Enterprise Development Software with AI – Examples

Artificial intelligence transforms many fields of running a modern corporation. In general, technologies and solutions like AI, ML, and business intelligence help companies work quicker, more efficiently, and smarter. Among many, AI and ML transform modern enterprise application software (EAS). In this article, we are going to show you some of the crucial examples of enterprise development software combined with artificial intelligence. Let’s just dive in!

However, first things first. Perhaps many of you have already heard the EAS abbreviation. It stands for Enterprise Application Software, and, in general, it’s used to describe software that large companies utilize to meet their specific needs and goals. EAS is typically a tailor-made solution designed to help companies with their:

• Customer service and customer relationship management (CRM)
• HR and workforce management
• Taxes and finances
• Marketing and sales
• ERP and many more fields.

What’s also essential is that enterprise development software is designed to aid the entire organization, its every department, and its branch. Therefore, such a solution is, in most instances, fully scalable and centralized. As a result, even a worldwide company with offices and departments on all continents can easily use these tools.

The limitations of traditional EAS

When it comes to traditional enterprise development software, there are some serious limitations. One of the major ones is related strictly to the human factor. You see, in typical EAS, human activity is at its core. This means that human employees are responsible for entering, modifying, and deleting data. As a result, corporations struggle with errors, inadequate information, personal biases, misrepresentations, etc.

This could lead to many severe problems, just to mention:

• Decreased efficiency
• Data gaps
• Incorrect reports
• Incorrect financial documents, etc.

And finally, enterprise development software has one more major flaw. The vast majority of companies have to implement a series of changes and adjustments to use this new tool effectively. It’s even necessary to rebuild some of the processes or procedures within a company in many cases. Just to accommodate the process capability software!

How can AI improve enterprise development software?

We believe that artificial intelligence and machine learning answer the majority of the issues mentioned above. Although they are not strictly the same technology, AI and ML are tightly connected, and both of them can be used in order to enhance enterprise development software.

According to BusinessWire, by 2025, at least 90% of new enterprise apps will embed artificial intelligence[1].

Enhanced insights and analytics

In 2019, 1/3 of IT leaders were planning to use ML for business analytics[2]. And for a reason! Every year, companies gather, process, and produce hundreds of thousands of gigabytes of data. Today, when it comes to business and IT, we usually speak of big data. A construct that’s so vast and voluminous, it’s almost impossible to analyze it using traditional means. This is where machine learning comes into play

Enterprise development software that’s combined with ML-fueled algorithms is much more efficient in analyzing large amounts of data and gaining useful insights. According to refinitiv.com[3], the crucial machine Learning applications in 2019 were:

• Risk management: 82%
• Performance analysis and reporting: 74%
• Trading and investing idea generation (alpha generation): 63%
• Automation: 61%

So yes, with AI, you can improve your analytics and the decision-making process in your company. In many instances, even up to 10-20%!

Data optimization and energy consumption

Typically, large companies use data warehouses and data lakes to store their big data. However, this does not mean that these forms of storing data cannot be optimized. They can, thanks to machine learning.

As we can read in Google’s paper “Machine Learning Applications for Data Center Optimization”, published by Jim Gao:

“We develop a neural network framework that learns from actual operations data to model plant performance. The model has been extensively tested and validated at Google DCs [Data Centers]. The results demonstrate that machine learning is an effective way of leveraging existing sensor data to model DC performance and improve energy efficiency.”[4]

What about energy consumption? In 2016, DeepMind (a machine learning company that works with Google) reported that they managed to reduce Google Data Center cooling bills by 40%. You can read more about that achievement here.

Empowered employee intelligence

AI-fueled enterprise development software can enhance your employee intelligence by increasing ROI for every dollar spent on talent and workforce management. For instance, EAS designed for HR purposes can help you devise more effective and tailor-made training programs for each one of your employees. As a result, your company saves time, money, and has a more qualified team. Similarly, the recruitment process can be improved and simplified.

Consider the example of the resume selection software called Olivia[5]. It’s an application made by the Paradox company. In essence, Olivia is an AI algorithm that helps in screening candidates and even answering their questions during the recruitment process.

Optimized supply chains

The COVID-19 pandemic has altered many businesses and sectors. Especially many retail companies had to rethink their supply chains. As it happens, AI can significantly improve your supply chains and logistics in general.

Today, the supply chain management applications with AI features flourish. E-commerce and logistics companies are more and more interested in utilizing them. That’s because they help:

• Improve the delivery process (primarily the Just-In-Time delivery systems that align raw-material orders from suppliers directly with production schedules[6])
• Reduce costs
• Anticipate potential problems

According to the MHI Industry Report, 12% of supply chain professionals say their organizations are currently using artificial intelligence (AI) in their operations, and 60% expect to be doing so within the next five years. And another report, published by McKinsey, shows that a majority (63%) of early AI adopters have seen revenue increases, and around 44% report cost savings[7].

Now, let’s take a look at some of the intriguing enterprise development software examples.

Enterprise development software examples

Enterprise development software example: SAP Hana

It’s a database management system where you can develop intelligent and live solutions for quick decision-making on a single data copy. It uses machine learning algorithms to embed artificial intelligence into applications and analytics that happen within HANA[8]. HANA duplicates and ingests structured data from many sources and processes it to understand customer problems and choices. HANA analyzes customer satisfaction data, financial transactions, data from production plants, and data from desktop computers and mobile devices.

Walmart is one of many companies that utilize SAP HANA. They are using this tool to record and process high volume transactions in an effective way.

ENTERPRISE DEVELOPMENT SOFTWARE EXAMPLE: AVANADE

Avanade was founded as a joint venture between Microsoft Corporation and Accenture LLP. Generally, this company has built a data-based insight and predictive analytics tool. Companies utilize this tool to increase customer engagement, optimize supply chains, optimize asset management, detect fraud, and increase revenue. It also has features that aid companies in business analytics, robotic process automation, and the IoT.

Pacific Specialty, an insurance company, utilizes Avanade to facilitate team and company growth.

Enterprise development software example: Siemens MindSphere

MindSphere is an industrial IoT-as-a-service solution that uses advanced analytics and AI to power IoT solutions. It’s a Siemens’ tool based on machine learning. They are utilizing it in order to monitor and validate how their industry machinery equipment is working.

MindSphere also helps to schedule maintenance and manage equipment efficiently. As a result, their equipment’s lifespan is elongated.

Enterprise development software example: Domo

Domo is a mobile, cloud-based operating system that unifies every component of a company and brings it together into one place. In essence, DOMO offers a digital dashboard that gathers information from various sources (internal data, Salesforce, Square, Facebook, Shopify, etc.) and presents it in a legible way to help companies make accurate business decisions.

In March 2017, they announced their new project–Mr. Roboto. This feature offers a new set of capabilities that uses machine learning algorithms, artificial intelligence, and predictive analytics to enable more advanced insights and recommendations[9].

Enterprise development software example: Apptus

If you run an e-commerce business, Apptus is right up your street. It’s an online merchandising solution used to convert shoppers into buyers. Generally speaking, Apptus offers recommendations on actions that e-commerce companies can take to boost their sales. How does it work? Apptus is all about understanding consumers. It combines big data and machine learning algorithms that help companies determine which products might be attractive to a potential customer.

Apptus combines site search, navigation, recommendations, ads, and email recommendations into one app. What’s especially interesting, each component learns from and informs the others. As a result, Apptus allows you to offer a more relevant user experience that ultimately leads to higher conversions and increased sales[10].

Today, thanks to artificial intelligence and machine learning, enterprise development software flourishes. If you run a large company and want to tweak your sales or operations–you should be vitally interested in AI Software Development. We are happy to help you find a suitable solution. Just drop us a line, and let’s chat!

References

[1] Businesswire. IDC FutureScape Outlines the Impact “Digital Supremacy” Will Have on Enterprise Transformation and the IT Industry. Oct 29, 2019. URL: https://www.businesswire.com/news/home/20191029005144/en/IDC-FutureScape-Outlines-Impact-Digital-Supremacy-Enterprise. Accessed Oct 13, 2020.

[3] FinancesOnline. 60 Notable Machine Learning Statistics: 2020/2021 Market Share & Data Analysis. URL: https://financesonline.com/machine-learning-statistics/. Accessed Oct 13, 2020.

[4] GoogleUserContent. URL: https://static.googleusercontent.com/media/research.google.com/pl/pubs/archive/42542.pdf. Accessed Oct 13, 2020.

[5] Paradox. URL: https://www.paradox.ai/. Accessed Oct 13, 2020.

[6] Caroline Banton. Just in Time (JIT). Feb 17, 2021. URL: https://www.investopedia.com/terms/j/jit.asp. Accessed Oct 13, 2020.

[7] Terry Brown. Impact of AI in Supply Chain Management. Apr 28, 2020. URL: https://itchronicles.com/artificial-intelligence/ai-in-supply-chain-management/. Accessed Oct 13, 2020.

[8] SAP. SAP Business Technology Platform. URL: https://www.sap.com/products/hana.html?btp=8ef0cba7-2637-4828-8892-d48c37196a73. Accessed Oct 13, 2020.

[9] Domo. Domo Announces Mr. Roboto, The First Advanced Intelligence Platform to Fully Integrate Machine Learning and other AI Technologies into The Business Cloud. Mar 28, 2017. URL: https://www.domo.com/news/press/domo-announces-mr-roboto-the-first-advanced-intelligence-platform-to-fully-integrate-ai-technologies. Accessed Oct 13, 2020.

[10] Apptus. eSales – Radically Smarter Merchandisning. URL: https://www.apptus.com/esales/. Accessed Oct 13, 2020.