Unstructured data and AI: A dangerous combination for your business
Summary: Artificial intelligence (AI) is often seen as a miracle weapon for efficiency and automation, but in practice, risks and challenges quickly become apparent - especially when unstructured data comes into play. Without clear data structures and targeted data processing, however, AI becomes more of a danger than a solution: costs explode, storage is unnecessarily burdened, and compliance and security risks increase.
Why AI can become a threat without a clear data strategy
The expectations of AI are high: from faster processes to deep insights into business processes, AI is intended to leverage unused potential in the data set. But without clean data structures, the path for AI quickly becomes rocky and problematic.
A crucial point:
How do you ensure that AI systems only access the information they are actually supposed to process? In order for AI models to be used responsibly and safely, relevant data must be clearly defined and authorized to access. Otherwise, AI could access sensitive information that should not be visible to everyone - a huge compliance and security risk.
Filter relevant data: Save time, money and energy
Another problem is the massive amount of irrelevant information:
Often, unimportant or outdated data accounts for 80–95% of the data volume.
The result? AI has to scan endless amounts of data, which costs time, energy and storage space but provides only minimal added value.
timeliness and relevance: Outdated or irrelevant data leads to inaccurate results and wrong decisions. AI must learn to “forget” and only use current data.
time and costs: The excessive amount of data costs resources and drives up operating costs.
memory load: Irrelevant data takes up excessive storage in the AI database index, increasing cost and complexity.
Two key challenges on the way to safe AI use
The use of AI in companies creates two critical requirements:
- Cost efficiency through reduction of irrelevant data: A well-thought-out data strategy that clearly defines what can be “forgotten” and what information is really relevant for AI training.
- "He who asks, receives": AI must specifically filter data so that everyone only receives the content to which they are entitled in order to minimize data protection and compliance risks.
Open questions about the flood of data and the use of AI
How can unstructured data be handled? Which measures help to structure the increasing data volumes efficiently and securely? Register for the webinar on Tuesday, July 03.12.2024, 14 at 30:XNUMX p.m, and gain valuable insights from CEO Thomas Gomell and Prof. Dr. Ute Schmid, who heads the “Dare2Del” project at the University of Bamberg. Find out what the reasons are behind the constantly growing data volume, how you can get the flood of data under control and how you can use AI in a future-proof and responsible way.
>> Find out more about the expert webinar here
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