5 Ways Machine Learning Will Impact the Entrepreneurial Landscape in 2023
The opinions expressed by entrepreneurs contributors are their own.
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 businesses. This is especially true after the Covid-19 pandemic accelerated the adoption of machine learning.
How your business implements machine learning can have a direct impact on its performance in the coming year, especially as AI tools are used in a wider range of Commercial activities. By understanding where machine learning is likely to have the greatest impact, you can proactively adopt these tools for your own business efforts.
Related: Find out how machine learning can help your business
Decision-making automation:Machine learning's ability to efficiently analyze and interpret large amounts of data in a rapid time frame has made it a critical part of many companies' decision-making processes. In some cases, these tools can even be used to automate simpler, lower-level decisions that might otherwise be made by customer service representatives or others.
In this situation, machine learning extracts data from previous actions and trends, and uses the available data to recommend the most effective solution to a problem or request. This allows employees at all levels to spend less time focusing on more repetitive decision-making tasks so they can focus their efforts on deeper issues.
This is undoubtedly part of the reason why 81% of employees believe that AI improves their performance at work, with 49% specifically citing better decision-making.
1. Improved privacyWhile many consumers are concerned that big data and machine learning will negatively affect their privacy, machine learning is often used to improve privacy and protect data.
In a recent article for the Turkish Journal of Computer and Mathematics Education, Pramod Misra details several ways that machine learning can contribute to privacy, including through machine learning privacy counters, 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, the Misra research team was able to use PPML to model threats and prevent data leaks from various attack methods. In this case, machine learning is used to provide security for other enterprise applications.
Related: What is machine learning and how can it help content marketing?
2. Smarter customer recommendationsOne of the most popular uses of machine learning has been in customer recommendation engines. Examples of these tools include Amazon recommending additional items for a shopper to add to their cart based on past 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 provide a more streamlined and
The opinions expressed by entrepreneurs contributors are their own.
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 businesses. This is especially true after the Covid-19 pandemic accelerated the adoption of machine learning.
How your business implements machine learning can have a direct impact on its performance in the coming year, especially as AI tools are used in a wider range of Commercial activities. By understanding where machine learning is likely to have the greatest impact, you can proactively adopt these tools for your own business efforts.
Related: Find out how machine learning can help your business
Decision-making automation:Machine learning's ability to efficiently analyze and interpret large amounts of data in a rapid time frame has made it a critical part of many companies' decision-making processes. In some cases, these tools can even be used to automate simpler, lower-level decisions that might otherwise be made by customer service representatives or others.
In this situation, machine learning extracts data from previous actions and trends, and uses the available data to recommend the most effective solution to a problem or request. This allows employees at all levels to spend less time focusing on more repetitive decision-making tasks so they can focus their efforts on deeper issues.
This is undoubtedly part of the reason why 81% of employees believe that AI improves their performance at work, with 49% specifically citing better decision-making.
1. Improved privacyWhile many consumers are concerned that big data and machine learning will negatively affect their privacy, machine learning is often used to improve privacy and protect data.
In a recent article for the Turkish Journal of Computer and Mathematics Education, Pramod Misra details several ways that machine learning can contribute to privacy, including through machine learning privacy counters, 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, the Misra research team was able to use PPML to model threats and prevent data leaks from various attack methods. In this case, machine learning is used to provide security for other enterprise applications.
Related: What is machine learning and how can it help content marketing?
2. Smarter customer recommendationsOne of the most popular uses of machine learning has been in customer recommendation engines. Examples of these tools include Amazon recommending additional items for a shopper to add to their cart based on past 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 provide a more streamlined and
What's Your Reaction?
