Making generative AI work: Balancing security risks with powerful use cases

Generative AI technology has the potential to be transformative for businesses, but 

Salesforce’s Generative AI in IT Survey flags up security risks that need to be addressed across industries.

The technology is proving popular, with the Salesforce survey of more than 500 senior IT leaders finding that 67% are prioritising generative AI for their operations within the next 18 months and 33% citing it as a top priority. According to the report, tech infrastructure, data strategy, security and ethical guidelines, and employee skills will all need to be “primed … for the massive opportunities ahead.” 

Awareness of the security risks is high. Of the IT leaders surveyed, 79% said they had concerns about the security risks of generative AI solutions. Additionally, 99% of respondents said their businesses need to “equip themselves [in terms of mitigating security risks] to successfully leverage the technology.”

Writing for the World Economic Forum, Dorit Dor, chief technology officer, Check Point Software Technologies, says there was a 38% increase in cyberattacks worldwide in 2022 and “we could now see an exponential rise due to generative AI models.”

Dor also points out the “great potential” of generative AI to “help the cybersecurity industry accelerate development of new protection tools and validate some aspects of secure coding.”

“By incorporating AI into a unified, multi-layered security architecture, cybersecurity solutions can provide an intelligent system that not only detects – but actively prevents – advanced cyberattacks,” Dor writes.

Rashed AlFadala, CEO of Bridge Medical GPO, a UAE-based medical procurement solutions company, says the challenges of utilising generative AI solutions “include data quality and availability, integration with existing systems, staff training and adoption, ethical considerations, and cost.” 

“While generative AI has the potential to provide significant benefits to group purchasing organisations, it is important to carefully consider the challenges and risks involved in implementing AI-powered systems and to develop a comprehensive strategy for managing these challenges,” says AlFadala.

The company is using generative AI in a range of ways, according to AlFadala: “By analysing vast amounts of data, generative AI helps Bridge Medical GPO make informed decisions about pricing, contracts and vendor selection.” 

In addition, Bridge Medical GPO uses the technology to “manage contracts and vendor relationships more efficiently by analysing contracts, identifying key terms, and automating contract renewal processes, [and] … analyse spend data more effectively by identifying patterns and anomalies in spend data, highlighting areas for cost savings, and providing data-driven insights to help make informed decisions.”

AlFadala says that one of the main business cases for generative AI technology is its usefulness in risk management functions: “AI-powered risk management tools can help businesses identify and mitigate risks in their supply chain, ensuring that they are well-prepared for any disruptions.”

Courtesy of Georgia Lewis

Image credit: Markus Spiske/Pexels

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