Artificial intelligence (AI) and machine learning (ML) are two of today's most talked-about technologies. But what are they, how are they different, and how can you leverage them to best support your company?
Both AI and ML are powerful technologies that have the potential to revolutionize many industries. AI refers to machines' ability to perform tasks typically associated with human intelligence, such as learning, reasoning, and problem-solving. ML is a subset of AI that allows machines to learn from data without being explicitly programmed.
Below, we discuss the differences between AI and ML and their applications in the tech landscape:
What is Artificial Intelligence?
AI is a broader concept than ML in that it encompasses the spectrum of intelligent machines capable of mimicking human cognitive functions.
The objective of any AI-driven tool is to perform tasks that typically require human intelligence. AI should be able to recognize patterns and make choices and judgments. It aims to develop systems capable of replicating human cognitive abilities in order to improve efficiency, accuracy, and automation across various industries and applications.
Ultimately, AI aims to enhance human capabilities, simplify complex processes, and drive innovation in fields like healthcare, finance, transportation, and more.
Is your organization ready for AI?
Artificial Intelligence vs Machine Learning
Artificial intelligence (AI) and machine learning (ML) are closely related, but there are key differences. ML is a type of AI that allows machines to learn from data and adapt, omitting the need for regular programming. Knowing the differences between AI and ML is foundational for effective decision-making, resource management, problem-solving, and responsible technology deployment. A few key differences are outlined in the table below:
AI vs. ML
The Relationship Between Machine Learning and Artificial Intelligence
Think about it like this: modern-day computer systems leverage AI to not only be able to process information and "think" like a human being but to execute tasks like a human would, too. Machine learning is how that intelligence continues to expand and evolve over time as it is presented with new information. Machine learning systems, therefore, become a way to not only "train" an AI-driven platform but to enhance the capabilities of that tool as well. Read More: Machine Learning Process: A Complete Guide.Benefits of AI and ML For Businesses
Professional ML and AI developers help companies achieve personalized consumer services and reduced business operational costs. The implementation of both AI and ML ultimately improves the experience for all involved and provides benefits across various industries. Below are some of their key benefits:- Automation and Efficiency
- Improved Decision-Making
- Personalization
- Scalability and Adaptability
- Data Analysis and Insights
- Predictive Analytics and Forecasting
Real-World Examples of ML and AI
ML and AI optimize business operations and customer experience through their numerous real-world applications such as:Business Automation
AI can be used to analyze the types of large data sets humans would be incapable of. They can pour over years or even decades of sales information to anticipate future trends that a human might miss. They can look at real consumer behavior to more accurately segment audiences, making it easier to successfully up-sell and cross-sell based on what a person has already shown interest in. Analytical AI tools can look at real-time performance information to make recommendations about how workers and other resources should be allocated to improve collaboration and productivity. Rather than having it take months or even weeks for a human to arrive at similar conclusions, AI can get there in a fraction of the time. With machine learning, these tools can get more effective the more they're used - all while freeing up the valuable time of human workers to focus on more important matters. Read More: Integrate AI: How Your Business Can Stay Ahead of the CurveThe Supply Chain
Both artificial intelligence and machine learning can help keep global supply chain networks functioning, even as they grow more complex, with more vendors all the time. Right now, these technologies are employed to do everything from tracking shipments to anticipating delays to problem-solving in real-time, all to avoid the disruption that could cost countless organizations money.Healthcare-Driven Applications
Artificial intelligence and machine learning are being used to process patient records and medical tests and are the backbone of wearable devices like smartwatches. They're making it easier for humans to diagnose and treat even complex conditions daily, putting access to potentially life-saving care into the hands of people worldwide. Read More: Machine Learning Integration: A Guide for Business LeadersAI and ML Gigster Use Cases
Gigster provides professional AI development services to help companies better navigate the tech landscape. Here are a few examples of how our services have helped accelerate business success in a software-driven world:eBay
Gigster built an AI model and application that leveraged Computer Vision to classify content with 98.9% accuracy in detecting problems in content and an 80% reduction in time in manual monitoring.Canon
Gigster implemented an ML-based Photo Community powered by Google’s Computer Vision Engine to enhance the customer experience.Liberty Mutual
Using drones and ML algorithms to automate the roof damage claims process, Gigster increased the safety of adjusters while saving time and costs by using AI/ML. Read More: Explore additional client success stories, testimonials, and our tailored services to discover how Gigster can transform your business with innovative solutions.Benefits of AI and Machine Learning
AI and ML lead to personalized consumer services and reduced business operational costs. Both of these concepts ultimately improve the experience for all involved and provide benefits across various industries. Below are just a few key advantages:- Automation and Efficiency
- Improved Decision-Making
- Personalization
- Scalability and Adaptability
- Data Analysis and Insights
- Predictive Analytics and Forecasting
The Future of AI and ML
In terms of the future, it's been estimated [1] that the worldwide market for AI will grow from the $136.6 billion value it had in 2022 to an enormous $1.8 trillion by the end of the decade. Everyone is doubling down on both artificial intelligence and machine learning. Make no mistake, those that don't will quickly find themselves left behind.Receive Guidance From Professional AI Developers
At Gigster, we can help your business in a variety of different ways by offering both artificial intelligence and machine learning services designed to fit your every need. Through our AI development services, you can speed up your workflows and get more value out of your data by automating as many administrative tasks in particular as possible. Contact the expert AI developers at Gigster today to find out more information.
Resources:
[1] Grand View Research (2022). Artificial Intelligence Market Size, Share | AI Industry Report, 2025. [online] Grand View Research. Available at: https://www.grandviewresearch.com/industry-analysis/artificial-intelligence-ai-market.