5 Ways Machine Learning Can Help Entrepreneurs

Overview

Over the last five decades, technological advancement has brought about a complete paradigm shift in the business environment. Irrespective of the size of a venture, technological adaptation is attributed to improved efficiency and a general increase in the output of any business operations. Despite the short period associated with technological change within the business arena, its impact cuts across the large and small sectors. This article will illustrate five ways machine learning can help entrepreneurs. Specifically, the article focuses on efficiency, personalization of activities, multitasking, lightening of workload, and improved innovation.

Machine Learning and Efficiency of Entrepreneurs

Since time in sundry, entrepreneurs have devised different methods of improving efficiency in their approach to different business activities. It is in order to state that the primary drive of entrepreneurship is simply optimizing output, which is an active ingredient of an efficient method of operations. Machine learning has brought about artificial intelligence, which is the incorporation of technological instruments in the daily operations of an organization. For instance, machine learning has made it easy for entrepreneurs to tackle complex data-oriented activities quickly and in an efficient manner (Ivanovic, Perman & Grlj 2015). Through machine learning, an entrepreneur is empowered to have full control of the workflow. In the last two decades, artificial intelligence has enabled entrepreneurs to tackle challenges of inefficiency through the integration of technology in all aspects of production. For example, in the automobile industry, machine learning has improved on object recognition technology associated with driverless cars, electric automobile, and lighter or high-performance vehicles while reducing the cost of production. Moreover, machine learning has empowered entrepreneurs through availing a series of surveillance systems instrumental in tracking performance. From a central location, using a surveillance application allows a business owner to directly and real-time monitor every activity in his or her premise.

Another element of efficiency catalyzed by machine learning is in the improvement of accuracy and flow of data. Unlike before the advent of artificial intelligence, most business operations relied solely on the cognitive abilities of mankind, which are subject to errors and omissions (Ivanovic, Perman & Grlj 2015). Through machine learning, programs have been put in place that is capable of reducing errors associated with human negligence in a timely manner. For instance, due to the complexity of accounting numbers, Microsoft applications have created QuickBooks that enable entrepreneurs to track and accurately perform complex accounting duties efficiently with a near-zero margin of error.

Machine Learning and Personalization of Activities

In the complex and dynamic business environment, entrepreneurs may survive the impacts of stiff competition when they integrate the right hard and soft skills in the creation of focused products. Irrespective of a business environment, it is vital to implement the ideal mix of production or marketing techniques that are engineered to fit a specific customer niche. Machine learning tools such as market algorithm applications have simplified the chain of interaction between a business and its potential clients. For instance, Google and Facebook have created accurate marketing algorithms through focused artificial intelligence research that are relevant and can be personalized by any business [Source]. At present, an entrepreneur is capable of personalizing his or her inventions with a specific market demographic in mind from the trends gathered by the marketing algorithm applications. Machine learning has also made it possible for entrepreneurs to know what their target markets want, thereby sharpening focus to meet these specific needs.

Machine Learning and Lightening Workloads

Machine learning tools have improved on the performance of human beings through the integration of cognitive abilities to artificial intelligence kits. Machines have replaced most of the time-consuming tasks that require expensive and frequent adjustments to human skills. For instance, advancements in robotic research have displaced great potentials that cannot be ignored by business leaders. In the healthcare provision environment, robotics technology has advanced the methods of managing sensitive records, analysis of X-rays, laser surgery, and cancer therapy. Before advancements in artificial intelligence, most of these activities relied on human cognitive abilities that were inconsistent and difficult to reproduce in different environments.

Moreover, processing large data sets requires the integration of artificial intelligence tools. Across the globe, business leaders have incorporated these applications to ensure that more accurate machine learning applications complement the cognitive abilities of their workforces. For example, CitiBank uses artificial intelligence data mining software to track its past financial transaction records. Without these tools, the bank would need more than 400,000 man-hours to execute this activity (Cole 2015).

Machine Learning and Multitasking

Business optimization and profitability are directly proportional to the level of activities in place. Irrespective of the size of a business, it is significant to employ different diversification tools while managing all the operations from a centralized location. Machine learning comes in handy in creating an effective and replicable multitasking tool kit for an optimal outcome. For instance, machine learning activities have created a set of easy to use management tools that facilitate multitasking. At present, especially from a management perspective, it is possible to have a virtual office that is capable of running several real offices, irrespective of the number of business interests of an entity. For example, global shipping companies such as MAERSK rely on artificial intelligence tools that are capable of tracking and handling different activities concurrently (Obeidat, Masadeh & Abdallah 2014). Therefore, an entrepreneur might borrow from these successes to establish a similar management toolkit for an optimal outcome.

Machine Learning and Innovation

Machine learning is the drive behind major innovations in the business environment. Over the years, improvements in the scope of artificial intelligence have created a new set of advanced applications that steer the innovative business environment. Business leaders have been at the forefront in modifying previous innovative ideas into more efficient and global solutions to the current challenges facing mankind. For instance, in an attempt to fight global warming, several artificial intelligence tools have been put in place to track and proactively record the progress of each initiative (Vecchi & Brennan 2014). As a result, entrepreneurs have tons of ideas from these initiatives to create different soft products for the global market. For example, carbon print, biodegradable products, and greenbelt movement are some of the entrepreneurial activities catalyzed by artificial intelligence.

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