How AI and Data Science are poised to drive significant changes for enterprises?
Data Science has, without a doubt, been among the most treasured additions to the business ecosystem in recent years. The role of Big Data will only become more prominent on an enterprise level in the approaching years. Big Data and data science technologies are changing both front-end and back-end processes within companies that are progressively being powered by Artificial Intelligence, Machine Learning, and Deep Learning.
Below are some of the key trends observed in the year gone by, and those that are set to influence the enterprise ecosystem in 2019, and beyond.
AI as a Tool for Decision Management Will Gain Ground
There’s not much that needs to be said in this regard as the capabilities of enterprise AI platforms are renowned and have been valued all across the world. AI has already been acknowledged for its ability to help decision-makers work more efficiently; as the results from AI’s incorporation become apparent, we can anticipate seeing AI-driven technologies become more incorporated into the decision-making procedure. The dynamic nature of these technologies gives a strong foundation for enterprise decision-making engines, enhancing workflows, and delivering a superior customer experience.
AI Will Play a Crucial Role in the Hunt for Talent
AI and ML have already started to make their way into the HR industry, and it has already revealed its efficacy in finding and screening candidates, learning how an organization hires, and ranking potential candidates to confirm the right hiring decisions. Though companies find it particularly difficult to recognize and hire AI experts; besides skills pertaining to the sciences, including AI requires knowledge in social and legal issues, customer relationships, marketing, and operational management. It is because the proper training and management of AI systems are necessary to get good outcomes; put in the wrong data, and poor results are almost inevitable.
Machine Learning
Machine Learning (ML) has been in the limelight for quite some time now, and we can assume this to continue in 2019 as well. The notion of a self-learning machine may still be ‘shiny and new’ for some, but enterprises are starting to observe its practical and far-reaching applications in their business procedures. ML’s primary application is present in the field of analytics and Big Data, but we can assume to see further progressions in this field as its business applications grow.
AI-Optimized Hardware
As AI remains to become part of our daily lives – both professional and personal – we can expect to see the hardware we use become more AI-friendly also. Perhaps one of the first places where the change will begin is in the architecture of GPUs and CPUs that will be precisely designed to support AI, letting for smoother integration and operation of much more powerful machine learning and deep learning platforms which need higher processing power. Further, AI-optimized mobile tech is fast turning into reality, which will eventually make everyday interactions and data collection even simpler for businesses on a consumer level.
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