Blackbaud is a software company that provides cloud-based technology, data, and AI solutions to help nonprofits, educational institutions, healthcare organizations, foundations, and other social impact organizations manage fundraising, operations, and donor engagement.
Blackbaud recently published research showing a link between technology adoption and fundraising success among social impact organizations. What opportunity do you see for AI in the sector?
Fundraising is a major part of what social impact organizations do, but it is very difficult to scale. One university we work with has around 190,000 alumni but only a handful of fundraisers, so they focus on the 6,000 to 8,000 individuals they believe present the highest opportunity. The vast majority of alumni remain untouched because organizations simply cannot hire enough people to conduct the research, outreach, and relationship-building required to engage everyone effectively.
This challenge exists across universities, charities, animal shelters, food banks, foundations, and nonprofits of every size. There is also a shortage of roughly 10,000 fundraisers each year, along with high turnover rates that create additional disruption. AI presents an opportunity to address these scalability challenges. At Blackbaud, we are embedding fully agentic AI capabilities into our fundraising solutions to help organizations reach more people and operate more effectively.
Why do nonprofits often struggle to implement AI successfully and achieve a return on investment?
The challenge is similar for both nonprofits and for-profit organizations.
AI requires a fundamentally different approach to solving business problems. Traditionally, organizations identified a problem, built a solution, and deployed it. With AI, the process is much more iterative. Teams must continuously experiment, learn, and refine solutions through rapid cycles of improvement.
AI also enables organizations to solve problems across departments and workflows in ways that were not previously possible. At the same time, the technology itself is evolving extremely quickly. Tools available today are dramatically more capable than they were just a few months ago. Organizations are still learning how to adapt, and success depends on embracing experimentation and new ways of working rather than relying on traditional implementation models.
Can you share a practical example of how Blackbaud is using agentic AI to support fundraising efforts?
Last fall, we introduced a new category of products called Agents for Good. The first solution, now generally available, is our Development Agent, a fully agentic AI fundraising assistant. It functions much like an additional fundraiser. A manager can assign thousands of prospective donors to the agent, which then learns from the organization's data, develops outreach strategies, drafts communications, and engages donors through approved channels.
The agent can send texts and emails, manage conversations, collect donations, and record transactions directly within our platform. For larger opportunities, it can escalate a donor relationship to a human fundraiser based on rules established by the organization. It effectively acts as an additional member of the fundraising team while operating within the organization's existing workflows and systems.
How significant is the untapped fundraising opportunity that these AI agents could unlock?
The opportunity is substantial. Using the university example, an institution with five fundraisers cannot realistically expand to eighty fundraisers simply to engage all of its alumni. However, a software agent can scale outreach to the remaining 180,000 alumni who otherwise receive little or no engagement.
AI also enables organizations to build donor relationships much earlier. For example, a development agent could engage recent graduates, understand their background and connection to the institution, and encourage small recurring donations. Over time, those relationships can grow into larger contributions. This type of long-term engagement is extremely difficult to achieve at scale with human resources alone, but software makes it possible.
How does Blackbaud measure the return on investment of these AI solutions?
The return on investment is relatively straightforward. Organizations can compare the cost of the solution against the amount of revenue it generates through additional fundraising activity. Because the agent expands outreach capacity significantly, it creates opportunities that simply would not exist otherwise.
The Development Agent supports multiple engagement channels, including SMS, email, and customizable avatars. Customers can determine how those channels are used and tailor the experience to their audience. The flexibility gives organizations considerable control while enabling new levels of scalability.
Are Blackbaud's agentic fundraising solutions unique in the market today?
Yes, we believe we are first to market with this type of fully agentic fundraising solution. A key differentiator is that our Development Agent operates directly within the systems our customers already use. It lives inside the system of record where donor data, workflows, and fundraising activities already exist.
A standalone solution would require organizations to move data between different systems and establish entirely new governance and trust models. Our approach embeds the AI directly into the existing platform, allowing customers to manage fundraising activities, data, and AI capabilities in one integrated environment. That combination of deep integration, governance, and operational continuity creates a significant advantage.
Some donors may prefer interacting with a person rather than an AI agent. How do you respond to that concern?
We hear that concern, and it is understandable because this is an entirely new category of technology. These types of solutions have never been built, purchased, or used before at scale. As a result, there is a significant education component involved. We are working with industry partners, including companies such as Anthropic and Databricks, to provide free AI education across the social impact sector.
At the same time, we believe people will become increasingly comfortable interacting with AI agents as they encounter them in other aspects of their daily lives. The transition is similar to what happened with mobile banking. Initially, many people were hesitant, but over time it became a normal and trusted way of interacting with financial institutions. We expect a similar adoption curve for agentic AI solutions.
Trust is a major issue when it comes to AI. What safeguards are non-negotiable for Blackbaud?
Trust and governance are fundamental. The data within our systems is not available to public large language models. It remains inside our controlled environment, where it is protected through our existing cybersecurity, governance, and operational frameworks. This includes both customer data and Blackbaud's enriched data assets.
Importantly, our AI capabilities operate within the same trusted environments that customers already use today. We are not asking organizations to move sensitive information into a new ecosystem. The same governance structures, security controls, policies, and procedures that protect customer data today also govern our AI solutions.
How large is the social impact sector in the United States, and why is it often underestimated?
One thing that is not widely understood is the scale of the sector in the U.S. Annual donations are over $600 billion a year, and that has grown roughly in line with U.S. GDP for the last 40 to 45 years, at around two to three percent annually. Around 70 percent of that $600 billion comes from small donations, with the rest coming from larger gifts and major checks.
People often think of charities in a segmented way, such as a small animal shelter, a university, or a hospital foundation. But when you aggregate the entire social good sector, it represents over $600 billion in annual donations and is the third-largest employer in the United States. It is a very significant and important marketplace, especially given the missions these institutions serve.
What would you tell a nonprofit leader who is considering adopting AI today?
My advice would apply equally to nonprofit leaders and CEOs in the corporate world: AI transformation must be owned by the leader. It cannot simply be delegated. Many nonprofit executives come from mission-driven backgrounds, whether in healthcare, education, research, or social services, but AI has the potential to transform every aspect of how their organizations operate.
Whether it is fundraising, logistics, financial management, recruitment, or mission delivery, AI can reshape the way organizations function. Leaders need to take personal responsibility for understanding the technology, educating themselves, and driving the transformation. They can assign operational leadership to others, but they cannot remain on the sidelines.
If AI transformation is delegated entirely to a CTO or CIO, that executive must persuade every other department to change how it operates. That is extremely difficult. Successful transformation requires organization-wide alignment, which only the CEO can effectively drive. Leaders also need to understand the art of what is possible with AI. Many CEOs come from backgrounds in finance, marketing, sales, or operations and may not consider themselves technical. However, they must invest time in learning the technology themselves.
