Heavy hitting AI technology makes light work of data discovery

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Heavy hitting AI technology makes light work of data discovery  

-Jon Horden, CEO, iKVA, a Cambridge-based AI-enabled knowledge management software solutions company 

 

Cambridge is well recognised as a UK business hub, fostering a culture of growth across areas including technology, science and manufacturing; the most significant growth being in knowledge-intensive companies in the science and technology sectors. In fact, knowledge-intensive companies accounted for 28% of employment (68,000 people) and 38% of the total turnover (£18bn) in Cambridge in 2020 

 

One of the challenges facing these organisations, and indeed any large company, is the volume of data being generated on a daily basis, which they are unable to utilise without embarking on costly, labour-intensive processes. The amount of information is increasing rapidly and is in different formats and repositories, which may not even have search interfaces, making it difficult to access. Today, the average highly skilled and professional worker spends nearly 20 percent of their time searching for information in order to do their job, and inform business decisions.   

 

Solving the problem of having to access multiple systems, using a variety of queries, or not being able to access information at all, can result in high productivity increases and cost savings as well as significantly reducing business risk and increasing compliance. Reducing time spent looking for information by just 10 percent could result in a $2m/year saving for an average medium to large sized business. With research showing that nearly a quarter of UK businesses will adopt Artificial Intelligence (AI) technology by 2025, AI technology should be at the top of the agenda for any firm which wants to discover previously inaccessible data and transform this into insights to inform, and improve, their business.  

 

The trend for remote working has resulted in decision makers using MS Teams, Zoom and other platforms to communicate, hold meetings, and make decisions. Accessing knowledge created in MS Teams, for example, is challenging, especially since one meeting can cover multiple topics and multiple clients. All of these tools – iManage, email, MS Teams, Sharepoint – have different search interfaces which require multiple and repeated searches to find information. AI technology can overcome this by bringing all of these sources of information together in one place, indexing and segmenting the knowledge created, and allowing this to be discoverable. This provides for better and more accurate results and means that decision sources can be quickly and easily identified, increasing business compliance and helping to reduce business risk. 

 

Traditional search methods also require significant amounts of human time and labour to interpret, label and rank data, ready for inclusion in the search database, resources that could be deployed elsewhere in the business. It is impossible to pre-empt every keyword and synonym that may be used and documents will require multiple labels to prepare for all eventualities that cannot be pre-empted. This leads to irrelevant returns when using traditional search methods. Using AI-enabled technology allows a richer input of information as a query, including dragging and dropping full documents into the insight engine – which means results are more accurate, relevant and refined. This is particularly useful where there are potentially thousands of different results per keyword. The context enabled by AI data discovery refines the returned results to a manageable number that can easily be reviewed and utilised to avoid a loss of productivity.   

 

With a wealth of information archives worldwide, the data available to today’s organisations is almost limitless. However, accessing this,– especially when the information is in another language, can be difficult and time and money must be spent on translation services to understand the result, let alone apply it to the query in hand. Natural Language Processing (NLP) combined with Neural Networks and deep learning models enable computers to understand the full meaning of information including sentiment and intent without the need for translation. Using advanced language agnostic AI tools such as those developed by iKVA enable individuals to discover relevant information regardless of the language it was created in, which is particularly useful given the number of international organisations which are based in the city but operate globally – with teams in multiple countries, working in many different languages.  

 

All sectors will benefit from integrating AI technology into digital transformation strategies, to unlock insight and reduce business risk. To find out more about iKVA’s AI enabled knowledge management software solutions, or to book a demonstration, please, click here

Read the article online in Business Weekly

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