Top 6 AI trends that are dominating in 2021
According to the IDC spending guide, global spending on AI systems will touch near to $100 billion by 2023. Today, more than 70% of devices that we use are AI-related in a multitude of ways. AI has pervaded across multiple sectors, including logistics and supply chain, telecommunications, insurance, banking and finance, the mortgage for better serving customers and improving process efficiency. It will be exciting to see what spotlights today in the field of AI.
Robotic Process Automation
Intensive data and document-centric companies like insurance, supply chain, healthcare, banking, and financial sectors would be leveraging RPA to extract data from complex unstructured documents coming from different ways such as emails, fax, papers, hand-written documents, pdf formats, and much more. The main objective of leveraging RPA will be to ease employee pressure, for smoother operations functioning, and faster decision making.
RPA will use natural language processing and machine learning to convert unstructured data into structured information that could offer well-defined output for businesses.
Increase in demand for Ethical AI
There is an extensive demand for ethical AI in this decade. According to Forrester, c-suite information officers will have to respond to digital transformation and take-charge in managing uncertainty and business progress by practicing ethical use of AI.
Looking at how trends are changing today, businesses have to act and implement AI responsibly, and organizations have to be bold to choose business partners who are committed to data ethics in the upcoming years.
High influence of voice and language-driven AI
Due to the inefficient customer services and lower customer satisfaction levels, multiple organizations are involving AI voice, which can be also termed as digital or virtual assistant. It is an application program in which the robots understand human voice and complete the desired tasks for customers.
The pandemic has made people work to remotely that has given an opportunity for businesses to adopt voice and language-driven AI using Automated speech recognition (ASR) and Natural language processing (NLP). According to ISG’s Butterfield, less than 5% of all customer contacts are usually checked for quality feedback. Hence, businesses can utilize AI to complete the quality checks on consumer understanding that also intends to ensure continued compliance.
The rise of artificial intelligence of things – AIoT
AIoT is the combination of the Internet of Things and Artificial intelligence. It enables connected systems to make informed decisions using the data collected.
For instance, an IoT-enabled smart car will notify the low air on tires, and with AI technology combined, it provides the nearest location where you can fill the air. The technology is called AIoT and is one of the top 2021 AI trends that has emerged under the spotlight today.
Predictive analytics is the term where every business needs today for making an informed decision for a profitable and sustainable business. Predictive analytics uses current data to anticipate future events using various intelligent resources such as machine learning, data mining, and AI.
For instance, Artificial intelligence gathers personalized data of each customer, such as their buying behavior and key emotions over a period, helping businesses to make crucial decisions for the future.
The merger of Artificial Intelligence and Cloud
AI is blending with Cloud to improve the lives of the millions soon. The voice assistants like Google Home, Siri, Amazon’s Alexa are already in place, which is a combination of AI and Cloud.
AI is improving data management. Consider a large amount of data multiple businesses generate and collect. With AI in place, it can streamline the process of collecting data, updating, and managing so that organizations can feasibly offer real-time data to clients.
According to Rico Burnett, the director of innovation at Exigent says that AI will play a crucial role in the broader adoption of cloud solutions. Hence, monitoring and managing the vast amount of data generated in the cloud platform will be supercharged with AI deployment.