Business Benefits of AI/Machine Learning Solutions Development

by Manh Do Mobile and Application Development

Business Benefits of AI/Machine Learning Solutions Development

Artificial Intelligence (AI), Machine Learning (ML), and Big Data are among the most trending topics in the IT industry in the year 2019, especially with the increasing popularity of Cloud Platforms such as: Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform allowing for a better and more efficient way of collecting and managing as well as analyzing large amount of business data. In this article, we explore a number of benefits that AI/Machine Learning can bring to businesses.

Top Business Benefits of Machine Learning

Let’s examine a number of significant AI/ML benefits for businesses, in various industries as follow:

Improvement of productivity

Data is now the new business assets, and therefore, ensuring data quality and accuracy is among the most important aspect when it comes to data management. Data duplication is one of the significant problems faced by companies looking to automate their data entry process. Machine learning can help alleviate this problem effectively through predictive modeling which enables machine to perform this time-intensive task of data entry, free up more time for employees to focus on more important task.

Effective Spam Detection

Spam detection is one of the most popular problems that was solved using Machine Learning technology. This might come at a surprise to many people as they have been experiencing this application of machine learning without realizing it. Back then, email service providers used simple rule-based techniques in order to detect spam email. Now, with the introduction of ML technology, spam detection is being done through machine learning by using neural networks to filter out spam email. Such powerful ML algorithms provides high accuracy spam-filter result of up to 99.9% and can also be used to solve other classification problems.

Recommendation System

For e-commerce or online shopping companies, product and/or services recommendation system plays an important part in the sales and marketing strategy with the ultimate aim for customers to purchase more products or services offered. With a recommender system, based on large amount of data on customers shopping history collected, a companies will be able to provide/suggest on the items that consumers could be likely to be interested in and make a subsequent purchase.

Consumers usually take and trust the recommendation from people they know such as friends or family since those people know one another so well. This is similar to how a recommendation system tries to model on. Business can leverage the data they collected from customers and provide products that are suitable and tailored to customers, the kinds of products/services that customers don’t even know that they like. Such personalized recommendation enhance the overall shopping experience and will make customers more likely to come back for more, leading to an improved of customers retention rate.

Many of the prominent companies such as Amazon have a significant chunk of their revenues (35%) generated by its recommendation engines. Another instance of successful AI adoption for business is the streaming service provider Netflix who has 75% of their movies watched by their users through recommendation system.

Conclusion

Based on the large amount of business data collected, AI/Machine Learning development enables businesses to discover new insights and market trends. Business organizations can automate various aspects of their operations such as data analysis, which used to be performed manually by human, to derive actionable insights supporting profitable business decision making.

Investing in AI and Machine Learning development can be a strategic decision which could potentially provide many benefits to business in the long run. However, similar to any software development project, Ai and machine learning development carry certain risks that need to be carefully examined and addressed before carrying out.