For businesses to successfully implement AI , high-quality data is essential . With the success of generative AI ( Gen AI ) being built on data , organisations implementing Gen AI initiatives need to ensure that it is unbiased and secure . To succeed in this , businesses can benefit from investing in data management solutions to improve the quality of their data .
This month , we speak with Gaurav Pathak , Vice President of Product Management at Informatica , about how Informatica is moving towards ethical AI and what businesses can do to achieve fast AI in a responsible way .
Q . INFORMATICA ’ S RECENT CDO SURVEY FOUND THAT THE QUALITY OF DATA IS THE TOP DATA-RELATED OBSTACLE TO IMPLEMENTING AI . WHY DO YOU THINK THIS IS THE CASE ?
» There ’ s an old IT proverb – garbage in , garbage out – or simply , you are what you eat . Just as high-performance athletes can ’ t expect podium-worthy results on a diet of chips and soda , the output of LLMs and AI solutions are directly influenced by the quality of data that nourishes them .
The reality is – at the enterprise level – everyone claims to be ready for AI , but is their data ? Hybrid , multi-cloud , multi-vendor data estates remain largely fragmented and incredibly complex , disparate , burgeoning ecosystems of structured , semi-structured and unstructured data that , according to our recent survey results , are only expected
to worsen in the months ahead due to demands from Gen AI projects .
This is death by data : a corporate paralysis that comes from organisations ’ inability to properly manage their most important asset . This lack of trust and confidence is justified , given that organisations have not focused on data quality and governance as much as they should have .
And now Gen AI is bringing new but similar requirements like identifying and correcting / removing inaccurate , incomplete , or irrelevant sections from unstructured data , removing confidential and sensitive information about customers and employees ,
18 May 2024