5 Examples of Artificial Intelligence In Business Applications
In the current scenario, data became crucial for every industry around the globe, and you know what 90% of the available information or data just generated in the span of only the last two years. Surprisingly the data is generating faster than expected, and even humans also not able to examine the data.
With all situations happening around the globe, it is clear that enterprises or industries are going to a new world where the data or information controls everything. The thing which we are discussing now is once upon a time is fiction, but today’s reality, we are using AI in BI every day.
Get to know the basic differentiation on Artificial Intelligence Vs Robotic Process Automation
Most of the organizations are now started using ML algorithms to find out the latest insights & trends from a large chunk of the data to make the faster decision with ease that helps firms to be competitive in their field.
As you feel, it is not that much easy for organizations to assimilate ML into their current business system. Now, AI got some impetus, and the business intelligence future will be AI-enabled, and after this, most of the communication will happen through conversations.
As the importance of AI is increasing at rapid speed, top firms of application providers are developing more than traditional platforms, which used to mechanize the Business intelligence (BI) & analytics process.
Along with the major application development vendors like SAP, Siemens, and GE, there other emerging companies in the market that are offering above mentioned operating systems and Software’s.
As you continue reading this article, you will get to the information about the AI providers.
BI Application Developed on ML
It is a well-known company & software for most of the industries as well as software employees. SAP platform consists of different models in their gallery, but as per our requirement, we are going to discuss SAP’s cloud platform HANA.
Most of the organizations use this software to manage databases of information they have gathered. To be more clear or precise, it will duplicate & ingests structured data like customer satisfaction from an app, relational databases, and many other sources.
You can install this HANA platform in different ways; one is by running on-premise via company server or using cloud source. The platform will collect information with the help of access points like financial transactions, equipment at production plants, desktop computers & mobile, and sensors across various business verticals.
If your salesperson is using a tablet or Smartphone to document purchase orders, and the data will be collected from those recorded transactions, which can be examined and understand by HANA to know customer or user problems and choices.
Walmart is one of the top retail chain stores (11,000) in the world and the USA, which doesn’t require any introduction. It is using the HANA platform to record & process its high volume transactions that happen in 10 seconds.
In 2015, SAP conducted a conference in which Walmart CIO officer the reason behind choosing HANA over other platforms and how to use it.
Avanade is a company that is developed by two IT giants Accenture & Microsoft that has the capability to utilize Cortana intelligence and remaining solutions for data-based insights & predictive analytics.
Pacific Specialty, an insurance company that knocked the doors of Avanade to develop a deep analytics platform with the focus to provide more information to its staff regarding the business. The insurance firm’s primary aim is to use policy & customer data to enhance team and company growth.
When you can understand your policyholder interests, trends, and behaviour with the help of analytics, the company can give good advice about existing and new products that are available with the company.
Once, the company concluded that the coming future would be filled up with smart technologies where machines will do maximum work that can be done by a human resource. According to the study conducted by the Avanade across the globe stats that most of the organizations can raise their revenue by 33% with the usage of smart technologies.
And they also revealed that it is going to create new job roles for the professionals and many more benefits to users. It is also not precisely mentioned which professionals are going to be changed with the adoption of advanced smart technologies.
Machine learning has found out many ways to improve applications that also include Apptus. The company provides suggestions on actions that companies can utilize to maximize their sales.
The company is very much focused on making a connection between the revenue of a company and customer intent to buy. The platform combines ML and big data to find out which products or services might plea to the right customer when they search online.
For better understanding, let us look at a simple example. A customer enters a shopping mall or retail store, which is using the Apptus eSales platform. He uses the platform and searches for the products he is looking out using search console. As the customer enters the information, the ML will automatically predict the products customer looking for, and it also provides products which are associated with the search item.
The firms with different sizes are using this platform, and they are 100% benefiting from among them one firm is Bokus.com based out in Sweden. As time is moving on, AI & ML platforms are improving at predictive tasks like finding out what a customer is expecting, depending on the information provided by the customer in the fill-up form.
Still, the technology in the adoption stage, Cloudera Founder & CTO, said that deep learning is very good at anomaly detection and prediction. He also said it is getting simple for deep learning networks to comprehend what information is exactly authentic. And he also says, you can not teach to the platform what to work on, just provide a chunk of data from which it will sort out what it requires.
As of now, we have gone through the use cases of ML related to service sectors like insurance and retail. Now, we are going to look after AI in BI applications.
Reasons Why Businesses Need AI-Powered BI Systems
The explosion of new big data sources, such as mobile, tablets and the Internet of Things (IoT) devices will no longer undermine businesses.
They need increasingly practical experiences. This prompts AI-driven BI frameworks that will dramatically change business data into simple, precise, real-time narratives and reports.
Delivers Insights in Real Time – Big data growth in the market makes it difficult to make strategic decisions in within deadline. In recent years, Artificial Intelligence has increased BI systems to provide dashboards that provide alerts and business insights to key decision makers.
Reducing Talent Shortages – There is a shortage of experts with data analytical skills worldwide, and the well developed country, USA also has a shortage of 1.5 million (approx.) data analysts. Therefore, it is very important to hire data experts in each department of a company to complete the given tasks.
Preventing data overload – Data is growing at an un-imaginable rate these days and can easily choke off the business activities of organizations. This is where AI-powered BI tools come in, when a company has data bursting its BI platform from different sources.
It aids to analyze all the information and provide customized insights. Therefore, investing in AI-based BI software can help organizations break down data into maintainable insights.
BI and AI- application in large enterprises
Siemens is using its ML technology to monitor and validate how their industry machinery equipment is working. For this in 216, the company launched MindSphere, which is an open industry cloud platform in beta.
The primary focus of the cloud platform is to offer monitoring machine defects for service requirements with the help of machine tools & drive train analytics. The developed app can be used by many industries to keep an eye on machinery equipment tools at the plants across the world and analyze the feat stats of their assets.
It helps to schedule anticipatory maintenance & used to manage their equipment efficiently so that they can have a long lifespan.
When you compare Predix with MindSphere, the Siemens platform can work efficiently on every machine and plant regardless of the manufacturing industry. The core intention of the platform is to help plant operators to increase uptime of their equipment and makes maintenance more competent by predicting when there is a possibility of machinery breakdown.
By using these types of platforms, the industrial plants are seeing a reduction in maintenance costs. Siemens will provide a box whenever you opt for MindSphere, which you can attach to the machines, and it will collect the information related to the performance of the equipment by which the engineer can take action.
- GE (General Electronics)
The latest technologies are taking a major part in the newest advancement in various industries. The usage of sensors increasing in physical equipment like vehicles, equipment spaces, machinery, and production plants, and these can be automated & analyzed by artificial intelligence.
When it comes to IoT, it is not about just consumer gadgets, oil rigs, commercial trucks, cargo ships, and trains can be automated or digitalized, examined, and predicting through networks.
Industries like aviation and oil & gas are using GE’s Predix operating system to know the historical performance data of the equipment by using the advantage of the industrial apps, which can be used to identify different types of operational outcomes like when there is a possibility of machinery failure.
If you think the GE developed operating system is only for rudimentary, then you are mistaken because it can digest a large amount of information and using that it can prepare a forecast within no time. And it can be done via application developed by third parties or GE.
Oil & Gas industry is using Accenture’s intelligent pipeline solution to examine pipelines which are a million miles across the globe. It gathers information from the pipelines & external sources for the safety and proper use of the resources.
When it comes to the airline industry, they are using an app called Aircraft Landing Gear that built on Predix. The app helps airline engineering crews to check for how many days it will be in service before a plane place into the service.
And the app will prepare a schedule depending on the information that helps to minimize unexpected or unplanned equipment issues & flight delays.
In an instance, it is proved that ML can help to maximize the performance of the equipment. After Pitney developed an automated solution on top of Predix, it raised its machinery yield by 20%.
- Final words
After going through all the above things, we are expecting that BI applications will be the next hot and trending area for taking advantage of AI in the next upcoming five to ten years.
It is the right time for the businesses and various industries, where ML can take further steps into how resources get managed, how operations are handled, and how it chooses. It ultimately depends on the sectors to invest in AI or not because there is a chance of getting a 100% return for your investment.
Compared to early stages now, the capabilities & accuracy of deep learning have risen, and the technology is still struggling hard out into the world among various premature adopters.
Topmost industries and firms are taking the help of USM’s AI opportunity gallery to cross-check their AI strategy or to find the high return AI projects.
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