5 Concerns About Using Generative AI at Work

The emergence of generative AI (GenAI) has ushered a new era of adoption for artificial intelligence as organizations reap the benefits of incorporating the technology in numerous ways. A recent report by McKinsey & Company notes that GenAI could add from $2.6 trillion to $4.4 trillion annually to the global economy, spread across 63 business use cases.

Generative AI, though promising, is not without its flaws and risks. Many concerns revolve around security and ethical implications. The technology's ability to create highly realistic imagery, videos and written material could be used for malicious purposes, such as deepfakes or misinformation campaigns, posing threats to privacy, exploiting security vulnerabilities, and more.

Here are what organizations should consider when onboarding any generative AI tool:

Access to GenAI is a double-edged sword. While it empowers individuals to create content and perform tasks requiring specialized skills, this accessibility also raises security concerns.

For example, imagine a software developer using GenAI to check proprietary code. Not all AI chat platforms are considered secure and posting code into a chat could result in a data leak.

This highlights the need for stringent policies governing AI-powered tools. Without proper guidelines, there's a risk of inadvertently exposing confidential data and vulnerabilities of organizational systems to malicious actors.

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Bad actors are adept at using personal information to their advantage, and GenAI provides them with a new avenue for gathering data on prospective targets. Potentially, bad actors could employ GenAI tools to devise social engineering techniques to manipulate and deceive targets or exploit them for malicious purposes, such as generating fake reviews, impersonating individuals, or creating fraudulent documents. This could lead to identity theft, unauthorized system access, and other malicious activities.

Hackers could potentially turn GenAI's capabilities against organizations through phishing attacks. Malicious actors might manipulate GenAI systems to generate convincing phishing messages undistinguishable from legitimate communications. This highlights the importance of staying ahead of ethical hacking techniques to identify and address vulnerabilities before they can be exploited.

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As GenAI becomes more integrated into various aspects of an organization's operations, ethical considerations become paramount.

GenAI models learn from large datasets, and if these datasets contain biased or discriminatory information, the AI can replicate and amplify those biases in its output. Proper guardrails and QA processes must be enacted to curate outputs from GenAI or at a minimum notify the user of potential pitfalls.

Organizations must be cautious about the data they feed into these models and ensure they have proper consent and mechanisms in place to protect user privacy. Mishandling sensitive data could lead to breaches, leaks, and violations of privacy regulations. Generative AI models are often considered "black boxes" because their decision-making processes are obscured or hard to understand. This lack of transparency can be problematic, especially in highly regulated industries like healthcare or finance.

Organizations must ensure the use of GenAI aligns with ethical standards and doesn't compromise user privacy or security. Striking a balance between innovation and responsible AI usage is crucial.

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The implementation of GenAI in certain tasks, such as content generation, could raise concerns about job displacement. However, in fields like software development, where there's already a shortage of skilled workers, GenAI can actually augment human capabilities and alleviate shortages by enabling developers to work more efficiently.

The World Economic Forum (WEF) predicts this surge in AI adoption will lead to increased demand for machine learning specialists, information security analysts, data scientists and others. While some jobs are at risk, this technology also stands to add millions of new jobs.

GenAI-generated content isn't immune to issues such as repetition, language style inconsistencies, copyright infringement and even blatant errors (also known as “hallucinations”).

To harness the full potential of GenAI, users need to provide clear and specific prompts. Proper prompt engineering is a skill that organizations and individuals need to develop to ensure desired outcomes.

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The integration of AI tools like GenAI will likely reshape job roles and skill requirements across industries. Professionals will need to adapt to these changes by enhancing their skills in strategic thinking, problem solving, and utilizing GenAI as a capability enhancing tool.

While GenAI presents exciting opportunities for organizations, it also brings challenges that need to be carefully navigated. By staying informed about the potential risks and benefits, organizations can make informed decisions about how to leverage GenAI tools effectively while safeguarding their security, ethics, and overall mission.

The key lies in fostering a culture of responsible GenAI adoption and continuous learning to harness the full potential of this transformative technology. By engaging with Skillsoft, your organization can make informed decisions on how to best use GenAI.

See our 90-day training roadmap to find new training on ChatGPT and generative AI, and to see what else is on the horizon.

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