Artificial Intelligence (AI) continues to advance and increasingly impacts the business world. Virtually every industry now uses some form of AI in their day-to-day operations, allowing for greater efficiency and reducing labour costs where jobs can be automated.
While many sectors suffered as a result of Covid, technological developments in the AI space have been accelerated by the pandemic, with lockdown resulting in the need for more AI applications in a range of business, health and education settings, with AI even playing a role in the development of vaccines.
According to a recent Forbes article, PwC predicts that by the mid-2030s, up to 30% of jobs could be automated, and CBS News reports machines could replace 40% of the world’s workers within 15 to 25 years.
Here we explore some of the emerging AI trends which could directly affect business in 2022 and beyond:
1. Chatbots – Popular with businesses and consumers alike, chatbots are AI systems that enable customer engagement via messaging, text, or speech. Although the AI required to understand and interpret conversations with users can be complex, several platforms are available to help with sophisticated chatbot building. With this ease of creating chatbots, coupled with consumers’ demand for 24hr services and the normalcy of using messaging apps, the automation of online chat forums will likely increase. Chatbots don’t just provide advantages to customers; businesses can enjoy reduced operating costs in customer service, marketing, payments and processing. According to a recent report by Insider, it is predicted that by 2024, consumer retail spending via chatbots worldwide will reach $142 billion - up from just $2.8 billion in 2019.
2. Fully Automated Driving – The technology needed for autonomous driving, i.e. driving without the need for any human interaction within the car or remotely, continues to develop, with heavy investment in the testing and refining of driverless vehicles by leading companies such as ARGO AI. They have spent the last month of 2021 focussing on details such as ensuring that autonomous vehicles can recognise cyclists. The applications of driverless vehicles are immense, including deliveries, public transport and even military use. The advantages could be far-reaching, with autonomous vehicles having the potential to be safer and reduce congestion and emissions.
3. Security & Surveillance - AI is increasingly being used in several forms of biometric authentication for security and surveillance. This includes face recognition, voice identification, and video analysis. This technology reduces the need for human input, with AI able to better distinguish between genuine and fake biometric information in real-time, helping businesses with everything from monitoring storage in retail or manufacturing to validating customers for online banking. More advanced ‘anti-spoofing’ technology is currently in development, allowing companies greater flexibility and accuracy for increased security.
4. Real-time video processing - refers to instances when there is a need to process streamed video content in real-time. It is mainly associated with virtual conferencing such as Zoom and Microsoft Teams. Unsurprisingly, there has been a considerable increase in demand for effective software for real-time video editing, e.g. blurring and background removal or replacement. AI algorithms are constantly being designed and updated to identify objects at fast processing speeds without compromising accuracy while also ensuring security and privacy are retained where needed.
5. Visual Inspection – Used across various industries, automated optical inspection has recently seen a surge in popularity as the technology has seen rapid improvements in accuracy and performance. Applications of AI inspection include:
- Monitoring quality control and compliance in manufacturing
- Detecting product defects on an assembly line
- Identifying faults of mechanical and car body parts
- Baggage screening and aircraft maintenance
- Inspections of nuclear power stations
- Temperature screening and anomaly detection in test results for healthcare
According to the FMEA (Failure Modes and Effects Analysis) guidelines, human visual inspection is only 80% reliable due to various factors, including different points of sight or operators, visual fatigue and defects not detected by the human eye. In theory, AI inspection can be 100% accurate, providing that the technology is working correctly, and it can therefore save businesses money through reduced errors and reduced labour costs.
6. Low-Code & No-Code Platforms – One of the most significant barriers to employing AI technology for many companies is the cost, time and expertise needed to develop AI models from scratch. With new ‘No-code’ and ‘Low-Code’ solutions becoming more readily available, smaller organisations can now look to compete in the AI arena. No-code platforms are designed to have drag and drop functionality for ease of use and without coding. In contrast, Low-code platforms are suitable for more technical users and provide easy access to the code when needed to allow for more personalisation. Both of these out-of-the-box solutions help businesses to implement AI models quickly and at low cost without the need for a large team of highly qualified data scientists and therefore have the potential to accelerate the use of AI at an exponential rate.
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