In the third computing epoch, Artificial Intelligence (AI) has augmented the digital transformation of businesses owing to the countless benefits tied to it, such as faster insights, improved customer experiences and unmatched efficiency. As we approach Industry 4.0, AI trends are anticipated to witness an exponential rise while becoming more versatile and adaptive.

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Dell technologies Ireland made a 2023 forecast suggesting that AI could emerge as the “main engine of innovation” for the year given that an increasing number of organisations are beginning to resort to this novel tech in a bid to harness the ultimate potential of data and support teams. Also, research by the IDC (International Data Corporation) highlights that the AI sector might witness an investment of a whopping $500 billion this year. The Indian AI market itself is anticipated to achieve $7.8 Bn by 2025, up from $3.1 Bn in 202, at a CAGR of 20.2 per cent. 

"Natural Language Processing (NLP) that involves empowering computers with the ability to understand text and speech have been utilised by several AI services that launched last year including ChatGPT and Meta’s Galactica. The estimated worth of NLP market is expected to go beyond $341bn by 2030. This can be primarily attributed to its varied applications in chatbots, research-supporting AI systems and speech recognition," Delphin Varghese, co-founder and CBO, Adcounty India, said. 

Cybersecurity

Cyber attacks increased by 50 per cent over the previous year in 2021 and have not shown any signs of slowing down so far. This makes cyber security an utmost priority for organisations globally. The integration of AI and cyber security is nothing short of a dream come true as it would take the entire security ecosystem a notch higher. 

Kelly Ahuja, CEO of Versa Networks, said that incorporating AI and machine learning will add to the agility of IT teams and reduce the reaction time in the face of threats. 

"This would break past the conventional methods of fixing issues manually or with scripts which would inevitably be more time-consuming. AI can accelerate the automation of identity and access management systems. By integrating intelligent automation into security systems, organisations can drastically cut down the manual labour required for system security," Ahuja said. 

Collaborative AI

Human and AI collaboration will soon become a norm and we would soon be working alongside AI. Though AI has the capacity to make certain roles obsolete, yet there are several systems that would not be able to function without the perspective of a human. Celestine, the automation director of digital feedback provider Applause, commented that as the usage of AI grows, the concept of augmented intelligence would also pick up the pace. 

According to Gartner, the percentage of workforce interacting with smart AI tools on a daily basis would go up from 10 per cent today to 80 per cent by 2030. 

Risk Assessment and Management

AI has proven to be a significant tool empowering humans with the ability to bounce back from the deadly pandemic. It has aided in countless services ranging from accelerating clinical research to empowering the government to add people infected with Covid to watch list. AI can also be leveraged to track disasters produced by humans, such as forest fires, water pollution, air pollution, and other calamities that pose a threat to human existence. 

Quantum Computing and AI Integrated

With staggering amounts of data, the requirement for robust and efficient computing technologies also increases.Finance, healthcare, retail, and logistics are a few of the many industries that could be transformed by quantum computing. It has the power and the capability of carrying out calculations that are beyond the capabilities of conventional computers.

Despite the fact that quantum computing is still in its early stages, Microsoft, Amazon, and IBM's cloud-based quantum computing methods and simulations have started to revolutionise several things. With quantum computers, machine learning algorithms can find patterns and abnormalities in data, revealing insights that are not attainable on conventional computers.

The ability to develop more precise and thorough models will be a good proposition for the healthcare and financial sectors primarily, improving operational efficiency and decision-making.