Manual data entry involves putting large volumes of data into systems, which can be labor-intensive and prone to errors. However, the field of artificial intelligence has transformed this practice. Humans can get burnt out from repetitive and monotonous work, but machines won’t. Businesses can save money and focus on value-added tasks using AI to process their documents.
As a business grows, so does the amount of data that needs to be processed. It is where manual data entry can be particularly problematic. Slow data processing can impact the ability of businesses to make decisions, ship products or deliver services, and even generate financial reporting. Human errors can also be costly for a business. Those errors can include typos, improper formatting, or missing information affecting reports and documents’ accuracy. Using AI tools like People.ai to perform data entry and collection can save time by eliminating the need for manual, error-prone processes.
Another benefit of automating manual data entry is consistency. Having multiple people work on the same project can result in different methods and standards for input, making it difficult to get accurate results. A centralized AI-powered platform can ensure consistency across all projects and eliminate wasted time. It can also help avoid expensive mistakes, such as when unauthorized individuals misplace or access physical documents containing sensitive customer information.
Manual data entry involves human operators inputting information into digital systems, usually from physical documents like paper invoices. It’s a process that’s labor-intensive and susceptible to errors. For example, a retail business that relies on manual data entry to update inventory levels may end up overselling a product or delaying a marketing campaign because of insufficient stock. This type of error can lead to frustrated customers and significant revenue loss.
Another area for improvement with manual data entry is consistent formatting. For instance, a company with offices worldwide might use different formats to record dates — for example, the US office might follow MM/DD/YYYY. In contrast, the UK uses DD/MM/YYYY. It can be problematic because it lacks consistency, which may hamper analytics and reporting capabilities.
As AI becomes increasingly prevalent in businesses, the need to streamline and automate manual processes becomes increasingly important. The emergence of intelligent document processing (IDP) solutions is paving the way for this transformation. The technology transforms information from physical documents into structured digital data, allowing employees to focus on more valuable work.
Data entry processes often involve sensitive information. As such, security is paramount for any company that wants to protect its customers’ data. A robust security plan might include uniformed sentinels, covert and overt camera systems, security audits, etc. However, another aspect of security is equally essential: data integrity. It is where AI can come in handy, as it can help ensure data inputs are consistent and do not introduce any vulnerabilities. For example, when multiple individuals do manual data entry, each clerk might have different methods or standards for entering data. It can lead to inconsistencies, opening up vulnerabilities that malicious actors can exploit.
With AI automating high-volume, repetitive data tasks, organizations can reduce errors in critical areas such as customer data, employee records, research reports, and confidential business information. It helps them save time and money while enabling workers to focus on higher-level strategic initiatives to improve overall business performance. It is what we mean by redefining accuracy, efficiency, and productivity in the age of AI.
Automated Data Extraction
Using AI to automate data entry and collection, you can eliminate tedious tasks that detract from employee productivity. You can also improve data accuracy, which enables your organization to make more informed decisions. However, a complete switch to automation is only possible sometimes. Adding automation technology to existing manual processes requires a comprehensive analysis of the current workflow, including identifying the type of documents that need to be processed and their formats.
AI data entry solutions use Optical Character Recognition (OCR) to convert images into machine-readable text and follow hard-coded rules customized for different document types. It enables them to identify patterns and recognize specific fields in the documents. Once the documents are processed, they can be compared to previously extracted information to identify changes. It helps the system avoid duplicate or incorrect data and reduces the risk of human error.
It allows for better data quality and compliance with regulatory standards. Advanced functionalities can also enable users to filter, aggregate, cleanse, and sort the data according to specific business requirements. It enables them to extract data more efficiently and reveal additional value from the datasets.
Manual data entry is a time-consuming process, often the bottleneck to other business processes, such as decision-making, product shipments, and financial reporting. In addition, data processing delays can result in lost revenue and missed opportunities. Even the most diligent human data entry operators can make mistakes when transcribing information from one format to another. Typos, misinterpretations, and oversights can add significant time-wasting reworking errors.
Using AI to replace manually-driven work, like interpreting data from PDF documents, improves productivity and eliminates the need for costly employee overtime or hiring additional employees. Additionally, disengaged employees are risky for businesses – replacing mundane tasks with AI allows them to focus on more meaningful work that enables higher levels of productivity, which increases engagement and job satisfaction.