The nature of every industry has changed a lot with the introduction of advanced technologies. Data entry and data conversion services have supported advancement of technology in cloud adoption, big data, software defined networking, IOT (Internet of Things), virtualization, and so on. Recent reports indicate that AI and big data are driving various technological innovations and will impact the future of digital transformation. These technologies have developed rapidly over the years and will be implemented in every industry in the future. In fact, organizations need to observe and adapt to these trends to stay competitive.
To understand the role of these powerful technologies in future digital growth, we need to look more closely into what each one means.
AI is a powerful technology that allows machines to perform cognitive functions same as the way humans do. AI performs jobs that once required human intelligence to perform. An AI-enabled machine is designed to analyze and interpret data and then provide a solution to an issue based on those interpretations. With machine learning, the computer learns once how to respond to a certain result and will act in the same way in the future.
AI helps businesses make better decisions, faster by influencing forecasting tools. Entrepreneurs use predictive analytics tools to forecast customer behavior, anticipate equipment failure, and identify and choose the best product fit for customers. By paving the way for customer-centric data, predictive analysis and AI are helping businesses get ahead of competition.
Machine learning, a subset of AI, is now used various fields. Machine learning involves building machines or programs that can access data and apply algorithms to the information to get valuable insights, and then applying the information to other scenarios or new data sets. Machine learning can help detect insurance fraud, provide significant insights on consumer behavior, and detect and diagnose diseases. By analyzing large volumes of data, machine learning promotes fast and strategic decision-making. A part of machine learning, deep learning mimics the working of the human brain in processing data and creating patterns for use in decision making (www.investopedia.com).
Big data refers to the massive amounts of data that accumulate every day. Big data in key industries such as banking, healthcare, education, retail, and manufacturing is extremely varied. Big data sets include both structured and unstructured data. Structured data is that which is easily searchable such as data in spreadsheets and data from machine sensors. Unstructured data is not organized in a traditional format. Examples of unstructured data include Word documents, images, instant messages, collaboration software, documents, books, social media posts and so on. When big data is analyzed by machines, it can reveal patterns and trends, and facilitate making future predictions. Businesses utilize data entry services to convert critical business data into digital format and keep pace with the digitalization trend.
AI meets Big Data
AI and big data are becoming closely interconnected. Today, the most successful brands are those that have combined AI and Big data. The more data AI can capture, the greater the potential for disruption. In fact, AI now has capabilities to tap valuable information from big data. Successful organizations are taking advantage of this new inflow of information to take business to a whole new level.
Amazon, Alphabet, Microsoft, Netflix, Salesforce, Samsung, and Tencent are the tech giants that are leveraging AI and big data to accelerate profits. For example, Amazon collects data on the way users interact with the various elements of the site and tracks their entire journey, starting from discovering products at the start to buying products and final delivery or return of a product. AI is then used to analyze the data and refine the site to improve the experience for both buyers and sellers.
Thus, big data provides the fuel for AI.
MIT Sloan Management Review referred to this convergence of big data and Artificial Intelligence as “the single most important development that is shaping the future of how firms drive business value from their data and analytics capabilities” (www.su.org).
The key difference between big data and AI is that big data is the large volumes of raw data from various sources that can be used to learn new facts, or predict future events, and AI is the tool that is used to gain these insights from big data.
Big data needs to cleaned, structured and integrated before it becomes useful. Data entry and document scanning services have an important role to play in making data useful for the application of analytics. Scanning allows automated data capture from paper documents that contain valuable information that needs to be analyzed. For instance, mining customer mortgage files can help banks reduce risks on future mortgages, predict market trends, and even prevent fraud. Likewise, insurance companies have made use of data entry services to digitize paper policy forms so that they can be subject to analytics. Digitizing student records, patient records, and legal documents can help harness the power of data in them.
Today, more and more organizations are investing in big data and AI initiatives to increase productivity, efficiency, and performance. Business process outsourcing companies can support them in their efforts with intelligent data processing and document scanning solutions.