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Machine learning is much more than a buzzword: it has become a major player for many companies. More and more companies are implementing machine learning and other AI tools to complement or streamline their operations. This is especially true after the Covid-19 pandemic accelerated adoption of machine learning.
How your company implements machine learning can have a direct impact on its performance in the year ahead, especially as AI tools are used across a wider range of business activities. Understanding where machine learning will have the greatest impact will help you take proactive steps to apply these tools to your own enterprise efforts.
Related: Find out how machine learning can help your business
Automation of decision making:
Machine learning’s ability to expertly analyze and interpret large amounts of data in a rapid time frame has made it an essential part of many companies’ decision-making processes. In some cases, these tools can even be used to automate simpler, lower-level decisions that would otherwise be made by customer service representatives or others.
In this situation, machine learning pulls data from past actions and trends and uses available data to recommend the most efficient solution to a problem or request. This allows employees at all levels to spend less time on more repetitive decision-making tasks, so they can focus their efforts on deeper problems.
This is undoubtedly part of why 81% of employees feel AI improves their work performance, with 49% specifically citing improved decision making.
1. Improved privacy compliance
While many consumers are concerned about big data and machine learning negatively impacting their privacy, machine learning is often used to improve privacy compliance and protect data.
In a recent article for the Turkish Journal of Computer and Mathematics Education, Pramod Misra describes several ways machine learning can help with privacy compliance, namely through machine learning privacy meters, which assess potential privacy issues associated with other machine learning models; and privacy-preserving machine learning (PPML), which trains machine learning tools to protect confidential data.
With these tools, Misra’s research team was able to use PPML to model threats and prevent data breaches from various attack methods. In this case, machine learning is used to ensure the security of other business applications.
Related: What Is Machine Learning And How Can It Help In Content Marketing?
2. Smarter customer recommendations
One of the more popular machine learning applications is in customer recommendation engine. Examples of these tools include Amazon recommending additional items for a customer to add to their cart based on previous purchases, as well as Netflix’s personalized recommendations based on a customer’s viewing history and other factors.
The end goal of machine learning in this case is to deliver a more streamlined and enjoyable experience for the customer, based on the data they readily provide to the business. Notably, many of these machine learning tools also support direct customer feedback to improve their recommendations.
While these data filtering tools are hardly new, they could still have a transformative impact on entrepreneurs in 2023. Companies that can implement specific and relevant use cases for delivering personalized recommendations to their customers will be better positioned to deliver a positive experience that helps them stand out against the competition.
3. Generative AI
In the second half of 2022, generative AI proved to be one of the hottest topics in machine learning, drawing both enthusiasm and harsh criticism. Generative AI has been used to create highly realistic photos and videos, as well as generate “art” or even simple written content.
Many artists and celebrities have spoken against AI art, largely because of the way it uses other people’s creations as source material to generate its own content. Despite the outcry, many companies are likely to make their own tentative forays into generative AI to accelerate the creation of their own content and reduce costs.
While this trend is certainly worth paying attention to, it is an area where entrepreneurs should be careful. Generative AI is still prone to imperfections, and the backlash from using it can easily outweigh the potential benefits. Time will tell how this trend will shape (for better or for worse) the business and artistic landscape in the coming year.
4. More efficient financial management
Few things can have a greater impact on a company’s sustainability than cash flow and overall financial management. Machine learning algorithms are playing an increasingly important role in a wide variety of financial tasks to help leaders make better money-related decisions.
For example, machine learning can be used for tasks such as performing cost analysis or forecasting expenses related to certain business activities. This allows leaders to better determine how an action will affect the bottom line and whether the investment will really be “worth it”.
Machine learning tools can also be used to protect businesses and customers from fraud. Fraud detection tools can use information, such as the time and location where a customer typically uses their credit card, to identify fraudulent purchases. Protecting customers is a surefire way to increase trust and build a loyal customer base.
Are you prepared for the impact of machine learning on you?
Machine learning has already had a major impact on a wide range of business activities – and will only accelerate in 2023. Whether your company has already used AI tools or is just exploring machine learning, focusing on these technical tools can go a long way in improving efficiency, productivity, and profitability.