As the world slowly transitions to a post-covid landscape, organizations are looking at what the “new normal” is shaping up to be.
AI technologies gained immediate traction earlier this year and continue to fascinate businesses considering how and when to use its innovative solutions and platforms. Behind AI, however, is the workhorse that must be attended to behind the scenes—databases and associated data environments.
Data needs to be secure, highly available, and viable for AI and other advanced initiatives to succeed within enterprises.
According to a recent report by Research and Markets, the global big data and business analytics market in 2022 was valued at $294.16 billion. The market value is anticipated to grow to $662.63 billion by 2028.
The market value is expected to increase at a CAGR of 14.48% during the forecast period of 2023–2028, with the software segment being the dominant component.
According to the report, AI and machine learning (ML) are proving to be essential instruments in keeping control over the increasing amounts of data and enabling real-time execution. As much as AI is transforming the landscape, several risks impact widespread adoption. According to Gartner, the growing use of AI has exposed companies to new concerns such as ethical risks, poisoning of training data, or fraud detection circumvention, all of which must be mitigated. Managing AI risks is not only about being compliant with regulations. Effective AI governance and responsible AI practices are also critical in building trust among stakeholders and catalyzing AI adoption and use.
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