AI has been disrupting nearly every part of business management in recent months. With a slew of advancements, it could soon make every aspect of business more efficient.
A dynamic aspect of using AI is machine learning, which is the process by which a software learns from frequent and common actions that users take, and turns them into automated workflows.
Machine learning can be used to organize and analyze large batches of information effectively. It also enables easier searches for relevant content. Machine learning organizes information and adds structure to previously unstructured content.
The benefits of machine learning are many including:
• More efficient processes
• End users are no longer required to manually perform these tasks
• The software will work 24/7 and always be updated
• Document-intensive businesses will be positively affected
Depending on the level of machine learning implementation, appropriate tags and metadata must also be supplied to make it more efficient. This means that it will not only record reader preferences, but also recommend posts to readers based on their previous searches and clicks.
When coupled with machine learning, AI can help to manage digital content effectively and efficiently. Artificial Intelligence will soon also be used in content management, to analyze past and current consumer behavior, to help determine priorities, to predict which customers are likely to buy particular products or services, and to consider the best way to reach and engage them.
Machine learning can then help in:
• Social listening and audience monitoring
• Personalized marketing
• Customer engagement monitoring and quality assurance
Every business is concerned about reducing costs incurred, particularly customer acquisition costs. By using AI and machine learning effectively, employee productivity can increase, which in turn, helps to reduce cost.
Instead of salaried employees spending their time on administrative tasks, they can focus on core competencies and boosting bottom line. Additionally, by automatically removing data with no business value, companies can reduce their overall data volume, and subsequent, storage costs.