How the High-Tech Industry is Leveraging Artificial Intelligence for Exponential Business Growth


Artificial intelligence and machine learning are making their way into almost every industry. His next target is the high-tech industry. The emergence of artificial intelligence in the world of engineering and mechanics has raised many questions. What is the scope of artificial intelligence in the high-tech industry? Is it a good idea to invest in AI? Will AI replace engineers? Is it easy for artificial intelligence to surpass all fields of high technology?

There is no doubt that artificial intelligence is developing rapidly. It is capable of versatile applications and has marked remarkable changes in many industries. We have the example of the algorithms of Google, Amazon and Facebook in front of us. But with current developments in AI, it can’t outperform the high-tech mechanical and engineering industry anytime soon. You can modify the traditional tools of the industry, but it is useless without human labor.

In this article, we have assessed the scope of artificial intelligence in the high-tech industry. We have also discussed the obstacles to AI adoption in the industry.

Scope of AI in the high-tech industry

AI is now part of almost every industry, including high tech. It has made significant progress in recent years and appears to have a good reach in the technology field.

The most significant development of Artificial Intelligence is in the field of research. Today, AI tools and software are much more efficient at storing data and evaluating it. They help researchers make the most of existing research. Researchers can now focus more on finding new solutions than spending time extracting information from previous work with the help of AI.

Artificial intelligence can process and evaluate data much faster and more efficiently than the human brain. It can hold much more data than traditional computing devices and process it in just seconds. Now if you want to correlate the existing database with centennial data. Or you need to generate results based on an extensive database, artificial intelligence software and tools are there to help you. They can serve as efficient assistants to the data analysts and may take over their roles one day.

AI software and tools work with much larger databases and are expected to make accurate judgments in most cases. For example, a human brain can get confused when identifying a metal or chemical. But artificial intelligence tools can detect it accurately and efficiently.

Similarly, fingerprint detection and facial feature detection can be performed quickly and with less hesitation using artificial intelligence tools. Due to the precision of AI tools, Artificial Intelligence is supposed to replace many engineers and specialists in the future.

Although the scope of AI appears to be quite promising in the high-tech industry, there are some obstacles to adopting AI.

  • Higher resource consumption

All AI-based projects require a lot of time and investment. Industries and organizations need special hardware and software tools to run the AI ​​model. Furthermore, training the model is in itself an expensive and time-consuming procedure.

Since the success rate of AI experiments is not promising, many investors are reluctant to invest their resources in such projects. Therefore, limiting investment in high-risk AI projects is one of the main obstacles to its adoption in the high-tech industry.

Building AI-based hardware and training AI models is a tedious and time-consuming process. Produces results at a slower rate.

Considering the faster pace of the high-tech industry, most AI machines and models are out of date even before they are actually run. This time lag between the idea and its execution is an obstacle in the way of developing AI.

AI software and tools rely on data feed. They can only process and evaluate the data that is in the system. Anything that is beyond the reach of existing information is also beyond the ability of artificial intelligence tools. Also, it cannot detect errors in the data sent to it.

Therefore, any human error in the data feed can result in the failure of the entire AI model. Therefore, this dependence on data is another major obstacle to its adoption in the high-tech industry.

The high-tech industry demands fast and efficient decision-making. Unfortunately, while artificial intelligence tools can make quick and efficient judgments in many situations, they lack creativity.

To date, no artificial intelligence tool can make abstract decisions based on scenarios like a human mind can. To be sure, AI tools are versatile, but they lag far behind the creative capacity of the human brain.

Ending

Artificial intelligence seems to have a good reach in the high-tech industry, especially in the fields of telecommunications and computing. But it still has a long way to go before it is adopted in the fields of biotechnology and engineering.

AI is a high risk investment. And the reluctance to embrace AI is a major barrier in the way of its development and progress.

Image credit: provided by the author; Thank you!

Anas baig

Anas baig

Product Leader

With a passion for working on disruptive products, Anas Baig currently works as a product leader at Silicon Valley-based company Securiti. He has a degree in Computer Science from the University of Iqra and specializes in Information Security and Data Privacy.


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