Blog Posts

Donors often provide support to nonprofits in a way that responds to contemporary issues and the donor’s particular interests. Examples include a prohibition on spending principal or a requirement that the fund be used only for a specified program or within a given geographical area. Over time, such restrictions can make full use of the funds impracticable or impossible.

The fields of accounting and finance are undergoing a transformation driven by the rapid advancements in automation and artificial intelligence (AI). These technologies are not only streamlining processes and increasing efficiencies but also enabling business to gain deeper insights and engage in more strategic informed decision-making. But what does it all mean and how can it change the way we work? Let’s explore the current landscape of automation and AI in accounting and finance: the benefits, applications, and key challenges or considerations.

With a tight job market, declines in giving, and inflationary pressures, 2024 presents concerns for nonprofit CFOs. In a Forbes article featuring a survey on top risks, CFOs highlighted talent, economic uncertainty, and cyber as top risks. Nonprofit leaders are embracing these 4 strategies to mitigate enterprise risk.

My brilliant friend and nonprofit colleague Abigail Jarvis recently took to LinkedIn to tell nonprofits something remarkable: “You probably don’t need to worry about your email unsubscribe rate in 2024.” This isn’t the kind of message nonprofit pros tend to hear. There’s something that isn’t on fire?

Is your organization prepared to accept stock and mutual fund gifts? Donations of appreciated securities the donor has held for a year or more are generally more beneficial than cash donations for both the charity and the donor.

Lately, it seems, all we hear about is AI, or Artificial Intelligence. It’s as if AI is an entirely new business tool. In fact, machine learning, a building block to Generative AI such as the now familiar ChatGPT, has been around since 1958 with the advent of the neural network, designed to teach computers to process data similar to the human brain.