AI is changing every industry and business function resulting in an increased interest in AI. The usability derived of AI in the outbreak of COVID-19 also led to a significant acceptance of AI in businesses and everyday lives. Experts believe that more than 50% of organizations use AI in at least one business function and are quick to integrate more functions. It has been a world-known fact now that scaling AI in organizations can create a massive competitive advantage, but it also requires proper strategizing and decision making.
Beyond automation, AI is helping humans by adapting as needed to ever-changing circumstances, contexts, goals, and scenarios. Today, in this blog, we talk about AI's most adopted use cases in various industries. We are in the quest to address the most talked-about sectors here, but beyond those too, AI exists and thrives every day.
Artificial Intelligence in Healthcare
Healthcare is a demanding and booming industry for AI, as the available data collected from the patients is in tons and relies on a scientific discovery which makes it complex to comprehend. However, healthcare organizations exploring and investing in AI successfully deliver artificial intelligence applications for healthcare. They are creating incredible revenue opportunities and tending to a worthy cause.
While there is no shortcut to visiting a doctor, nothing quite as concrete and dependable as a diagnosis by them. Yet the use of Artificial Intelligence Technology in healthcare applications is helping people keep track of their health and make sense of their symptoms without constantly visiting a doctor. We can choose from a wide range of AI-powered healthcare apps available on both the Android and iOS stores and use them as a medical assistant to stay on top of your medication requirements, water intake analysis, movement analysis, etc. You can set reminders on the apps for drinking water, taking medicines, checking your blood pressure or sugar levels, and using their voice assistance feature for a convenient interface. The applications are limitless, and according to Global Market Insights, we can anticipate AI in the healthcare market size to reach $10 billion by 2024. Some of the most popular opportunities for AI in healthcare include,
Re-admission Risk Management
Artificial Intelligence in the Detection of Fraud
It is no secret that the increasing application of digitalization in the various facets of our lives, from banking to shopping, is also leading to a corresponding rise in the instances of fraud. The Banking and Finance sector is highly affected by fraud and misutilization of information. That is where Artificial Intelligence Technology holds tremendous potential in providing a legible solution.
The use of machine learning algorithms to detect fraudulent transactions is one of the most important AI use cases. While human beings cannot go through millions of similar transactions and discern the suspicious ones, it is easy for AI-powered software to do so. This way, fraudulent transactions can be detected and, in some instances, stopped from being executed in real-time.
Some of the widespread usage of AI-ML in the fraud cases that exist in the real world are,
Credit Card Theft
Artificial Intelligence in Quality Control
The application of artificial intelligence in Quality Control is one of the top AI use cases. Since manufacturing is usually conducted on a large scale, the manual quality check has loopholes and inefficiencies. However, quality control processes can be easily automated and standardized with AI-enabled systems.
Whether identifying a missing accessory on a car on the assembly line or flagging a manufacturing defect in a plastic box, Artificial Intelligence Technology is increasingly employed to accomplish quality control at high speed and accuracy. Quality control is considered the second most prominent AI use case and carries more than a fifth of the weightage of AI use cases.
Some of the well-known benefits of using AI in quality control are,
Well-researched build release
Effortless test planning
Improved regression testing
Visual interface testing
Enhanced defect tracing
Artificial Intelligence in Advanced Data Analytics
Information is power, and the availability of the latest information at the right time and the right place is key to a business's ability to tap into opportunities and flourish. Data plays a crucial role in how modern-day companies shape their production and marketing strategies, from forecasting the market demand to analyzing ever-evolving consumer preferences.
The application of artificial intelligence in Data Analytics is a critical AI business use case. AI can be employed to analyze the data on market trends and consumer behavior on a large scale and draw patterns and vital information to take the necessary actions. This approach can help the business's plans become impactful, manage risk better, and optimize its supply chain.
AI in advanced data analytics helps businesses in,
Discovering new insights
Predicting business and marketing outcomes
Unifying analytics and customer data
Building a successful Artificial Intelligence Roadmap
To build a successful artificial intelligence roadmap for your organization, you must first identify the areas where AI is beneficial. Then, you must research the relevant AI use cases and study them in-depth. It is essential to assess the impact and relevance of a particular use case of AI in your organization.
Once you have shortlisted the AI use cases that are most suitable and applicable for your organization, you must go ahead with laying the groundwork for its implementation, from drawing a roadmap of the required infrastructure to the need for technical expertise. Subsequently, you can start implementing the steps in the roadmap and bring your plans from paper to the production line.
AI is set to disrupt with no downturn in sight. Companies are spending billions of dollars on AI products and services, and tech giants like Google, Apple, Microsoft, and Amazon spend billions to create those AI products and services. Educational institutes are making AI a more central part of their respective curricula, and defense departments worldwide are upping their AI implementations; remarkable things will occur. As Google's former Brain leader and Baidu chief scientist, Andrew Ng, told ZDNet in 2020, "Lots of industries go through this pattern of winter, winter, and then an eternal spring. We may be in the eternal spring of AI."
We conclude our enriching and popular AI blog series with this blog and will continue to talk about AI and its innovations through our future blogs wherever applicable. Stay tuned!
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