Use Cases For Artificial Intelligence


Artificial intelligence is an innovative technology that helps you to do more with less. Storqa can make your business more productive and improve your life.

AI can also help you save time and money by automating repetitive tasks. There are many ways to use AI, from creating e-commerce content to coding and product development.

AI In Business

You’re already using AI if you have an Alexa device, or if you use a chatbot for customer service. Businesses use artificial intelligence to automate business processes, gain insight through data analysis and engage with customers and employees more effectively.


AI helps businesses increase productivity, drive growth and innovation and achieve key business results. It offers data-driven, consistent recommendations and allows for faster responses to changes in the market.

AI is used in many business applications, including personalization, maintenance prediction and risk detection. Netflix, for example, has been using AI and machine learning software to recommend content based upon your viewing habits. And, the insurance industry is leveraging AI to predict fraudulent healthcare claims and reduce costs.

AI not only helps businesses provide personalized experiences for their customers, but it also helps them make better business decisions. AI analyzes vast amounts of data faster and more accurately than humans. In order to achieve this, the most important thing is to ensure that the data you feed AI is clean and structured. To achieve this, companies can use tools such as Improvado, which allows them to extract data, normalize it, perform quality control and prepare the data for AI analysis.

Unlike humans, who can be prone to biases and inconsistent levels of performance, AI systems are able to provide consistent, reliable results. This ensures that decisions and recommendations are based on sound data, reducing the chance of error. Moreover, it can reduce time spent on gathering and analyzing data, allowing valuable resources to be allocated to other business tasks.

AI In Healthcare

There are numerous use cases for AI in healthcare, including helping to reduce errors, identifying patients who could benefit from a medication switch and improving patient engagement. However, there are also significant barriers to scaling up AI in healthcare. The industry needs to invest in basic digitization, training and data-sharing policies.

One of the most pressing challenges in healthcare is finding ways to improve workflows and make data-driven decisions with more accuracy and efficiency. AI can help with these goals by automating repetitive tasks, providing better access to data and aiding medical and non-medical staff. AI can also help identify patterns and trends in data, which can provide valuable insights about the health of patients. For example, AI can detect early signs of sepsis.

However, AI must be designed to work alongside humans in order to be effective. Moreover, healthcare professionals must be aware of how AI works in order to assess whether it is safe and trustworthy. They must understand the algorithms that are used and what biases may exist. They must also be willing to embrace the latest technologies based on scientific research.

In the long term, the best way of integrating AI into healthcare will be to focus on areas which have a direct effect on patients. AI can help diagnose diseases through the analysis of medical images and simulations. It can be used to identify drugs by comparing molecule structures and analyzing chemical properties. It can also help with interpreting and processing complex unstructured data. It can standardize formats and assist with repetitive tasks such as HCC risk adjustments coding and interpreting Electronic Health Records (EHRs). Additionally, it can provide round-the-clock virtual healthcare assistants to answer simple questions or help patients navigate their insurance claims.

AI In Gaming

AI in gaming transforms gamer experiences with personalized experiences, realistic graphics and intelligent NPCs. It also streamlines marketing with data-driven marketing & automated code generation. Additionally, it prevents fraud & cheating by analyzing player patterns & behavior.

AI has become a major part of gaming. It can be used for many different applications, including character creation, dialog, and interaction, as well as real-time simulation and character movement. AI technology is a vital part of the development of VR/AR games, enabling gesture recognition and immersive environments.

Some companies, such as Beat Saber and Pokemon GO, are using AI to develop innovative gameplay with the potential to reshape the gaming industry. However, it is important to remember that incorporating AI into a game requires a human touch and innate creativity.

AI will play a greater role in the future of video games. It can create dynamic and evolving stories that will be more engaging to players. It will also enable developers to create more interactive and realistic worlds to bring their games to live.

AI will continue to revolutionize gaming, making it more efficient, faster, and more engaging. With the recent advancements in mobile devices, AI is transforming how gamers interact with their games and providing them with new and exciting ways to engage with the gaming world. Implementing AI into a video game requires complex technical considerations in order to ensure a seamless, secure integration. It is also important to keep in mind that AI can be expensive and may not always be cost-effective for small game studios or indie developers.

AI In Smart Homes

AI is being used to create integrated smart home systems that enhance user convenience, efficiency and comfort. The technology can learn a homeowner’s preferences, habits and schedules in order to automate the way appliances work. It can also improve the security of a home by integrating biometrics and facial recognition.

Moreover, the system can detect abnormalities like water leakage from pipes in walls or anomalies with gas or electricity in appliances. It will then pause these utilities in order to control the issue. It can also track, analyze and monitor data collected via wearable devices, to monitor health and fitness, such as heart rates, sleep patterns, and exercise levels. This information can be used to suggest lifestyle changes.

With the rise of voice assistants and smart hubs, AI is becoming a common feature in homes. Users can interact these AI-powered home systems through voice commands or a mobile application to control different devices including lights, appliances, and entertainment systems. These AI-enabled systems can also adapt to the family’s routines, personalizing the experience.

AI-powered smart homes can also detect potential problems and send alerts, for example, if a washing machine or fridge starts making strange sounds or vibrations. This allows the owners to take corrective actions on time, preventing appliances from failing and minimising inconveniences.

To get the most out of your AI-enabled smart home system, it is best to partner with a software development company that specializes in intelligent home automation. Working with an expert developer can help you determine the right type of AI for your smart home system and ensure a smooth installation process. Additionally, they can provide guidance on how you can optimize your system through voice commands, routines and scenes.

AI In Cybersecurity

AI can provide context and conclusions that are more relevant to suspicious behavior, allowing teams to identify threats faster and address security weaknesses. These capabilities improve the efficiency of cybersecurity teams as they can analyze large amounts of incident data faster than human beings.

AI can detect deviations from norms by observing patterns in user behaviour. This can help prevent hackers from accessing critical assets by detecting possible threats that could slip past human safety personnel. For example, IBM’s AI-powered security tools can use real-time analysis of a multitude of factors to determine the risk level of login attempts, such as the network reputation, device fingerprint and user location, in order to recommend additional verification steps before allowing a user into a system.