Despite AI's promise for addressing global challenges, empirical understanding of AI adoption in mission-driven organizations (MDOs) remains limited. While research emphasizes individual applications or ethical principles, little is known about how resource-constrained, values-driven organizations navigate AI integration across operations. We conducted thematic analysis of semi-structured interviews with 15 practitioners from environmental, humanitarian, and development organizations across the Global North and South contexts. Our analysis examines how MDOs currently deploy AI, what barriers constrain adoption, and how practitioners envision future integration. MDOs adopt AI selectively, with sophisticated deployment in content creation and data analysis while maintaining human oversight for mission-critical applications. When AI's efficiency benefits conflict with organizational values, decision-making stalls rather than negotiating trade-offs. This study contributes empirical evidence that AI adoption in MDOs should be understood as conditional rather than inevitable, proceeding only where it strengthens organizational sovereignty and mission integrity while preserving human-centered approaches essential to their missions.

That's why the technology team at the well-known nonprofit Crisis Text Line in New York City analyzed some 65 million text messages to determine what words were most statistically associated with a high risk of suicide. This scale of analysis would clearly be infeasible without some form of automated analysis, and its results surprised the team. Use of the term "EMS" in a text, for example, is five times more predictive of a high risk of suicide than the actual word "suicide." As a result, the organization is now able to respond to 94 percent of high-risk texters in fewer than five minutes. This is just one example of "mission-driven artificial intelligence"--the responsible application of artificial intelligence (AI) to solve societal and ecological challenges. Sometimes dubbed "AI for good," mission-driven AI is the use of machine-learning techniques to streamline operations and enhance programs at nonprofits, nongovernmental organizations (NGOs), and social enterprises.

Humanity is now developing our greatest contribution to the expansion of intelligence on the planet: the flowering of artificial intelligence. It would be a shame if all we used it for were Amazon shopping and Facebook birthday reminders. Universities, companies, nonprofits, and governmental agencies are already busy developing interesting tools and applications that direct machine learning toward the common good. Though still in their early days, these initiatives just may represent our best bet for addressing our most challenging ecological and societal problems. Welcome to the world of "Mission-Driven AI." Being mission-driven is not the same thing as having a mission statement.