Four Things to Tackle Before Jumping into AI

By Guest Contributor on December 8, 2018

Almost every day you must be reading a story or an article about artificial intelligence or AI. In just a few more years, AI is expected to take over all the jobs.

AI will be doing all menial, repetitive tasks performed by admins on a daily basis. Even AI is going to grow and would be inculcated in all the systems to produce more human interactions and better results.

Certainly, there is lots of stuff, which AI will be doing in the future, but there are a lot of things that AI can do even now, like custom searches, automation, analysis, security interventions, data predictions, working as a digital assistant, performing algorithm-based machine learning, and more.

It will take a good number of years for developing AI and bring it into everything, but what we can do in the meantime is to prepare ourselves so that we are able to take the advantage of AI.

So, this post discusses the 4 important things that you need to consider before getting involved with AI.

#1. Stay Up to Date to Get Best Results

If you are thinking of how AI can be useful for handling current struggles, like compliance, updates, setting adjustments, patching, and making changes to meet the baselines, then there is one thing that you first have to do on your part.

To ensure that AI is able to perform such tasks and you get rid of such mundane things, it is essential for you to stay on platforms, which are ready to get such items. For example, if your present platform is made of Windows 7, server 2003 on physical devices, individual IIS servers for every app, and VB apps, then you are not focusing on current use of AI.

You can get the best results, only if you stay up to date on everything. The best solution is to get what’s existing up to date so that you can leverage AI right away. From firmware, apps, vendors, to operating systems, you need to adopt everything latest.

#2. Collect Data on a Strong, Unified Platform

AI has already started bringing a data revolution, and organizations can get benefit from it only if they have a strong data platform. It can be simple to have a reliable data platform by simply gathering and storing data safely in one platform, connecting the apps to the unified data store.

You can connect your apps to a single data store with a cloud-based data warehousing system and begin to do basic visualization and reporting on it. The more volume of data is available, the better AI will be at leveraging it. Additionally, a single platform provides easy access and review of the data. The more data you have, the easier it would be for AI to make predictions and trends based on data. Also, more data will enhance the accuracy of the predictions made.

#3.  Modernize Every App

The next step to take before jumping into AI is to modernize your apps, which is crucial in preparing for AI to take control over day-to-day functioning and optimization of applications. If we consider the example of a usual three-tier application including data, presentation, and application, we can dissect the separate tiers and advance each with a secured data platform, hosted cloud containers, and servers.

After having reliability on individual OSEs, nodes, and other sturdy constraints are lifted, offering the application the ability to stretch, move, and expand dynamically. As a result, AI is able to perform all such actions on its own or on the basis of complex reasoning that either a human helped create or is self-developed by AI.

#4. Develop Process and Flow

You can start by developing simple flow diagrams, even on paper, but make sure you map out business and application process and workflows correctly. With a proper understanding of documented applications, data as well as businesses procedures to interact and flow into each other, it is possible to build a strong foundation of how and what the AI would be performing in your business.

It is possible to organizations to gain immense success with AI, initial contact assistants, and chatbots by ensuring that they map out a script that pulls data from one repository and even AI follows a particular workflow.

Conclusion

In addition to the above mentioned points, AI can also be helpful to organizations that have humanized their existing systems, including managing applications, executing business processes, reporting, updating systems, and more.

Though we are still handling these things without AI and have been able to reach to an advanced technology environment, if we continue doing all this work by ourselves, then we might not be able to reap the best fruit of our labor.

Hence, we should welcome AI into our environment, focus on developing AI, and make necessary changes to tackle AI in our preferred way.

This article is contributed by Kavya gajjar, a Marketing Manager at AIS Technolabs which is Web design and Development Company, helping global businesses to grow by Developing Ai Services 

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