Despite the economic difficulties that companies may face, investment in digital transformation remains high, and does not seem to be going down in the future, due to the strategic and essential role of technology in their daily lives. Within it, it is especially relevant the AIwhose future will be of great importance for the operation of companies and professionals from all sectors.
One of the ingredients for its advancement, according to Couchbasewill be the use of data in real timel. In the case of generative AI, they will be vital so that companies can enhance experiences with it. And they will become even more so as AI becomes a critical factor for business. For this reason, companies will also have to ensure that the data on which AI models are based is based on truth and reality. Furthermore, this data must be as recent as possible.
For generative AI to be effective and accurate, and its results constantly relevant, it needs to be based on data that is continuously updated, and that does so in real time. That’s why, starting in 2024, companies will increasingly leverage a data layer that supports real-time and transactional analytics. This will facilitate decision making and it will be possible to respond instantly to market dynamics.
The future will also see a move from model-centric to data-centric AI. These are currently fundamental for machine learning, but it is necessary that they are appropriately managed and selected in AI projects. The current approach to Artificial Intelligence, focused on the model, causes hundreds of hours to be lost adjusting them, since among other things they are generated from low quality data.
As Artificial Intelligence models mature and grow in number, attention will shift to improving them through data. This data-centric AI will enable generative and predictive experiences with the latest data, improving model performance and reducing hallucinations.
On the other hand, the future of AI will increasingly involve almost detailed personalization, with companies using tailored AI co-pilots to more quickly obtain the information they need. This will increase as the use of generative AI spreads, with organizations developing co-pilots in their products. In a few years, this tool will change the way companies develop infrastructures and applications. Augmented data management will automate routine data quality and integration tasks, and augmented analytics will provide advanced insights and automate data-driven decision making.
As for developers, Artificial Intelligence will separate the good from the best. While the former will use AI to lighten their workload, the latter will use it to increase productivity by eliminating repetitive and mundane tasks to focus on more creative or complicated ones, as well as to manage tasks of greater value and importance. Artificial Intelligence will continue to play a critical role in developer productivity, as long as they use it with good judgment and are clear about its limitations.
Another trend that will change the way many companies will act in the future is hyperpersonalization, which will change the way organizations connect with their customers. The trend is towards making the user feel that products, services and content have been created for them. To achieve this, it is necessary to have a real-time data infrastructure. In this way, companies will be able to collect, process and act on large amounts of data instantly to generate individualized and dynamic interactions.
Federated machine learning will also enter the scene as the popularity of generative AI grows. Given its ability to secure training models and support privacy-sensitive applications, federated learning will be central to the future of Artificial Intelligence, while addressing data privacy and security concerns.
Finally, Convergence between AI and edge computing will continue to grow, which will lead to real-time analytics and more robust decision making. AI capabilities at the edge will reduce the need to move data to the cloud, ensuring faster responses and better privacy. When combined with Artificial Intelligence at the edge, it will give the opportunity to process data efficiently locally, reducing latency and guaranteeing privacy.