The Next Big Thing in AI and ML – Trends That Will Drive Innovation in 2022 and Beyond
By: Sukanya Mandal, IEEE Senior Member
Advanced technologies like Artificial intelligence and Machine Learning have had a remarkable impact on the strengthening and transformation of industries all over the world. As we move towards a digitally transformed society, artificial intelligence and machine learning continue to be transformative forces in global industries and beyond. The AI/ML market is poised to expand at a rapid pace, thanks to the increased adoption in a wide range of applications. In fact, according to International Data Corporation (IDC), the global AI market will be worth $500 billion by 2024. Additionally, it estimates that the Indian market for AI software, hardware, and services will grow from $3.1 billion in 2020 to $7.8 billion by 2025.
From a business point of view, AI can be the single most powerful tool that can be used to make key decisions, drive new revenue lines, attract new customers, and optimize business operations costs. Not only that, but it might also emerge as one of the most important technology to drive innovation in sectors like healthcare, retail, and banking.
Healthcare: In the healthcare industry, a significant number of errors can be avoided by leveraging the applications of AI. Some algorithms and systems aid in the detection and treatment of chronic diseases, and with electronic health records in place, artificial intelligence and machine learning systems are only now making personalized healthcare a reality. The future of AI is a step toward democratizing healthcare for the benefit of both patients and healthcare professionals while also making it more affordable and more accurate through AI-powered predictive care.
Banking: In the banking sector, AI plays an important role in the early detection of fraud and helps banks implement appropriate risk mitigation measures. In addition to this, banks use artificial intelligence technology to monitor payment networks in real-time, analyze data and assess transaction risk. Banks are also leveraging the power of this intelligent technology to detect money laundering and monitor for cyber threats.
Retail and E-commerce: AI has significant applications in the retail sector. AI-powered drones are expected to be able to deliver packages and significantly reduce delivery time. Additionally, it is also predicted that AI will play a critical role in all aspects of e-commerce, from customer experience to marketing to fulfillment and distribution. It will continue to drive e-commerce in the future through chatbots, shopper personalization, image-based targeted advertising, and warehouse and inventory automation.
AI/ML trends that will take the center stage in 2022 and beyond
AIoT: The convergence of AI and IoT, popularly known as AIoT, has the potential to reshape industries, businesses, and economies. AI-enabled IoT allows for the creation of intelligent machines that are capable of advanced-level behavior and decision-making without human intervention. The combination of these two streams will benefit both the general public as well as the professional community.
Tiny ML: While large-scale machine learning applications are available, their usability is limited. By operating smaller-scale ML programs on IoT edge devices, we can get lower latency, lower power consumption, lower required bandwidth, and safeguard user privacy. Because the data is not sent to a data center, latency, bandwidth, and power consumption are greatly reduced. Furthermore, since the computations are all done locally, privacy is also maintained. This emerging innovation has numerous applications in fields such as predictive maintenance for industrial facilities, healthcare industries, agriculture, and others.
Auto ML: It aims to make the creation of machine learning applications easier for developers. Off-the-shelf solutions have been in high demand as machine learning has become increasingly useful in a variety of industries. Furthermore, it will provide simple and approachable solutions to problems that do not require the use of ML experts.
Deepfakes, generative AI, and synthetic data: Generative AI refers to artificial intelligence algorithms that can generate new plausible content from existing content such as text, audio files, or images. In other words, it enables computers to abstract the underlying pattern associated with the input and then use it to generate similar content. It is thought to have enormous potential for creating synthetic data for the training of other machine learning algorithms.
The rapid advancements of AI are making innovations possible in all sectors. What was difficult to imagine a few years back, is likely now possible. This rapid advancement is what will make innovations happen soon, catering to both industrial use cases as well as enriching human lives. In the coming years, AI and ML in various shapes and forms will continue to improve and drive innovation, assisting organizations in achieving their business goals.
