Introduction

Data, Artificial Intelligence (AI), and Machine Learning (ML) are changing businesses are contributing to economic growth by creating efficient processes. These technologies will also transform the workplace and the nature of work. Machines will now be able to do more than humans can while complementing the work we humans do and also perform tasks which are much beyond the capability of humans.

The buzz words in the present era are data science, Machine Learning (ML), data mining, Artificial Intelligence (AI), and deep learning. These are the disciples of data.

Key differences between AI vs ML vs Data Science vs Deep Learning vs Data Mining

Let us quickly understand the main differences between data mining, artificial intelligence, data science, machine learning, and deep learning

• Data science is the umbrella for all the disciplines that is used to understand huge volumes of data. Data science research is the basis for developing smart AI products
• Unlike data science, data mining is referred to as a set of techniques and tools used for collecting, cleansing, and analyzing data. Data mining is also commonly used when working on AI projects.
• Machine learning falls within an AI system that can self-learn depending on algorithms and previously learned patterns.
• Deep learning is a kind of ML, but this approach uses neural networks for making predictions based on processed data.
• Artificial Intelligence or AI is a code, an algorithm or a technique that allows machines to mimic, human behavior or cognition.

Areas where AI, and Automation will Make a Huge Impact

AI is now standard in all businesses and not just in tech world. In fact, ninety percent of leading organizations have some kind of an ongoing investment in AI technologies. Also, businesses that have adopted some kind of AI-driven technology report a greater productivity. In the coming year, AI is most likely to have a huge impact on the following sections in particular:

• Medical:

The possible advantages of using AI in the medical field are already being explored. The medical industry has a huge amount of robust data, that can be used to create predictive models associated to healthcare. Also, AI has been more effective than physicians in various diagnostic contexts.

• Automotive:

We are already witnessing how AI is affecting the transportation world as well as automobiles with the arrival of autonomous navigation and vehicles. AI will also impact the manufacturing units, including within the automotive sector.

• Cybersecurity:

Cybersecurity is what most business leaders are worried about, particularly considering the increase in cybersecurity breaches throughout 2021 and 2022. Machine Learning and AI will be crucial tools in recognizing and forecasting threats in cybersecurity

• E-Commerce:

AI will play a crucial role within e-commerce in the future, in all sectors of the industry from marketing to user experience to distribution and fulfilment. Moving forward, AI will drive e-commerce, via chat-bots, image-based targeting advertising, a shopper personalization, and warehouse and inventory automation.

• Job Searches

AI is already playing significant role in the hiring processes. In fact, 75% of resumes are vetoed by an automated applicant tracking system, or ATS, even more they reach the hiring manager. AI is also an excellent area to focus on if you are wanting to upskill your career, or make professional profiles more competitive within the job market, particularly when you consider that AI has such significant impacts across the industries.

Conclusion

AI is definitely here to stay, whether we like it or not. The best way to move ahead is to be aware of and adapt to the technology around us, including AI.