Artificial Intelligence in Business: The Future of Business - AITechTrend
artificial intelligence in business

Artificial Intelligence in Business: The Future of Business

Business artificial intelligence simply involves using intelligent computer software with human capabilities to increase sales, improve customer experience, increase productivity and efficiency, and stimulate business growth and transformation.

AI in Business

Below are the main areas where artificial intelligence (AI) can be beneficial to businesses: Increasing Business Revenue Artificial intelligence can leverage digital technology to drive revenue for your business in many different ways.

Some examples of AI in Business are:

  • Remote location targeting
  • Smart CRM systems
  • Personalized marketing campaigns
  • Predictive pricing and supply chain management
  • Advertising decisions
  • Customized product recommendations
  • Better Customer Service AI can also enhance customer service. For example, AI-powered chatbots can improve customer support by using machine learning to personalize the customer service experience. Customized Customer Experiences AI can also help create customer experiences customized to your needs.

AI in Marketing

As an emerging marketing technology, the ability to use machine learning and AI is driving a new age of marketing in which brands use automation to analyze customer data, enrich with natural language processing (NLP), automate activities and services, and provide personalized communication that pushes traditional barriers to entry.

Businesses are applying AI to automate tasks, improving customer experience and engagement, ensuring the effectiveness of marketing programs, and improving employee productivity and efficiency.

AI in Customer Service

One of the biggest benefits that AI can bring to the customer service industry is its ability to predict customer behavior. The next time you are stuck in a traffic jam and can’t find a parking spot at the mall, know that the traffic app on your phone has the perfect solution for you. So, where AI provides only predictions that improve customer experience in the near term, we should think about how it could improve the experience and satisfaction of customers in the long term.

Customer Happiness Another expected advantage of AI in customer service is that it can be trained to anticipate customer needs before they even have them.

AI in Sales

Artificial intelligence in sales is used to predict your customers’ needs, and respond to these needs when it would be the best time to do so. The resulting automated phone calls and chatbots provide you with a better understanding of the potential client and more importantly help in deciding how to engage them more effectively. This also saves your time and increases your accuracy in decision-making.

In addition, there are also chatbots that can help in searching for specific terms and phrases that your customers are searching for. These chatbots then connect with you automatically to provide you with the relevant information that you need to provide to your customers.

AI in Operations & Logistics

Artificial intelligence in logistics means advanced software, which helps companies improve efficiency by reducing shipping costs, time, and errors.

Amazon has developed AutoRip, an AI-powered robotic service that digitally copies CDs and audiobooks and delivers them to Amazon customers’ doors for free.

Oracle has developed an AI-powered solution for shopping cart abandonment in retail stores. The solution automatically detects items customers have abandoned and alerts store personnel.

Shop.org, a supermarket company, has replaced card scanners with facial recognition software in selected stores. The facial recognition software detects customers who are shopping with expired or invalid cards.

Conclusion

An ability to process data at the edge is one of the core elements needed to achieve significant business intelligence and data mining solutions. The last few years have seen the emergence of edge computing technology, that enables the processing of large amounts of data at the endpoints, increasing the available storage capacity on the devices themselves and reducing the computing and transmission of the data.

However, technology advancements are continuously causing hardware shortages, which are not improving with time. So it is important for the companies to leverage other ways of storing and processing the data.