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How Industries Are Catching Faster In Adoption Of AI/ML Use For Business Improvements To Productivity

Artificial intelligence and machine learning are the emerging technologies and among the greatest boon to the evolving industries and have helped them grow from all the verticals with the advancement in cloud computing and big data. It brings improved efficiency and productivity and better performance thereby.

In this article, we are trying to give you an idea, and the sections where AI/ML is incorporated for different areas of business improving overall productivity aiding in varied business operations. Keep reading!

  1. Engaging Customers: AI/ML offerings such as chatbots are helping enterprises invoke conversation with customers and giving a presence round the clock. This 24/7 presence has helped in marketing as well as addressing customer issues regarding the services and in multiple languages also.
  2. Conversion And Sales: AI and ML are also providing assistance in the sales process and converting leads quickly directing the sales representatives to prioritize what they should for gaining maximum leverage. It is thus helping sales teams to become more productive.
  3. Employee Hiring And Onboarding: AI and ML can help by automating the process of recruitment by sorting relevant applications in lesser time making the process less tedious for shortlisting the right talent.
  4. Employee Engagement– AI and ML are providing solutions to keep the employees encouraged and productive, both in-office and remote. Companies can now perform activities such as monitoring employees in real-time, mitigate conflicts, and accelerate learning and development.
  5. Maintenance – With AI and ML-powered assets-as-a-service, companies are now using AI and ML in the form of embedded sensors into equipment to detect defects in advance predicting where there is a need for maintenance. With predictive maintenance, companies are achieving improved productivity with less downtime and saving cost and time on unnecessary maintenance activities.
  6. Regulatory Compliances: AI and ML are helping the companies to cope up with changes in regulations and compliances for them. By automating compliance in IT systems, organizations can leave them to the robots who will carry on the functions further.
  7. Monitor Fraudulent Attacks: With ever-growing numbers of transactions in the companies, there is a concern always associated with the growing scams and cyber attacks. AI can detect fraudsters and prevent revenue loss by avoiding the malware in the system prone to phishing and other unwanted cyber activities.

Conclusion:

The future is AI and ML, the way they are advancing and helping in various industry functions is worth mentioning.  They are aiding in better decision making for critical business operations.

Nevertheless, enterprises have realized the potential of these emerging technologies and are advancing to explore new avenues to improve business productivity with applied artificial intelligence and machine learning.

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