The Voluntary Carbon Market (VCM) has challenges to overcome if it is to rapidly scale. This necessitates providing proponents and stakeholders with the best tools to help raise the bar for consistently high quality delivery of NbS projects.

In particular, we are seeing that artificial intelligence (AI) truly can dramatically improve practitioners’ approach to planning, monitoring, and evaluating nature-based projects. Impact Inside cleverly employs AI in several ways to achieve this. Here’s how:

AI Assistant

Impact Inside features an AI Assistant that provides users with real-time guidance, answering user questions about project requirements and helping them navigate the software’s many features. Informed not only by a huge data repository containing exhaustive information about Impact Inside but also by a deep repository of third party documentation (e.g., from various standards, certifications, carbon ratings agencies, and more), this personalized support enables practitioners to quickly access the information they need to utilize the platform effectively and optimize their project(s) against the outcomes, certifications, and standards they target.

1. Automated Documentation Generation: AI helps automate the creation of essential project documentation, such as project reports and proposals. By using data from the Theory of Change and other inputs, the AI Assistant can draft various types of documents, significantly reducing time spent on administrative tasks and allowing users to focus on strategy and execution.
2. Theory of Change (ToC) Guidance: The AI Assistant provides recommendations for building and refining a ToC. It analyzes the entered data to suggest new or modified connections and identify potential issues and gaps, ensuring that project plans are robust and aligned with best practices in project design.
3. Data Collection and Integration: With built-in tools for conducting surveys and gathering field data, AI assists in analyzing and integrating this information. This capability allows organizations to track progress in real-time, detect potential problems, and to facilitate quicker decision-making and better project oversight.
4. Community Engagement Tools: AI facilitates the creation of dynamic microsites and compelling project community portals. This makes it easier to communicate project details, fostering engagement and transparency.
5. Smart Recommendations: AI analyzes user inputs to deliver tailored recommendations for project adjustments. For instance, it can suggest modifications to improve compliance with carbon credit buyer requirements, optimizing project value in the carbon market.
6. Enhanced Learning and Adaptation: AI improves its suggestions and responses over time, providing increasingly relevant support tailored to individual user needs.
7. Integrations with Advanced AI Technologies: Future integrations with technologies like OpenAI and Amazon Bedrock are being explored to enhance data management and support the provision of sophisticated AI-driven insights and resources, directly impacting project planning and execution efficiency.
   

Overall, Impact Inside does its best to make AI work hard for project proponents and stakeholders – to automate processes, provide real-time support, generate insights, and enhance communication, all of which contribute to a more efficient and effective project management experience. Whether in regard to AI or any other tech, our goal is always to use it prudently and cleverly to help well intentioned practitioners secure project funding, minimize risk and maximize crediting potential.