Generative AI Challenges in 2024

Generative AI, particularly large language models (LLMs) like ChatGPT, has become a pivotal product in artificial intelligence, significantly boosting economic productivity. McKinsey estimates that generative AI could annually contribute up to $7.9 trillion to the global economy, rivaling the combined contributions of Canada, Great Britain, Russia, and Austria.

Despite its immense potential, generative AI faces several challenges. Here are the top six problems with generative AI and some strategies to address them, ten months after the release of ChatGPT 4:

Accuracy: Generative AI, like ChatGPT, sometimes produces inaccurate or misleading responses, known as hallucinations. Enterprises can mitigate this by implementing topic and ethical guardrails and enhancing training with domain-specific knowledge bases. However, human oversight remains crucial for ensuring accuracy.

Bias: Generative AI can perpetuate biases, including political, gender, and racial biases. Enterprises must closely monitor and guide their AI to align with their corporate and human values, ensuring that diverse viewpoints are not suppressed in favor of a single perspective.

Volume: The ease of generating content with generative AI has led to an overwhelming volume of information. Enterprises need to develop strategies to manage this influx, including organizing teams and leveraging technology for data analytics and content attribution.

Cybersecurity: Generative AI has expanded the capabilities of cyber attackers, enabling them to create sophisticated attacks, such as malware and phishing schemes. Organizations should use AI for code analysis and penetration testing and prioritize cybersecurity training for staff.

Intellectual Property Issues: There are concerns about intellectual property rights related to the use of generative AI. Enterprises should ensure that humans are involved in the creation process and stay updated on evolving laws regarding copyright and patents.

Shadow AI: Many employees use generative AI tools without their organization’s approval, posing governance challenges. Organizations should establish clear policies for the responsible use of AI and educate staff about these guidelines.

Despite these challenges, generative AI offers immense potential for industries such as healthcare, banking, logistics, insurance, customer service, and e-commerce. Enterprises that effectively harness this technology will gain a significant competitive advantage. AI should be a top priority for board-level discussions to navigate this transformative shift in business operations effectively.

If you’re interested in learning more about how AI is shaping business outcomes and how to manage AI risk, stay tuned for future articles and updates.