In the evolving realm of Environmental, Social, and Governance (ESG) concerns, offering precise, truthful, and authorised responses holds significant sway over both a company’s reputation and its financial health. The integration of AI systems that can leverage large data sources positions them as invaluable time-saving tools. However, similar to any other tool, AI necessitates human expertise to function optimally: crafting high-quality prompts is vital for achieving peak performance. Herein, we outline a series of strategies designed to guide you in maximising your AI uses, ensuring that they contribute effectively to your organisation’s ESG objectives.
1. Define a Clear Objective
When formulating instructions for AI systems, it’s essential to articulate your goals with clarity, a task that holds particular importance within the diverse and expansive ESG landscape. A firm grasp of your objectives when interacting with AI will lay the groundwork for successful outcomes, as it establishes a framework within which AI can operate most effectively.
- Weak prompt: What are Scope 3 emissions?
- Strong prompt: What are the specific Scope 3 emissions in the year 2023?
Understanding your objective ensures a well-defined context, thereby enabling AI to more efficiently filter through vast arrays of information and deliver the most relevant and accurate results possible. This process is integral to obtaining high-quality insights that can drive strategic decision-making.
2. Specify Desired Outputs
The nature of information requests can differ extensively, necessitating clear directives regarding the intended audience, the preferred language, and the format of responses. Establishing these parameters is crucial as it ensures that the outputs generated by AI align precisely with your expectations and the specific needs of your organisation.
- Weak prompt: What are the Scope 3 emissions in the year 2023?
- Strong prompt: Provide an executive-level summary of the Scope 3 emissions for the year 2023?
By specifying the desired outputs with precision, you enhance the effectiveness of AI-powered analyses, ensuring that the results are not only informative but also actionable. This form of structured inquiry is essential when preparing data presentations or strategic overviews for stakeholders.
3. Break Down Complex Queries and Use Iteration
ESG issues often possess layers of complexity and show variability across different company-specific metrics. Correspondingly, AI systems encounter limitations when tasked with processing extensive volumes of information while preserving quality. Therefore, segmenting large-scale queries into manageable components is recommended to achieve superior results.
- Weak prompt: Provide an executive-level summary of the Scope 3 emissions for the year 2023 focusing on Category 1, 7, and 13, outlining improvements that can be made to ensure the company reaches its net-zero goals.
- Strong prompt: Provide an executive-level summary of the Scope 3 emissions for the year 2023.
- Follow up: Concentrate this summary on the detailed reporting framework, particularly focusing on Categories 1, 7, and 13 of Scope 3.
- Follow up: Identify opportunities for improvement that the company can pursue in these categories to effectively meet their ambitious net-zero targets.
By adopting a methodical approach to breaking down queries, you can leverage AI’s capabilities for refined, insightful, and comprehensive analysis, essential for strategic planning in ESG domains.
In the realm of AI-enhanced ESG reporting, clarity is essential. By formulating clear prompts, businesses can leverage the time-saving abilities of AI while providing insights that are precise, informative, and fully data-driven, meeting the high standards required in the ESG sector. To maximise this time-saving benefit using EA’s Scratchpad you’re able to:
- Search unlimited evidence sources.
- Force the AI to use only company information by controlling knowledgebase access.
- Send answers for review and approval within the application
- Use approved responses to generate future answers in your company’s approved tone and language.
EA effectively minimises the need for manual input on repetitive tasks by continuously learning and integrating your business’s data into responses. This optimises your ESG processes and frees up time for more strategic, data-driven decision-making.