Key Artificial Intelligence and Data Analytics Trends


AI and data analytics have emerged as the backbone of the industry’s digital transformation.

Artificial Intelligence (AI) and Data Analytics, two prominent emerging technologies, are expected to play a key role in improving organisational efficiency and productivity in 2022 and beyond; the AI software market is expected to reach $62 billion in 2022, while the big data analytics market is expected to reach $103 billion by 2023.

The epidemic has demonstrated how volatile the market can be, and with the eCommerce and cloud computing industries continually expanding, firms must be aware of trends in order to plan and stay ahead.

1. Increased data policy and regulation of enterprises’ access to customer data will be the result of new rules.

The General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA) are two new data privacy laws designed to improve cyber security and impact how businesses handle customer data.

Businesses will be unable to sell and use their customers’ data without their consent in 2022 and beyond, must allow users to opt-out of the sale of their personal data, and must design a procedure to produce a report on how they handle and control their customers’ data when requested.

These rules give consumers greater power, and while they may be restrictive for firms, they will provide important benefits.

2. AI will assist firms in resolving skills shortages.

In 2022 and beyond, Artificial Intelligence will aid many firms in reducing hiring costs by better managing skills shortages. Because competent data scientists are hard to come by and expensive to acquire, organisations will search for other options, such as making the roles open to everyone.

Businesses using Automated Artificial Intelligence (AutoAI) may, for example, make analyst positions available to scientists with varying degrees of experience to undertake operations such as evaluating data streams, producing real-time insights, and generating machine learning models.

These businesses will be able to scale quickly as a result of the cost savings and increased efficiency.

3.AI using low-code and no-code

The terms “low-code” and “no-code” are used interchangeably. Because there are few competent data scientists available to replace unfilled roles, AI may become increasingly relevant in the coming years

 Businesses will be able to automate manual coding procedures with AI, making application development easier. They’ll also cut down on hand coding to the bare minimum in order to get results faster.

Low-code and no-code platforms will allow anybody with a rudimentary understanding of computer science or software engineering ideas to design and build programmes with the correct tools, rather than working with specialists.

This will allow enterprises and organisations to create and develop applications for their users more quickly and at a lower cost. They will also work more closely with existing teams to create more functional apps.

AI will bridge the gap between firms with professional data scientists and those without, allowing them to compete and remain ahead of the game with quick and affordable solutions.

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