What Impact Is AI Having on Impact Investing?

Artificial Intelligence, or “AI,” is gradually weaving its way into many aspects of our lives. The other day, for example, I received a peculiar cover letter from a student who had applied for an internship. Something was distinctly odd about how it read: the flow was incoherent and much of the content was, frankly, gibberish. When asked, the student was brave enough to confess that he had used ChatGPT to generate the letter, but then launched into a spirited defense of its use. AI is a technology that will make our lives easier and more productive, he argued. I would tend to agree. If you can use AI to save time on a first draft, why not? Just be sure to put it in your own words. A few additional prompts, or some good old-fashioned editing, and I probably never would have known the difference, but a cover letter that was clearly generated by a computer, in my view, defeats the purpose.

Over the past several years, we have seen how microfinance institutions and “fin-techs” have harnessed machine learning to analyze customer data and automate credit decision-making. This has helped to lower the cost and improve the accuracy of lending across the developing world. Whether this will ultimately result in lower interest rates on microloans, or some form of risk-based pricing (as my previous blog post asked) remains an open question. But what is clear is that technology continues to disrupt the microfinance business model. In addition to credit, AI is being harnessed in other ways to serve the financial needs of the poor. As this blog reported in 2019, financial institutions such as Kaleidofin have been using AI to enable low-income customers to save, invest and insure against risk.

AI is showing up in other aspects of impact investing. In the area of impact monitoring and management there are some emerging service providers that are using AI to help companies formulate their impact story to potential investors and stakeholders. Agile Impacts, for example, uses AI to translate the mission statement of a company into a tailored set of impact indicators. These metrics can then be used by the company to market itself to potential impact investors. This makes impact measurement more accessible to a company by significantly reducing the time and cost required to identify the impact metrics relevant to its business model. Agile Impacts also maps these indicators to different reporting standards, such as the UN Sustainable Development Goals, making it easier for investors to measure and monitor impact across a portfolio of companies.

Another AI enabled service provider, Impactable, is described by its founder, Catherine Griffin as, “predictive impact analytics and reporting for founders and funders.” Impactable develops impact models that enable companies to quantify (in terms of cost savings or value creation) the positive social or environmental outcomes that their product or service generates. It then uses AI to find publicly available research and data to translate these outcomes into economic dollar value. These logical impact frameworks, which are grounded in relevant, publicly available research, can help convince skeptical investors of the economic value created from a specific investment, or to forecast future impact based on a company’s expected sales. Translating the social or environmental impact a product or service generates into dollar terms enables investors to maximize both these “non-financial” returns as well as financial ones.

While attending SOCAP23, I learned about another company, Viamo, which is using AI to enable individuals in developing countries who are “digitally disconnected” to access the internet. While the internet has made our lives more productive and efficient, approximately one-third of the world’s population still does not have access to it according to Viamo, creating barriers to other basic services such as healthcare. Even in countries where mobile data networks are available, an estimated 600 million people still use “feature phones,” which are cost effective but are not internet enabled (not “smart” phones). Viamo’s AI enabled platform allows individuals with feature phones to verbally ask questions to access the internet, turning the question into a search request and then using text-to-voice technology to deliver back the search results. Since the platform is voice enabled, it can be used by people with low levels of literacy, further democratizing access to information.

These are just a few examples of how AI is changing the impact investing landscape. If you have other examples of how AI is disrupting the impact investing space, or enabling new and improved social enterprise business models, please send me a message using the contact form, or leave a comment below.

We are witnessing just the tip of the iceberg in terms of AI’s potential, and while I am not against using generative AI (I have used Dall-E, for example, to create the images used in this and other blog posts) I am concerned that chatbots will not respect the Creative Commons License under which my blog is made available. Under this license, the content of this blog is made freely available to anyone, provided the material is used with appropriate attribution and not used for commercial purposes. I have taken some measures to prevent generative AI from scraping my content without attribution, but technology experts tell me there is no fool-proof way to prevent it.

Concerns aside, I will continue to publish freely, but I cannot guarantee that I will not introduce additional protective measures, such as a registration wall, in the future. One thing I can guarantee though is I will never use generative AI to draft content for this blog, not even a first draft.