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Data management is an exceptionally resource-intensive business process for many businesses. The costs of managing data grow quickly as businesses scale, making it extremely difficult to do so without hiring a robust data staff to handle the sheer volume of documents needed to run a mid-size or enterprise business. As a result, the demand for automation tools has exploded in recent years.
Data transformation with AI is one of the most popular paths to reducing these costs and improving scalability. With the right AI tool or data partner, businesses can scale without having to hire a single new data entry clerk or analyst.
In this quick guide, we will cover:
- How AI can transform data management processes
- Benefits of AI data transformation
- How to transform your company’s data management
Let’s dive into each to better understand how AI has changed the way tech-forward businesses handle data.
Data Transformation with AI
AI and machine learning (ML) have enabled software to automate far more than it could before, especially in ingestion workloads like data entry/capture. All of the following can be automated with AI:
- Document digitization and indexing
- Data entry
- Data organization
- Report generation
- Data security procedures
While this isn’t an exhaustive list of what AI can do for data management, these are the most common use cases that businesses leverage, since they provide the most material benefit.
Benefits of AI Data Transformation
Making such a big change doesn’t happen overnight, and it takes significant investment to transform any business process. As a result, business leaders should understand exactly how AI data transformation will benefit their team.
By utilizing AI-powered data tools, or contracting with a full-service data contractor that does, businesses will see several valuable benefits. We’ve broken up the following table into benefits that can be experienced with software alone, and those that are made available when you choose to contract with a full-service provider:
| Rapid Data Entry | Data capture automation solutions store data automatically, making data capture near-instant. As documents are scanned, their data can be stored in the proper databases immediately, without requiring a manual data entry clerk to punch anything in. |
| Consistent Data Accuracy | ML-paired OCR is more accurate than human data entry clerks, reducing mistakes and giving staff more time to audit and improve accuracy even further. |
| Indexable Handwritten/Older Documents | A unique “superpower” of ML-powered OCR technology is its ability to extract data from handwritten documents and older documents with obscured or less intact text. Your existing data team will want to audit the data extracted from these documents more closely, but it is far more accurate than it has ever been before. |
| Improved Data Security | AI-powered data security improves the consistency of applying data security best practices and provides real-time warnings about potential breaches. This helps businesses reduce outsourcing risks by ensuring that data security regulations are always complied with. |
| Unified Data Access | Full-service providers typically offer cloud-based storage and automated document indexing, making it easier to search for specific documents and even specific information across a database. |
| Scalability Without Hiring More Staff | By outsourcing to a full-service data capture team, instead of simply adopting a data entry automation platform, businesses can completely eliminate the need to hire data entry staff as they grow, making it far cheaper to scale. |
Best AI Data Transformation Deployment Strategy
Due to the massive improvement in scalability they provide, outsourcing to a third party that provides data capture automation is the best way to accomplish data transformation with AI. This gives enterprise businesses access to a cost-effective data management tool and a team that already knows how to operate it, so they can just send in scanned documents, and have their data captured and organized completely by the third party. This means that, as their business scales and data volume grows, these businesses don’t need to hire countless new data clerks to catch up.
When selecting a full-service data contractor, business leaders should seek out a partner that:
- Offers the most advanced data technology
- Provides support that aligns with their working hours regardless of where they operate
- Stores data in an easily auditable database with transparent operation
- Prioritizes data security
- Has experience working with enterprise-level businesses across multiple industries
These are the features that make a third party worth the investment and mitigate the risks associated with outsourcing. Make sure your data is not only captured and organized properly, but also kept completely secure and accessible throughout the process.
Sample Industry Application: Logistics
Logistics companies often use iTech’s services to lower their data costs and improve scalability. By allowing iTech to handle all of their invoices, purchase orders, and shipping manifests/bills of lading, logistics companies can avoid having to hire any new data staff as they expand their services and deliver more goods.
Not only does this improve scalability, but it also speeds up their backend processes significantly, reduces misinputs that can cost the company money and potentially cause serious conflict with clients, and makes it far easier to search every bit of data across all documents so that your staff can audit, answer client questions, or make more informed business decisions.
Achieve Total Data Transformation with iTech
We at iTech pride ourselves on our cutting-edge machine learning OCR software, top-of-the-line onboarding experience, and ongoing support. We also offer 24/7 access to support personnel and senior account managers to maximize visibility and peace of mind, eliminating the “black box” approach to outsourcing.
To learn more about data transformation with AI, fill out the contact form below.
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IDS Commander iTech2021
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