Speed, efficiency, and accuracy: How AI is supercharging critical document analysis

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Historically, the implementation of technologies in the analysis of confidential or private data has been slow, mainly due to limited digitalisation and reluctance to trust computer systems to manage sensitive information. Technology is often seen as an adversary or a risk, with teams preferring manual methods because they are considered more secure and controllable, despite being less efficient. However, increasing pressure to improve efficiency and comply with regulations is driving the adoption of artificial intelligence (AI) to handle large volumes of data more effectively.

“The challenges faced by companies across all sectors are mainly the same,” says Alfonso Ibá?ez, Head of Artificial Intelligence & Analytics Technology at Telefonica Tech. “In financial or healthcare companies, regulations are complex, and obligations are greater. In the industrial sector, intellectual property and trade secrets come into play. The main challenge for any team dealing with critical documents in these sectors is the workload and tight deadlines. This dual pressure often results in less time being spent on reviews than would be ideal, or in delays that go far beyond what is desired.”

The matter of data confidentiality is critical, especially in these sectors, necessitating the use of special measures for information handling, which further increases the workload and need for resources.

“If we focus on the healthcare sector, for example, medical data is considered especially sensitive, and applicable regulations require the implementation of special measures for its processing,” says Alfonso. “Any information breach in this area poses a significant risk for companies as they may face substantial fines and a loss of trust from their stakeholders, which are often penalised with severe sanctions.”

But it doesn’t need to be that way.

Beyond the boundary

Advances in technology are paving the way for a revolutionised approach to critical document analysis, one that can provide cost-optimisation, streamlined resources, and a reduction in errors. The advent of AI in this field is transforming the document analysis process, providing an efficient, and increasingly accurate alternative to manual analysis. Using a combination of advanced algorithms, natural language processing (NLP), and machine learning (ML), AI can quickly analyse text and extract important information.

One of the most prominent benefits of AI in critical document analysis is its ability to process vast amounts of information much faster than humans. AI can perform tasks in a matter of seconds, which would otherwise take weeks if done manually. This capability allows staff to allocate more time to complex tasks and strategic decisions rather than tedious document reviews.