It’s not an overstatement to say that Artificial Intelligence is going to serve every work processes of businesses, but it needs to be approached in the right way so it does not hit any costly snags.
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Artificial Intelligence () emulates human intelligence process which involves extracting meaningful insights and patterns, predicting plausible future decisions made possible by the three major tenants of the technology which translates to Machine Learning (), Natural Language Processing () and Deep Learning (Neural Networks).
has established encapsulating everything from rule-based to image classification whose applications range from preventing high-end cybersecurity threats to object recognition. Artificial Intelligence redefines Business Processes across geolocations. Here are the use cases that explain the pursuit of in business parlance.
Customer Relationship Management
Machine Learning and have reached users on every platform be it online or offline. Artificial Intelligence deploys Natural Language Processing () techniques to interpret words, data and apply contextual and reasoning algorithms to generate useful insights and provide relevant data for analysts to focus on growing data needs.
Artificial Intelligence frees decision-makers from the rule-based mundane and tedious process of customer query handling for common questions asked. It optimizes the CRM process by relevant keyword-based searches analysing customer sentiments and answering them accordingly.
Human Resource Planning and Intelligent Recruitment
Human resource management has gone through irrevocable workflow changes with the help of and Machine Learning. The constant pile of irrelevant resumes and long hours spent on retention and appraisals are such a passé.
Though making better hires is just the start, retaining and mentoring them brings together another level of planning. tools can aid to assess employees by creating a plan to know if the employees need training, and when to motivate and reward the most deserving ones.
Customer Experience Improvement
With the advent of , the focus has shifted towards improving the customer experience from bare CRM. -based business process management helps to get accurate insights into customer’s behaviour and based on these inputs the future consumption trends can be chalked out. Implementation of chatbots that understand user intent are the most common examples of -backed customer service which promotes a transparent platform for communication.
The advancement in has introduced sophisticated algorithms such as neural networks and decision trees. These algorithms help managers, business owners to solve problems which they might face describing properties for specific datasets. -based decision-theoretic models can assist the managers to take decisions within business processes explaining whether a customer should be sent a product recommendation or needs a follow-up call.
Analysing Sales Calls
When it comes to simulating business processes and operations, sales calls are one critical aspect. Sales and revenue generation are the bread and butter of the business. Top-tier sales representatives will ensure the organisation keeps on chugging along and reaching new boundaries credit to .
Occupational fraud leads to organizations lose about 5% of their total revenue every year with a potential total loss of US$3.5 trillion. algorithms are actively quelling this trend by spotting discrepancies and anomalies in everyday processes.
For example, banks and financial institutions use intelligent algorithms to detect suspicious money transactions and payments. Besides, these processes are applicable in customs clearing processes, insurance, cybersecurity and tax evasion. Large-scale organizations which leverage are potentially looking at cost savings that tune to millions of dollars each year. These resources can be spent in other critical areas like research and development to let organisations stay ahead of the curve and remain competitive. […]