When most people hear the words “artificial intelligence” (AI), their minds may immediately jump to AI chatbots like ChatGPT. These chatbots have been a visible, consumer-facing example of AI’s power, bringing knowledge and access to a technology that once felt like science fiction. As AI technology evolves, what are some of the other use cases that AI could be used for? In this blog, learn more about applications of AI, AI use cases, and how AI could be used across various industries and opportunities.

AI Use Cases

There are many potential industries that could be posed for disruption by AI technology. The following are some of the industries that could experience benefits from integrated AI technologies.

AI in Drug Development

The traditional path of drug discovery can be slow, expensive, and have many mistakes. It can take many years and cost significant amounts of money in order to bring a single new medication to market, with the potential for failure in clinical trials.[1] With the implementation of AI technologies into drug development processes, there could become streamlined effects in target identification, drug design and discovery, and the potential for accelerated clinical trials.

Target Identification

AI can help streamline the target identification step of drug development. The first step in developing a new drug is understanding the specific aspect of a disease that they want to attempt to target with the new drug. AI algorithms can analyst vast datasets in order to identify novel targets that human researchers might miss, potentially uncovering new pathways for treatment options.

Drug Design & Discovery

Once the target has been identified, researchers typically manually test thousands of chemical compounds and their effects on the target. Alternatively, AI models can generate and screen millions of datasets for molecules via computer simulation to predict efficacy, potential side effects, and impacts on the target. The implementation of AI at this phase of drug development can help cut down the time and costs associated with finding the right combinations to impact the target.

Accelerating Clinical Trials

AI can also optimize the trial design aspect of drug development by identifying patient cohorts based on genetic markers and medical history in order to get the most robust group for testing. It can also monitor trial data in real time to predict adverse events and ensure patient safety.

AI in Logistics and Supply Chains

The global supply chain is a complex web of suppliers, manufacturers, shippers, and retailers. When one aspect of the supply chain breaks, its impacts are felt across every aspect, all the way to the end consumer. AI can serve as a central system, enhancing efficiency, resilience, and contingencies in the case of disaster.

Predictive Demand Forecasting

By analyzing historical sales data, weather patterns, social media trends, and macroeconomic indicators, AI can help predict future product demand. This can allow companies to optimize inventory levels, reducing both costly overstock and lost sales from understocking.

Intelligent Route Optimization

For delivering, every minute and mile counts. AI-powered logistic platforms can help companies find the most efficient route based on real-time data on traffic, weather road closures, and fuel prices to dynamically reroute trucks, potentially saving money in fuel costs and reducing delivery times.

Warehouse Automation

Autonomous robots can navigate warehouses to pick and pack orders. These systems can learn the most efficient paths and can work 24/7, helping speed up fulfillment.

AI for Safer Driving

As 100% fully autonomous “self-driving” cars have been capturing headlines, the most impactful AI safety features can be implemented into the cars already on the road today, working silently to help prevent accidents.

Advanced Driver-Assistance Systems (ADAS)

This umbrella terms can include features like automatic emergency braking, blind-spot monitoring, and assisting with unintentional lane departures. These systems use a combination of sensors, cameras, and radar that assess the road and environment in real time.

Computer Vision

For computer vision use cases, the AI doesn’t just see an object, it can classify it as well. It can distinguish between a pedestrian, cyclist, or a trash can and predict their trajectory and calculate if a collision is imminent, providing a warning or even triggering breaks to avoid a collision.

Predictive Maintenance

On the commercial trucking side, AI can analyze data from vehicles sensors to predict mechanical failures before they open. AI can alert a fleet manager that a specific truck’s brakes are likely to fail in the next 1,000 miles, allowing for proactive maintenance that prevents accidents and costly downtime.

AI in Energy Management

The transition to renewable energy introduces complexity from our current systems. The sun doesn’t always shine and the wind doesn’t always blow. AI can provide tools to help manage a new energy grid that’s greener.

Smart Grid Optimization

AI algorithms can balance energy supply and demand in real time. They can predict energy output from solar and wind farms and seamlessly integrate them with traditional power sources, preventing blackouts and helping maximize the use of clean energy.

Predictive Maintenance for Infrastructure

Just like with trucks, AI can monitor data from power lines, wind turbines, and transformers to predict failures and schedule repairs before an outage occurs.

Optimizing Energy Consumption

For large buildings and factories, AI systems can learn usage patterns and automatically adjust heating, cooling, and lighting to minimize energy waste without sacrificing comfort, leading to potential cost and carbon savings.

Final Thoughts

As AI continues to become more advanced, there are many use cases for this technology beyond personal assistants and AI chatbots. AI can help transform the future through drug development, supply chain management, safer driving, and energy management. What used to be an imaginative science fiction is becoming a reality that can help advance many industries in a positive way.

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• Investing in the Future: The Rise of GreenTech
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• The Role of Private Investments in Retirement Portfolios

 

[1] https://pmc.ncbi.nlm.nih.gov/articles/PMC9293739/

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