Machine Learning, an essential subset of artificial intelligence, is undoubtedly an advanced technological innovation, providing systems the ability to learn automatically. Forward-looking organizations already capitalize on the potential of this technology to transform business and society. Effectively implementing ML models can give enterprises strategic new opportunities. Companies can integrate these models into a wide range of business processes such as operations, customer service, prediction, and decision-making, in scalable and adaptable ways.
In an IDG’s Digital Business Study, 78% of IT and business leaders have already deployed machine learning technologies as part of their digital business strategy. The technology is able to assess voluminous amounts of data to derive meaningful and actionable insights. It can also provide business leaders with new ways to innovate, generate new revenue streams, enhance operational efficiencies, and assist employees to make faster and more informed decisions.
Unlocking Business Value with Machine Learning
Significantly, leveraging machine learning enables organizations to perform tasks on a scale and scope that were previously impossible to accomplish. In turn, it expedites the speed of work, lessens errors and enhances accuracy, while helping employees and customers alike. Today, companies striving to drive innovation are exploring ways to employ machine learning to not just deliver efficiencies and drive improvements but to strengthen new business opportunities in order to remain relevant and resilient in the modern highly-competitive marketplace.
Since machine learning has come a long way from being aspirational technology to the mainstream one, it is advancing almost every business function and process automation by enabling operational adaptation based on changing scenarios. The technology is particularly effective in finding insights from big datasets. Companies seek to uncover information from their datasets that are large in size, diverse in nature and fast-changing can deploy machine learning models.
Businesses nowadays increasingly make use of IoT devices or sensors that produce a massive amount of data. Using machine learning along with big data technologies to extract insight can help improve productivity and efficiency. With its combined techniques of supervised and unsupervised learning, ML models can also be used to analyze potential customer churn across data from manifold sources such as transactions, texts, social media, and CRM sources.
Developing the Intelligent Enterprise
Today, businesses seek to drive a successful digital transformation journey to drive a smart, intelligent enterprise. It is a strategic approach for enabling the rapid transformation of data into actionable insight. Typically, the intelligent enterprise integrates emerging technologies such as artificial intelligence, machine learning, IoT, and data analytics that help employees to focus on higher-value outcomes.
To build the next phase of intelligent enterprise, leaders must prioritize bringing the right talent at the same table and implement the right technology infrastructure. AI and machine learning already offer innovative ways to reinvigorate productivity, close skill gaps and drive organizational change by enhancing business administrations’ ability to take the right actions when things go wrong. Implementing machine intelligence can also assist business leaders to drive effective decision making and help build intelligent enterprise.
The intelligent enterprise enables leaders to achieve breakthrough outcomes as it redefines the end-to-end customer experience, delivers a step-change in productivity, transforms workforce engagement, and more. The enterprise then processes a cluster of data, prioritizing items according to pertinence, which helps in easing information surplus from leaders reviewing the reports. This innovation strategy also visualizes AI and machine learning systems across every department and business function within an organization so that each operation can be optimized with intelligent systems that provide decision support to employees.
Pervasive Machine Learning
Machine learning today has become a ubiquitous technology. From voice assistants to autonomous driving and more, applications of machine learning can be found everywhere. Almost every business across diverse industries use this technique for big economic gains. The healthcare sector, for instance, leverage machine learning to better inform decision making that could generate much value based on optimized innovation, improved efficiency of clinical trials and the development of various new tools for medical personal, insurers as well as consumers.
On the other hand, manufacturers use this technology to spot defects and address them instantly, maintaining the quality of production. In the financial services industry, machine learning helps to offer personalized services to customers at rational cost, better compliance and enables financial institutions to generate greater ROI.
In a nutshell, to get most from their businesses, leaders must realize the potentials of machine learning. They must make use of tools and techniques available out there to get started with this technology and drive innovation and business excellence.