Before the global pandemic hit in 2020, artificial intelligence (AI), specifically the branch of AI known as machine learning (ML), was already causing widespread disruption in almost every industry. The Covid-19 pandemic has affected many aspects of the way we do business, but it has not diminished the impact of AI on our lives. It has become clear that self-learning algorithms and intelligent machines will play an essential role in this new era.
This year, AI will help automate DevOps, with AI-driven app development much larger. Aspects of DevOps can be automated and, over time, made more efficient by using AI capabilities. Some of the key areas we expect to see significant growth: AI-assisted development, including entity suggestions and workflows; data modelling and auditing; data cleansing and integrity maintenance; search for functionalities in an ecosystem of applications with Natural Language Processing (NLP); a suite of automated tests focused on data security and privacy; intelligent data mining and processing using prebuilt operations, prediction services, and forecasting tools;
On the other hand, data privacy will play a more important role. Concerns about data privacy will also affect software development in 2021. With the recent approvals of the European Union’s General Data Protection Regulation (GDPR), privacy regulation is rising. Developers are increasingly concerned about their users’ privacy and their applications, but they will need to be aware of new privacy policies for the services they offer. Increased regulation will change the types of relationships that various tech companies currently have with their customers. In addition, working remotely increases privacy and data security risks,
Business Analytics and Forecasting: With data analytics techniques, analysts collect and review a set of data over a period which is then analyzed and used to make intelligent decisions. Machine learning networks can provide forecasts with up to 95% accuracy if trained on various data sets.
In 2022 we expected companies to incorporate recurrent neural networks for high-fidelity forecasting. For example, deep learning solutions can be incorporated to find hidden patterns and accurate forecasts.
Regarding the automation of data analysis through artificial intelligence, it is expected that the analysis of large amounts of data will become even more automated. In this year of pandemic, the need to quickly analyze the data that has been generated has become more than evident. Whether we are talking about analyzing data derived from the spread and tracking of the virus or analyzing the huge amounts of medical literature generated, the application of AI and ML mechanisms will be key to agile management of global health. Therefore, new developments can be expected to be applied to all types of industries.