With large tech organisations embracing the power of machine learning, smaller companies are becoming more interested in the capabilities. Machine learning is an application of AI that uses statistical models and big data to predict future trends, and it can be applied across just about every industry.
Machine learning, as the name implies, is the concept that machines can increase their intelligence. The idea is at the core of nearly all AI theory, as it is generally more feasible to teach a machine how to learn and process information gradually than it is to program the relevant data into the machine from the outset. Machine learning enables AI to detect patterns in structured data. One well-known example of machine learning is predictive recommendations, including those found on many e-commerce sites and streaming services.
Machine learning can be used to analyse information from emails, calendars, and CRM data to proactively recommend actions, such as the best email response to move a deal forward.
Machine learning technology helps provide actionable insights to improve marketing campaigns and decisions. Many marketing departments already use machine learning and AI to enhance predictive models and reach revenue goals.
One of the greatest advantages of machine learning is the automation of repetitive tasks for better productivity. Many businesses use automation for email and administrative tasks, Internet of Things, as well as chatbots for customer service needs.
Machine learning recognises patterns in data, so these algorithms are excellent for identifying suspicious activity and detecting fraud. While these uses are most notable in finance and network security, the capabilities are beneficial for many industries.
The algorithms used by Google and other search engines are informed by machine learning, so many businesses use search engine optimisation (SEO) to keep their websites at the top of the rankings. Tools like Google Analytics use machine learning technology to enhance pattern tracking and provide feedback to their customers.
Customer lifetime value prediction and customer segmentation are among the significant challenges that marketers face. Companies amass huge amounts of data, which can be used to gain insights about business decisions. Machine learning can help businesses predict customer behaviours and purchasing patterns to send personalised offers to individual customers.
Many manufacturing companies need preventative and corrective maintenance practices, which are too often inefficient and costly. Machine learning is changing that, however, by discovering patterns in factory data to reduce the risk of unexpected failures and added expenses.
Data cleaning is time-consuming, but if it isn’t done, businesses are left with inaccurate or duplicate data that distorts insights. Machine learning can reduce the errors from manual data entry, providing clean, valuable data that allows employees to spend their time with analysis.
Machine learning is often used with e-commerce websites to find product recommendations. The process uses a customer’s purchase history and product inventory to identify patterns and separate similar products into groups. These products can be suggested to customers to motivate a purchase.
Image recognition is a unique capability of machine learning that can be used to produce information from images and other data. It’s currently in use across many industries, including automotive, cybersecurity, and healthcare.
One of the earliest and most prominent uses of machine learning in our daily lives is spam detection. Email providers use rule-based techniques to filter out spam, but new filters are in development that use neural networks to effectively reduce spam and phishing messages with fewer inbox errors.
Machine learning can be used to improve the security of an organisation by detecting threats. Using this information, security providers can develop technology to combat common risks and enhance security efforts.
In addition to retail, machine learning has its own uses in many industries, such as healthcare and medical diagnoses, government, financial services, and more.
Machine learning has numerous benefits for virtually every industry, which is only expected to improve as more capabilities are realised. Though many people are concerned that machine learning will replace human jobs but the goal of machine learning in business is to replace the redundant tasks that waste human employees' time. Ultimately, machine learning can never replace human intuitive, insight, and connections.