Table of Contents
Are you following Gartner? If not, it’s high time one should! Being his out and out fan, Gartner is considered as The God of the software development realm and God predicts that 80% of emerging technologies will have AI at its core. By the end of 2020, more and more enterprises will be found employing a dedicated bunch of people to monitor and guide complicated stuff including machine learning and neural works.
But the real question is; is it right for my business? Very well, retaining this in thoughts I hope to give you a quick guide on AI and automation in the enterprise sector.
About Artificial Intelligence
Artificial Intelligence works like everything under the hood including machine learning, cognitive computing, natural language processing (NLP), and deep learning. In a layman’s language, AI is said when a computing system or robot acts as smartly as a human brain would or even better. They are self-sufficient beings; one of the finest examples of AI- Terminator. However, there is still a long way to go to reach this stage.
By using autonomous processes, currently, businesses are found improving operations which certainly leads to a huge change in the face of customer service. For example, AI-powered chatbots relieving humans to an extent so that they can focus on other important work.
How Impactful can it be?
Artificial Intelligence seems to be having a huge impact on the way like never before. The developed enterprise application becomes quite user-friendly for both your business as well as end-users. Moreover, it will take all the necessary insights from the way a user interacts with the application. The best examples to refer to include: Facebook, Uber, and Paytm.
A wide range of industries including finance, transportation, life sciences, federal, public sector and security, AI has touched every vertical. And in the upcoming years, the tech seems to have a greater role to play. And so, instead of serving as a substitute for human intelligence and ingenuity, artificial intelligence is generally seen as a supporting tool for enterprise software development.
It can be used to accomplish a wide range of purposes including:
- Increase competitive advantage and improve efficiency
- Advance automated interactions with customers, partners, and workers
- Multiply productivity gains by automating processes
- Power smarter machinery, vehicles and structures
- Enhance customer intimacy and thereby increase consumer demand
- Improve analysis of video and audio in real-time
Its applications include:
Ranging from Image and speech recognition to medical diagnosis, and self-driving vehicles, personalized healthcare, apart from these: -
- Fraud detection- Ability to compare millions of transactions and distinguish precisely between legitimate and fraudulent transactions
- Data security- Identifying patterns in a way data in the cloud is accessed, and report anomalies that could predict security breaches
- Marketing- AI helps to increase the likelihood of a user clicking by programming targeted ads and optimizing what mix to display.
- Recommendations- Of course, we all know that this is regarding the ability to determine what you might like to buy or watch next. This is done by analyzing millions of other users and their behavioral patterns.
- Security screening- All false alarms can be eliminated here. Moreover, several things spotted especially the ones which can be missed by the human eye in regards to security.
- Online search- Google and its competitors are improving constantly on how to deliver better results in the future.
Language mining- This language processing has the potential to aid customer service agents. In fact, it directly and quickly route customers to the required information
AI for Enterprise Software Development
This is definitely going to be the next level! Combining Artificial Intelligence with the development of enterprise software would put an inescapable in all innovation circles like never before. Further, I would like to mention certain reasons why one needs to consider AI for Enterprise Software Development.
#1 Huge support for developers as much as testers
By using common tests led by processing gadgets to avoid screen blunders in a split-second and software developers should be doing this right before sending them for quality assurance. These types of tests can operate automatically as and when the source code is checked depending on which the application manufacturer or the squad can be informed in a similarly. The test outcome will surely end up being fruitless.
#2 Leveraging the Test Scope
Software testing when combined with artificial intelligence, the client here can conclude from all the profundity of tests, constant improvement in software quality to be precise. Artificial intelligence-driven software testing enables researchers to investigate the capacity limit and record content, the state of the system inside, and information tables to determine whether or not the product is working as it should or not. All in all, test mechanization will be conducting over a thousand different experiments in each trial, offering an expansion that could never have been feasible by manual testing.
#3 Less time consuming
Repeating software tests, again and again, every time source code is modified, dreary manual tests can prove to be massively and tedious specialized technical masters including Google, Amazon, Facebook and spending a tremendous amount of cash on getting AI into software. Artificial intelligence has grown as a technological breakthrough and has changed the perspective of everything, including software advancement and software testing. Let's pause for a moment and explore the job of artificial intelligence in advancing and testing software.
#4 Increasing Level of Precision
People are bound to make blunders, which is very common these days and enterprise software developers are no exception. With computerized testing, certain advances can be executed with accuracy each time an errand of testing. Testers are excluded from progressing manual assessment, and they may have a progressively critical time period to grow new robotic software tests and monitor chic properties.
The Challenges
#1 Control
Businesses must be able to control the scope of how its AI makes a decision, i.e. the ability to change from opaque to transparent where decisions can be made by AI. And trust me this is not explainable. Businesses must now turn between transparent and opaque application of AI. Now tell me what, without an expensive and major teardown, one can control the technology. Trusting AI is a major challenge.
#2 Lack of skills and AI
It has been well-documented where any organization looking to integrate AI and automation processes. For that, you will need employees who can work with and understand the technology. And instead of considering it a threat professionals must adapt themselves to focus on higher-value tasks.
And it’s a Wrap!
Incorporating Artificial Intelligence with software development procedures, businesses will be able to get the best possible outcome that can be easily inspected, analyzed, and changed.
