Generative AI is omnipresent as business leaders across the globe are evaluating GenAI's prowess to help them gain operational efficiencies and cater to customers effectively. GenAI depends on a large volume of data sets incorporating third-party data, complex algorithms, and neural network architecture to create content; the risks associated with data privacy and security are real and need to be addressed.  With so much uncertainty about the risks associated with using Generative AI, there is a need to think about the risks and proactively create a strategy to mitigate these risks successfully. In the current scenario, businesses are giving GenAI access to their business information user information and allowing GenAI to access their document management systems and a lot more to avail the benefit of AI to automate their processes and optimize efficiency. Therefore, having the right strategy in place can help businesses to avert the risks associated with GenAI smartly.

How to Manage Risks Associated with GenAI Proactively

Generative AI is undoubtedly one of the most potent tools in current times, as it has played a crucial role in creating robust results ranging from content creation to data analytics. The way businesses are allowing the usage of GenAI into their workflows, it is imperative to bring out the practices that a company can use to avoid risks associated with GenAI. So, let's get started with it.

  1. Bring an Artificial Intelligence Policy into the Organization: If you already have implemented GenAI into your processes or are still in the consideration phase, it is essential to chalk out the Artificial Intelligence usage policy in the entire organization. It will help strategize the departments, processes, and roles utilizing AI. Moreover, setting the regulations regarding which business data will be shared with GenAI and which particular workflows will be automated using AI models enables the teams to work with predetermined regulations. The leadership also knows what kind of behavior to monitor and rectify to gain a better understanding and utilization of GenAI in business processes.
  2. Employees' Training to Utilize AI Models: Having a set policy for AI usage doesn't ensure that all employees know the rules and use them as the foundation for AI usage. Therefore, setting up regular training sessions for employees is crucial and would guide them to use AI by complying with policy regulations. Moreover, those departments that deal with sensitive business and customer information should be regularly trained to avoid hefty errors. Employees should know how to optimize GenAI tools and enhance their understanding of the optimal utilization of GenAI with the capability to detect deep fakes, hallucinations, and misleading information. 
  3. Availability of Cybersecurity Tools: It is essential to recognize that AI tools and GenAI models must be utilized with cybersecurity protections to monitor all data ingested and sent out. As most GenAI models don't have inbuilt security infrastructure, organizations aiming to utilize these models must have their network security tools to counter attacks via GenAI models. Some of these tools incorporate threat intelligence, data encryption, and data security tools, penetration testing, identity and access management, cloud security posture management, to name a few. It would help businesses to stay vigilant about cyber threats and proactively handle any possible threats with precision.
  4. Having the Quality Assurance Analyst Team: Companies that are planning to invest in GenAI at the broader level must have a quality assurance analyst to ensure that the GenAI models and the data on which they are trained are fully secure, and if any issue is detected in input or output data, it is immediately taken care of. In addition, they monitor unusual behavioral patterns in AI models and APIs,  including documentation of behavioral anomalies of models and working coherently with cybersecurity and data science professionals to optimize the safe usage of GenAI.

Conclusion

To sum up, businesses that intend to leverage GenAI's potential to streamline their operations need to mitigate the risks associated with using the technology. Reaching the benefits of GenAI without resorting to the best practices to mitigate those risks successfully is challenging. Therefore, by following the above recommendations, businesses across industries can optimize GenAI, and those without robust security infrastructure can seek the expertise and potential of an IT partner that can help companies unleash the full potential of GenAI backed with all security parameters.