst the speed of transformations due to advances in Generative Artificial Intelligence, you still need to do the basics: get used to the new way that technology talks to humans.

After all, we were “taught” to always expect direct answers from machines. To give an example, Softplan's CTO brings up a very common situation in the daily lives of companies: “When issuing a financial report, the expectation is that, in front of a machine, a specific and precise number will be reached: R$1,2 million . However, when asking a human being, it is acceptable to receive an answer like plus or minus a million.”

The challenge involved in transitioning from the technology we are used to to Generative Artificial Intelligence is understanding that the answer will not be completely accurate, just as a human's answer may not be.

It is important, little by little, to better build the elements so that people get used to interacting with Generative AI (IAG) tools, understanding that in many aspects it could even be incorrect. 

A visible benefit and a much greater dynamic of information management with the computer. The tendency is for Generative AI to generate a very large and positive disruption around productivity of people, due to their ability to work exposed to a large volume of information.

Generative AI, user experience and security

One of the main benefits of generative AI for the user experience is the ability to personalization, increasingly specific.  

Guilherme de Assis Brasil points out that when interaction stops being based on traditional navigation and becomes conversational, which is the essence of generative AI, countless layers of customization possibilities automated for the user. “Now, it is possible to talk to the system, without needing to memorize exactly all the paths to reach a result, when taking a report”, he reinforces. 

Generative AI Models They can be used in different sectors of a company: IT, auditing, human resources, operations, etc. When exploring these use cases, it's important to remember that despite the many opportunities that generative AI has to offer, it also presents some challenges.

Even when used legitimately, Generative AI has its risks. Models create responses based on the information they receive, so there is a danger of producing false content.

ChatGPT, for example, presents what we call “hallucinations”, inventing facts. Therefore, it was improved using reinforced learning from human feedback in order to prevent undesirable responses.

To ensure the appropriate and effective use of generative AIs, it is essential that organizations create safe use guidelines. With a responsible AI program implemented, companies can begin to advance in the development of more reliable and assertive processes with the help of this resource.   

Application of Generative AI in the public sector

The public sector is perhaps one of the places with the greatest potential to generate a significant impact on society through the use of business models. Generative AI. This is because the nature of a public operation is, in most cases, extremely complex – and an AI has the ability to solve processes with a high degree of complexity. 

When applying the Generative AI in the public sector, The tendency is for citizens to experience services that are faster, more efficient and easier to find. “Once it is possible to shorten the time between the entry and execution of a demand, this will completely change the way we deal with and receive public services”, reinforces Brasil.

The challenge, however, is the processing of a lot of sensitive information, even much more than the private sector. Furthermore, it is not possible to admit major failures, as this will impact a much larger number of people. At the judiciary, for example, the misinterpretation of data by an AI could, in theory, affect sentences. 

It's needed double down on data security and risk management, so that possible damage is properly avoided or controlled. Properly trained, generative AIs can revolutionize public management.

Find out more about how technology has become an ally of Justice

What to expect in the future

For the coming years, the Softplan executive points out that, together with generative AI, we can expect a greater process of specialization of technologies.

It reinforces the expansion of communication capacity and the evolution of new technologies such as 5G moving in partnership with generative AI. By having more possibilities to interact with data in real time, IAG will evolve quickly – and on a large scale.

“The greater the power and speed of communication, the more capillarity we will have to expand and take advantage of technologies that require greater processing”, he explains. 

Discussions about governance, privacy, copyright and disinformation associated with generative AI will still be common. It is very likely that countries will create new regulations about the use of generative AI models. 

Possible markers or trackers should be implemented, showing that the content was generated by artificial intelligence, in order to prevent calls deepfakes, when visual or audio content is altered to make it appear that someone has said or done something that is not true.

According to Gartner, we will see a rapid expansion in the use of generative artificial intelligence and AI-enabled applications. By 2026, more than 80% of companies are expected to adopt this technology, compared to less than 5% in 2023.

This means that the AI will be increasingly present in everyday business, from senior management, who will use the insights from AI to make strategic decisions, to the operational team, who will depend on it for their daily tasks.

O advancement of generative AI will transform several areas. Significant changes will need to be made in companies' internal processes so that this technology is used in a safe and assertive way, and adds value to the consumer. Enjoy and discover other impacts of generative AI here! 

Softplan Editorial

Softplan Editorial

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