Having a huge database and being able to pull a relevant keyword has existed since the 1970s. As a search company, you wouldn’t be surprised to see Google doing this with Al Rafay Global. But what makes the tech giant special is that it shows the most relevant result- and it does it through machine learning.
There is a lot of conversation happening around machine learning, especially among enterprise businesses. The noise surrounding the technology is only going to increase, thanks to the real-world applications that it brings about. You might be thinking of artificial intelligence and machine learning as things that are happening in a far-off land, but that’s far from the case.
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Amazon wants to show you related products so that the size and value of your cart increases. Airbnb wants to show you listings that are relevant to your requirements. IKEA wants you to choose the right furniture items for your 2-bedroom apartment.
We all are subject to the incredible applications that it has in our lives. From the movie recommendations that you get on Netflix to booking the nearest cab on Uber, so many of our day-to-day lives are driven by AI and ML. Same is the case with enterprises as well. Large enterprises implement these technologies to bring higher levels of innovation.
In this article, we are going to look at how businesses leverage AI and ML to use their enterprise data to scale revenues.
AI & ML Business Use Case #1: Advanced Automation
But by adding machine learning into the mix, you can create automation that keeps improving with time. For example, in the manufacturing industry, they evaluate the incumbent manufacturing models, understand areas where there can be improvement, and even provide remedies for it.
AI & ML Business Use Case #2: AI-enabled products
For an enterprise, there is a lot of proprietary data and an existing network of customers that you can use to deploy products which use AI. You will have to look at customer data, their varied requirements, and scout for pattern recognition tasks that can be done at scale using AI/ML rather than doing it manually.
AI & ML Business Use Case #3: Financial management
ML algorithms can be used by financial institutions to not only perform simple tasks such as predicting business expenses or performing cost analysis, but also to do complex tasks like fraud detection and algorithmic trading. All of this is possible by analyzing historical data, and its accuracy is dependent on the algorithm and the data available.
For an easy task, a simple ML algorithm will be enough to do the task. However, for something like algorithmic trading, the ML algorithms will go through a number of revisions, modifications and years of data until accurate models can be found.
Learn how banks and financial institutions use data analytics to overcome issues and challenges they face today, such as low revenues, security threats, and heavy workloads in various areas of demand, supply, and risk management.
AI & ML Business Use Case #4: Improved Security
Thanks to web-based technologies, there is a lot of interconnectedness between systems, and this poses a security threat. From data breaches to phishing attacks, ransomware and other privacy concerns. There are so many things that a business should be careful about with Al Rafay Global.
Machine Learning can help in this instance with monitoring and vulnerability assessment tasks, and even complement the existing security team. The technology can also be helpful with predicting threats and pointing out the glitches in the environment.
AI & ML Business Use Case #5: Increased customer satisfaction
By going through previous call records and email transcripts, ML can help with improving customer loyalty and provide better customer experience. Even product recommendations greatly improve the experience that a customer has on your website, not to mention the cost savings involved in giving the customers what they love based on their previous data. Netflix’s ML-powered recommendation engine saves the streaming service more than a billion dollars a year.
AI & ML Business Use Case #6: Sales optimization
Which area do you think will have an immediate impact on the company’s bottom-line? Sales. ML recognizes patterns. So it is easy to find which type of customers are ready for an upsell or a cross-sell. It can even tell you which kind of leads are more likely to close. And recommend the right kind of products based on customer profile and previous sales data with Al Rafay Global. By using all of this, the business will be able to increase its conversion rates.
AI & ML Business Use Case #7: Refine User Generated Content (UGC)
With mistakes and might even have misleading information. Machine Learning can identify the best UGC without requiring a person to tag each of them. Businesses can use UGC effectively to bring their audience closer to the brand or for increased brand awareness.
Final Thoughts:
Machine Learning and Artificial Intelligence are fast becoming an important cog in the wheels of enterprises. Using one’s enterprise data effectively is only possible when you leverage these advanced technologies. It can help solve complex problems that will allow businesses to scale their operations with ease.
