The symbiotic relationship between Artificial Intelligence and cloud computing is propelling businesses forward in strategic, efficient, and insight-driven ways while driving digital transformation across the organizations. By 2026, cloud computing market is projected to double from its current valuation to $947 Billion, on the other hand AI market is expected to grow 5 times more in the same period with $309 Billion[ ].
Let’s explore generative AI use cases in FinTech and areas within the fintech industry primed for generative AI-driven transformation. We will also walk you through the success stories of integrating Gen AI in FinTech operations.
Generative AI in enterprise stands out for massive leap in ability and its potential scope of impact across any industry and business function.
Artificial Intelligence in enterprise solutions stands out from traditional software systems because of the exponential speed at which one can do things. In today’s hyper-connected world, where speed of processing and speed to market are critically important factors, enterprise AI has the potential to accelerate digital transformation.
The healthcare sector has been the front runner in adopting digital transformation across the board. Right now, machine learning (ML), a subset of artificial intelligence, is playing a key role to address health-related areas.
Social distancing in the workplace and other surroundings is now becoming a norm. Though it is vital to understand and address how employees interact within any ecosystem.
One of the most exciting areas in testing and quality assurance (QA) at present is the potential influence of artificial intelligence (AI) and machine learning (ML). Imagine, what if the software could learn to do all the testing itself? What if it could automatically track down and weed out bugs?
Machine Learning (ML) has greatly benefited the retail industry by enabling companies to improve their bottom line. It is made possible by the generated data that helps unlock the opportunities to anticipate, adapt and meet constantly changing customer demands.
The application of disruptive tech like Artificial Intelligence is quite popular in the point of sales (POS) market especially across retail. It offers the consumers the ability to handle virtually all payment methods, across online platforms, mobile apps, via chat, social apps and of course, in-store payments.
Machine learning in fleet management helps increase business productivity & efficiency while reducing operational costs. Besides, it enables drivers to keep track of their performance and improve long-term outcomes.
In the age of digital renaissance, innovation is no longer a buzzword but a necessity. Everything around us is getting smarter by the day. Our cars, phones, homes, schools and cities – all moving towards a ‘smarter’ avatar.