How AI Can Help Do the Grunt Work

AI is improving data management and easing workloads behind the scenes

Artificial intelligence has been applied successfully in thousands of ways, but one of the less visible and less dramatic ones is in improving data management.

  • Classification: Broadly encompasses obtaining, extracting, and structuring data from documents, photos, handwriting, and other media.
  • Cataloging: Helping to locate data.
  • Quality: Reducing errors in the data.
  • Security: Keeping data safe from bad actors and making sure it’s used in accordance with relevant laws, policies, and customs.
  • Data integration: Helping to build “master lists” of data, including by merging lists.

1: Classification

Newer AI systems have expanded on OCR with deep learning models that are now becoming capable of accurately reading human handwriting.

2: Cataloging

3: Quality

Importantly, vendors could improve their tools if they supported a more proactive approach to data quality management — one that focused on preventing data errors rather than finding and fixing them.

4: Security

AI can also be used to identify internal threats of fraud or noncompliance with regulations.

5: Data Integration

Combining and mastering data across a large organization has historically been an enormous task requiring years of effort.

The Vendor Environment for AI and Data

What AI Can’t Do — and Where Humans Matter Most

Overall, good data still requires good managers who care about data, view it as an important asset, and establish a management system that treats it as such.

  • Creating a data strategy and deciding which data is most important to a business.
  • Creating a data-driven culture.
  • Calibrating sensors or equipment.
  • Developing data governance policies and structures.
  • Defining key business terms or putting a common language in place.
  • Establishing whether an organization is using the right data or the wrong data to solve a problem.
  • Recommending where an organization should store or process its data.
  • Punishing anyone for cybersecurity violations or data-related fraud.



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