For a long time, businesses of all stripes have struggled with the problem of how to get reliable information that is stored (somewhere) inside the company fast. You just know it exists, but where exactly is it? The development of generative AI in recent years has showed promise in mitigating, if not totally solving, this issue. While businesses rely on AI to find detailed information, they are also cognizant of the risks associated with the technology.
This significant Pryon survey, carried out by Unisphere Research, highlights the conflict brought about by financial constraints, lack of managerial support, legacy systems, and data silos. Attempts to provide the framework for a fully informed business can occasionally appear like one of those puzzle pieces that gained so much popularity during pandemic lockdowns. They are complex, presumably made to be frustrating, difficult but not to the point where you want to smash the pieces to the ground in exasperation.
According to the survey, enterprises are aware of the dangers associated with data quality, security, privacy, accuracy, and governance even as they are enthusiastic about the potential of AI to enhance knowledge management and information access. Knowledge managers are familiar with these problems, but when AI is involved, they are being examined more closely. How well does technology handle these crucial challenges, and how much supervision and human intervention will be needed?
AI’s promises
Although it is still in its early stages of deployment, AI is top of mind for organizations, as the poll indicates. There are plans to use AI in some capacity within the upcoming year. Information retrieval and summarization from unstructured data is a significant endeavor when businesses are initially beginning to fit the puzzle pieces together. We have long known that most of the data kept by businesses is unstructured, and that end users still have difficulty finding unstructured data. People are also expecting more and more that information will be available quickly, and they are also prepared to spend less time searching for pertinent information. AI is expected to assist meet such expectations and reduce the amount of time spent frantically—and occasionally fruitlessly—looking for information. This should therefore increase output and enhance information exchange.
A genuinely informed organization is not supported by the current state of affairs, which includes numerous data silos and systems that are difficult to cross-search. There are several reasons why silos form. The company culture may be more competitive than collaborative. People may just wish to have their data in a manner they want, readily available. It could be the result of infrastructure incompatibilities. It could be a lack of communication concerning the data that departments and teams gather and keep amongst them.
When historical systems are not brought into common compliance with internal standards, mergers and acquisitions may result in several non-communicative systems. Alternatively, it is possible that they were constructed as “shadow IT” initiatives, in which a system is created without the need to notify IT. The reasons behind the creation of these rival systems and data silos might help IT personnel and knowledge managers remove them. It can also identify silos—like those related to human resources, strategy planning, and some financial areas—that have good reasons for being closed to the general public.
