Artificial Intelligence is certainly making the way for the future. Although, what happens when you combine AI, data, and analytics with human intelligence? It gives rise to the phenomenon of Augmented Intelligence and its examples.
Examples of augmented intelligence help us understand the power of analytics and the speed at which AI can process data. Moreover, with its examples, Augmented Intelligence helps guide resources that rapidly make well-informed and smart decisions.
Data is certainly the new oil and a very precious asset for businesses. However, it is merely a raw material that requires refinement through analytics. As a result, businesses hire expert data analysts and scientists for effective decision-making.
Furthermore, businesses often leverage the collaboration between technological advancements and industry expertise. Hence, Augmented intelligence transforms the decision-making process and its examples capture the attention of business leaders across industries.
Therefore, here we will learn more about the concept and examples of Augmented Intelligence and the way it can transform businesses.
Learn the Examples and Concept of Augmented Intelligence
Artificial Intelligence and its systems are now a requirement for various technologies. Although there are different types of AI systems that operate autonomously, Augmented Intelligence is an important aspect.
Augmented Intelligence aka Intelligence Amplification, Cognitive Augmentation, Decision Support, Machine Augmented Intelligence, and Enhanced Intelligence. It refers to using machines and devices to improve and enhance human tasks. Moreover, it uses machine learning and predictive analysis of data sets to amplify human intelligence for better decisions.
Therefore, it enables businesses to gain insights from the data without having to prepare, process, or analyze it. Furthermore, it goes beyond the self-service business intelligence tools.
It also leverages machine learning, NLP, and automated insights to analyze the data and provide rapid insights. It not only improves the decision-making process but also increases efficiency through the actions taken.
According to Gartner, this is the definition of Augmented Intelligence, “Augmented intelligence is a design pattern for a human-centered partnership model of people and artificial intelligence (AI) working together to enhance cognitive performance, including learning, decision making, and new experiences.”
Firstly, Augmented Intelligence applies a five-function flow of action to learn using human influence. Moreover, it constantly replicates the course of action. Hence, here is the flow of functions that it follows:
- Understanding: Large sets of data are instilled in the systems. Hence, the systems analysis and assess the data to derive insights.
- Interpretation: Although, when businesses input new data into the system it then reflects on the previous data and assesses the newer data sets.
- Reasoning: Further, once the data is assessed, the system generates results for a new data set.
- Learning: Businesses then study the output and provide feedback on the output and customize the system for more desirable results.
- Assurance: It is also important to understand that the data in the systems include confidential information about the business. Hence, it ensures security and compliance using blockchain and other AI technologies.
- Firstly, Augmented Intelligence helps reduce costs by increasing accuracy. Hence, it impacts the decisions about invoice processing to sales forecasts.
- Moreover, it helps representatives take smarter initiatives on the basis of the data. As a result, it influences employees to create better opportunities for themselves and the business.
- Furthermore, Augmented Intelligence assembles human resources and technology to foster a collaborative environment.
- It also performs repetitive and time-intensive tasks to help teams work on the strategies and plans for the business.
- Above all, it works as a virtual assistant for data analysts and scientists. That is to say, it provides further insights and data to the analysts and scientists, for better actionable insights.
- It also provides opportunities for better, more accurate, and data-driven decisions for science, businesses, and daily life.
- Most importantly, it provides capabilities for decision-making processes and handling large data sets.
Here are the top solutions for Augmented Intelligence:
Oracle Analytics Cloud is an AI-centric self-service analysis tool. Moreover, it provides data preparation, visualization, reporting, and augmented analysis features.
Additionally, it gathers content from different sources and systems. Hence, it makes it easier for businesses to interact with the data and integrate information.
Sisense is one of the best tools for augmented intelligence as it provides actionable insights from large and complex datasets. It also enables businesses to combine data and provides insights through a single interface.
Moreover, it is a single-stack solution with a back-end to prepare and model data.
IBM offers a range of Business Intelligence and analytic features under two product lines. Its Cognos Analytics solution enables users to access data and generate dashboards as well as reports.
Further, IBM Watson Analytics provides machine learning abilities to improve user experience. It also automates processes like pattern detection, support for natural language query, etc.
- Firstly, it is pivotal to develop and employ bilingual resources to incorporate various expertise for enterprise-class approaches.
- It is also crucial to consider change management for the smooth adoption of new and better solutions.
- Further, businesses can collaborate business strategies with the latest technologies for integral governance of the human and machine workforce.
- It also increases agility, flexibility, and scalability by migrating data and analytics to the cloud.
- Above all, it is critical to developing white-box algorithms to detect and diagnose issues in case of any discrepancies.
In light of the Covid-19 pandemic, the retail industry is now facing various challenges. As a result, challenges like customer preferences, logistics, etc need addressing.
Further, augmented intelligence can help retailers effectively utilize data to enhance day-to-day operations. Therefore, data analysis assists to capitalize on consumer trends and optimize the inventory.
Above all, it analyzes data for inventory movement and warehousing space.
Financial institutions often look for innovative solutions to provide better services. Moreover, a change in government regulations or customer demand can have an impact on Fintech solutions.
As a result, augmented intelligence can process and analyze customer data to offer better solutions. Moreover, the data can help gain insights that will enable the banks to promote their solutions for their customers.
Hence, with such insights institutions can now indulge in various trends. As a result, institutions will reach the right demography, optimize budgets and gain more market share.
The Healthcare Industry is now observing an increase in cost. Moreover, patients now demand new payment models from hospitals. Hence, there is now a push towards a share-saving method to provide preventive care.
Above all, enhancing patient care is an important aspect that results in more revenue for hospitals. As a result, augmented Intelligence offers solutions for hospitals to enhance their operations. It also analyzes the important metrics like length of the stay, occupancy rate, etc.
Hence, the insights help hospitals allocate resources, develop daily operations, doctor schedules, etc.
The manufacturing industry now faces impeccable challenges due to the Covid-19 pandemic. Moreover, issues like disruptions in the supply chain, shortages in raw materials, etc. are on a rise. Hence, manufacturers now depend on data and other innovative technologies to survive in the industry.
Further, manufacturers now cope with the changes by leveraging on manufacturing trends and by adapting solutions for on-demand products.
As a result, the manufacturing industry uses augmented intelligence to analyze and assess key data points like production lines, shipping timings, etc. Hence, these insights provide manufacturers with more accuracy during production tasks.
In conclusion, the above examples of augmented intelligence prove that it means to enhance human productivity. Hence, the approach enables businesses to develop a future-ready analysis by encouraging data-driven decisions.
According to this recent report by Markets and Markets, the global market for Augmented Intelligence will reach $18.4 billion by 2023 with a CAGR of 30.6%.
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