The perils of AI in KM also received considerable notice in the survey. Timely access to information, while remaining elusive, also raises the question of accuracy. It doesn’t help anyone if the puzzle piece that is closest to hand while working that jigsaw puzzle is actually one from a different puzzle and doesn’t fit the one you’re working on. The risks of AI returning incorrect information are recognized by survey respondents as a serious concern. Identified by them as significant risks were lost revenue, safety issues, poor decision, and putting the business at a competitive disadvantage.
The survey found that a quarter of companies surveyed had banned or restricted use of publicly available tools or platforms. Whether this is a trend that will continue is unknown. More likely is that enterprises will find workarounds, with AI that is reliant on known data stored internally rather than the vast expanse of information floating around the free web. Although that was not specifically addressed in the survey, the number of employee and contractor workforce using enterprise-provided AI was revealed to be relatively low, something that will probably climb as time goes on.
When asked what still needs to happen for full implementation, survey respondents put governance at the top of their lists, followed by having the right technology, data quality, appropriate business use cases, training, identifying data and content, evaluating internal capabilities, and hiring the right talent.
Overall, the survey reveals both excitement and trepidation around enterprise AI adoption for knowledge management. Long-standing problems around information access, data quality, and speedy acquisition of needed information are the puzzle pieces that AI has the potential to solve.
See the Survey HERE.