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Three trends we expect to see across Artificial intelligence in 2023

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​Artificial intelligence is starting to dominate the mainstream. With a significant growth rate of 30% annually and around 45% of companies already adopting some sort of AI within their business, the applications and improvements AI can have on a business are starting to be recognised globally.

Developments within AI are exploding; in H2 of 2022, generative AI took centre stage, with unicorn valuations made of AI businesses and significant funding rounds into generative AI businesses for text and image creation. With this in mind, there is much more to come from the AI industry.

With new commercial opportunities continuing to be realised, we look at three key trends to watch in 2023.

1. Hyper automation (or intellectual automation)

Hyper automation is the process of automating all organisational tasks that can be automated through multiple AI processes. Using this concept will help streamline the process and use robotic processes, as well as other technology which doesn't require human intervention. Gartner has already identified hyper-automation as one of the top ten trends.

How businesses are looking to use hyper automation varies; however, the Gartner report shows that those looking to adopt hyper automation see this as a critical strategic decision, not just an option for a specific situation or challenge.

Choosing hyper automation for continuous repetitive tasks can create a streamlined process which often results in cost savings and moves businesses into competitively solid positions within their industries.

One key difference between automation and hyper automation is that automation looks at an individual task. It is often run on a smaller scale. Hyperautomation uses multiple tools to enable intelligent automation, enabling businesses to scale.

2. AI Cybersecurity

AI can learn and know how to adapt to situations. Automated processes can help locate threats and create more robust cybersecurity methods.

Using AI to learn signature-based techniques (which traditionally can detect 90% of threats) could increase this security for businesses.

Vulnerability management could move from reactive to preventative using AI. "Through learning" techniques can analyse baseline behaviours from user accounts and servers and discover abnormal behaviour before it happens.

AI can also reduce the cost of hardware maintenance in data centres by monitoring essential processes such as backup power, power consumption and bandwidth usage. AI can alert ahead of potential breaks, which could take longer and cost more.

3. AI and IoT 

The Internet of Things (IoT) already has over 10 billion connections today. The number of connections is looking to rise to 22 billion by 2025. Gartner research suggests that over 80% of IoT projects in corporations will have AI and ML.

Integrating AI into IoT can be helpful to consumers, with 41% believing AI options will make life easier. For example, a smart home would allow for automatic lights, heating control and appliance operation. However, unlike setting timers, AI smart home would adapt to the homeowner's habits, making it more beneficial to the consumer.

The integration between AI, industry, and consumer use shows no signs of slowing. Creating more opportunities for efficiency and convenience in everyday life will change how we live.

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