The author suggests using language model libraries (LLMs) as managed services within cloud platforms like Azure, AWS, or GCP to secure applications built on them. For custom training of LLMs on-premises, OpenAI and Google's LLMs are recommended. Testing prompts in simulation environments, leveraging in-context learning methodologies, and mastering advanced prompting techniques can improve the outcomes. The author concludes that the combination of auditor expertise and GenAI can set new benchmarks in ESG audits, provided there are solid risk management and governance practices in place.
Key takeaways:
- Generative AI (GenAI) can streamline the ESG audit process by automating complex information-mining processes, enhancing efficiency in stakeholder management, and improving audit assessment quality.
- GenAI does come with challenges such as hallucination risk, implementation issues, regulatory concerns, and data security.
- Successful implementation of GenAI into the ESG audit process can be achieved by employing LLMs as managed services within cloud platforms, using simulation environments to test prompts, and mastering advanced prompting techniques.
- The convergence of auditor expertise and generative AI can create new benchmarks in ESG audits, enhancing efficiencies, making more intelligent decisions and nurturing a resilient, data-driven audit ecosystem.