Machine learning (ML) could not have come at a better time than now. As businesses move towards a new era of digitization, ML is needed to help in various operations of organizations, starting with data processing to customer support. Machine learning algorithms learn from data and find different hidden patterns and insights, which is crucial for businesses to make critical decisions. ML and artificial intelligence tools and algorithms have gained fame over the past few years in business circles and the analytics community due to their potential to help sift through massive amounts of data from different sources. With growing data volumes, higher and faster computational power and affordable data storage, machine learning has become more feasible now than ever.

The past two years have been among the most challenging ever witnessed in the history of humanity. They were full of untold suffering among citizens, businesses and governments across the globe. With the spread of the pandemic, which resulted in far-reaching health and safety restrictions, online work became the norm. This is where modern technology came into aid. One modern technology that has proven helpful during the pandemic is artificial intelligence (AI). AI applications played a critical role in saving lives and fostering economic resilience during difficult moments. With the potential of AI in different areas, this technology is advancing on many fronts with research and development to improve its capabilities of this technology. AI is now driving other industries, including autonomous driving, e-commerce and quantum computing. Here are some AI developments that will shape 2022 and beyond.

There is a major disconnect between what people would want to do with AI and their potential to actually do it. With the rising number of companies now adopting artificial intelligence in their operations or planning to invest in it to enhance their products, operations, and services, this technology must be understood with regard to its potential and challenges. Get past these roadblocks to AI implementation and succeed in your implementation plan.