The Technologies That Will Define the AI+ Era

It is undeniable that we are well into a technological era defined by generative artificial intelligence. We are surrounded by the echoing possibilities of this era. Although artificial intelligence has been a reality for decades – IBM has been involved in its development since the 1960s – we are finally at the stage where it can be available to the end consumer, and its applications for solving complex commercial problems are more readily available than ever. 

This is in great measure due to the application of large language models (LLMs) and the new possibilities for data management, analysis and governance that have come along with this latest innovation. Undoubtedly, for the past year we have taken a step from the +AI era (where technology and system architectures considered artificial intelligence as an additional component) into the AI+ era, a new stage where generative artificial intelligence is at the center of strategic decision-making at enterprises, as well as at the core of technological considerations.

This new era for technology has also become the starting point for a new paradigm for decision-makers in this sector. While AI regains a position at the center of decisions affecting growth, operations, logistics, and even team building, a new set of technical considerations appears at an exponential rate. In this context, it is important to remember that AI exists – and is implemented – in conjunction with other technologies that boost its potential within organizations.

Key Technologies in the AI+ Era

That is why, as we continue forward in the AI+ era, companies and leaders in the tech space need to consider other transformative technologies that will be key to sustain and propel the power of generative artificial intelligence for business. 

The first of these technologies is the hybrid cloud: Simply put, the hybrid cloud is a combination of private and public environments that create a single, local computing infrastructure that supports and executes every-day operational needs for companies. For example, for a bank, the hybrid cloud is where the transactions for their banking core could take place; for a company that needs to communicate with customers consistently, it is where the application to schedule and deliver direct messages could be executed. There are endless examples of the potential of the hybrid cloud, but in the context of the AI+ era, it becomes even more important because of how much more complex these processes will become, the exponential increase in data volume that companies will need to protect and process, and because it is the infrastructure that sustains the operations in which AI capabilities are embedded.

The “cloud” is an innovation that has long been implemented to cater to companies’ technological needs, but its relevance is more current than ever, not only because it is the infrastructure that supports operational activities, but because in the AI+ era, it will become the environment in which companies’ intellectual property and innovations are stored.

In the end, the purpose of AI for business should be to create value for companies. A significant way in which this technology will be able to do that is by creating innovative content, systems, data sets and processes. Which leads me to the following key technology. 

AI+ and Security

Another element that should be at the forefront of all strategies that consider artificial intelligence for business is cybersecurity. This is by no means a new concept; neither is it new for CTOs and CEOs. But the landscape is continuously evolving, pushed forward by artificial intelligence at a considerably faster pace than we have been accustomed to. 

Because of the amount and the nature of the data that companies must handle nowadays, the stakes for cybersecurity are also higher: in 2023, the average cost of a data breach in Latin America was US$2.46 million, representing an unprecedented increase of 76% in relation to 2020.

Looking Into the Future

Last, but definitely not least, enterprises and their leaders need to consider that the AI+ era is no longer the future, but the present. In that sense, we need to start considering and preparing for the next horizon in technological development. As far as we can see, harnessing the power of quantum computing in the coming years, it will become essential to build stronger, faster, and more secure systems for enterprises. 

The acceleration of quantum computing and the technologies of the future deserve their own dedicated entry. So, for now, I will leave you with the conclusion that the moment to make the most of the AI+ era is today. Right now, there is a landscape where artificial intelligence for business and the technological infrastructure to support it are ready to be implemented. Not only that, but all of these technologies can coexist, and be customized to solve the world’s most pressing issues, and companies’ most complex commercial, and operational challenges.