With endless possibilities, corporations across the globe are progressively switching to employ artificial intelligence (AI). As the machine learning facility succours businesses with a competitive advantage, here is a brief guide on how to integrate it, despite challenges.
With increased productivity and a higher level of automation, machine learning and artificial intelligence (AI) is an emerging technology. It is the intellect displayed by machines perceiving its environment and taking actions to accomplish a goal. These virtual assistants use Natural Language Processing (NLP), an ability of the computers through which they can program itself to respond in real-world languages, to match user’s input.
Various companies like Google, Facebook and Twitter are using AI to track their visitor behaviour and accordingly show posts, comments, likes and shares on their feed. Similarly, e-commerce websites like Amazon and eBay track the browsing pattern of each user with the help of AI to reach out to its customers more efficiently.
As the use of predictive analysis, NLP, and computer vision is gaining momentum, here are some initial treads to incorporate AI into businesses.
There is an overwhelming effort needed in data preparation and exploration, largely due to data quality problems. Analyse your business process and visualise your data by using interactive dashboards and insight modules. Start with data-rich processes and a well-defined business case.
Overcome AI challenges
Tackle data challenges by employing solid platforms for data preparation, prediction and visualisation. Secure your data, yet keep it highly available to let the machine intelligence access it effectively.
Grip on automated machine learning
Take out the technicality of AI modelling by leveraging automated machine learning with best of breed algorithms.
Take advantage of different skill types
To make up for lack of skills and shortage of data scientists or AI specialists, empower users of all skill types to quickly develop and deploy predictive models. Let the niche experts transform data into insights and enable the technology to start showing some results.