The Future of Nonprofit Work: How AI Will Reshape Roles in the Next Decade
The World Economic Forum estimates that around 1.1 billion jobs could be transformed by technology over the next decade, with 39% of workers' core skills expected to change by 2030. For the nonprofit sector, this transformation presents both unprecedented challenges and remarkable opportunities. This article examines how AI will reshape nonprofit roles—from fundraising to program delivery to operations—and what leaders must do now to prepare their organizations for the workforce of the future.
When your development director asks whether AI will replace fundraisers, or your program manager wonders if their job will still exist in ten years, they're asking questions that deserve honest, thoughtful answers. The nonprofit workforce—currently 12.5 million strong in the United States alone—stands at an inflection point. Emerging technologies such as machine learning and AI will create more jobs than they eliminate over the next five years, according to research by ServiceNow and Pearson. Yet this broad reassurance masks the profound transformation ahead: the jobs that exist in 2030 will look significantly different from those today, and some roles will indeed change dramatically or disappear entirely.
The World Economic Forum's Future of Jobs Report projects that by 2030, job disruption will affect 22% of all jobs, with 170 million new roles created and 92 million displaced, yielding a net gain of 78 million positions globally. For nonprofits, this means that while the sector will continue to need people, the skills those people need and the work they perform will evolve substantially. The organizations that thrive will be those that prepare their workforces now—not by resisting change, but by shaping how that change unfolds.
This article provides a clear-eyed look at how AI is likely to reshape nonprofit roles across the sector. We'll examine specific functions—fundraising, program management, operations, communications—and explore what changes are coming, what skills will become more valuable, and what leaders can do to prepare their teams. We'll also address the elephant in the room: job security concerns and how to navigate them with honesty and compassion.
Understanding the future of work isn't about predicting with certainty—the pace and direction of AI development contains genuine uncertainties. Instead, it's about developing the adaptive capacity to respond to multiple possible futures. The nonprofit leaders who engage thoughtfully with these questions now will position their organizations and their people to navigate whatever the next decade brings.
Understanding the Big Picture: Four Scenarios for 2030
Rather than predicting a single future, it's more useful to understand the range of possibilities. The World Economic Forum's "Four Futures for Jobs in the New Economy" framework helps leaders think through different scenarios based on two key variables: the pace of AI advancement and the readiness of the workforce to adapt. Each scenario has different implications for nonprofit work.
Scenario 1: Supercharged Progress
Exponential AI advancement meets widespread workforce readiness
In this scenario, AI capabilities advance rapidly while education and training systems successfully prepare workers for new roles. Businesses harness the "agentic leap"—AI systems that can operate autonomously on complex tasks—driving a shift toward an AI-centric economy. Productivity and innovation soar.
For nonprofits, this means many current tasks disappear but new occupations emerge quickly. Staff become "agent orchestrators," directing AI systems rather than performing tasks manually. Program staff might manage AI agents that handle intake, scheduling, and follow-up communications while they focus on complex client relationships. Development teams could oversee AI systems that conduct prospect research, draft initial appeals, and optimize campaign timing while fundraisers concentrate on major donor relationships and strategic planning.
Key implication: Heavy investment in workforce reskilling pays off. Organizations that prepare staff for AI orchestration roles thrive.
Scenario 2: Age of Displacement
Rapid AI advancement outpaces workforce adaptation
AI capabilities advance exponentially, but education and reskilling systems can't keep pace. Businesses race to automate in lieu of scarce talent, displacing workers faster than the workforce can adapt. Economies advance technologically but fracture socially, with unemployment spikes and eroding consumer confidence.
For nonprofits, this scenario increases demand for services (more people needing help) while potentially reducing the available workforce and donor base. Organizations might face pressure to automate heavily to maintain services with smaller teams. Staff who can adapt quickly gain significant advantage; those who can't face difficult transitions.
Key implication: Organizations must invest in workforce development both internally and as part of their mission—the sector becomes both subject to and responder to workforce disruption.
Scenario 3: Co-Pilot Economy
Incremental AI progress meets widespread workforce readiness
AI progress is more incremental than exponential—perhaps due to technical limitations, regulation, or market dynamics. Meanwhile, AI-ready skillsets become widespread as education systems successfully adapt. An "AI bubble" burst shifts focus from mass automation to pragmatic integration and augmentation.
For nonprofits, this is perhaps the most manageable scenario. AI becomes a widely-used tool that enhances human capabilities rather than replacing them. Most roles evolve gradually, with AI handling routine aspects while humans retain core functions. Staff have time to develop new skills, and the transition feels more like the adoption of email or cloud computing—significant but not overwhelming.
Key implication: Steady, sustainable investment in AI literacy and tool adoption. Less urgency but still need for consistent skill development.
Scenario 4: Stalled Progress
Gradual AI advancement combined with skills gaps
AI advancement slows while the workforce also fails to develop critical skills. Technical limitations, regulatory constraints, or economic factors limit AI capabilities. Governments and businesses adopt conservative, selective AI deployment focused on incremental efficiency gains within existing workflows.
For nonprofits, this scenario means the status quo largely continues. AI remains a useful tool for specific tasks but doesn't fundamentally transform work. Organizations that over-invested in AI preparation may feel they wasted resources; those that delayed may feel vindicated. However, this scenario seems least likely given current AI development trajectories.
Key implication: Even in this scenario, basic AI literacy remains valuable. The risk of this scenario doesn't justify ignoring AI entirely.
Most experts expect reality to unfold somewhere between scenarios 1-3, with significant variation across sectors and regions. For nonprofit leaders, the key insight is that preparing for workforce transformation is valuable across most plausible futures—and particularly important if more disruptive scenarios unfold. The downside of preparation if change is slow is modest; the downside of failing to prepare if change is rapid is severe.
How Specific Nonprofit Roles Will Evolve
While the overall picture involves uncertainty, we can be more specific about how AI is likely to change particular functions within nonprofits. Understanding these role-specific changes helps leaders have honest conversations with staff and plan workforce development investments. For more on how different roles can use AI effectively, see our articles on AI tools for development directors and AI for program managers.
Fundraising and Development
From transactional processes to relationship-centric craft
Fundraising stands at the center of AI-driven transformation in nonprofits. Soon, artificial intelligence will be part of every fundraising platform, screening donors, drafting solicitations, and predicting lapses. The danger is clear: AI could speed up the hamster wheel, flooding inboxes and accelerating donor fatigue. Email response rates are already stuck below 1%, and only 19% of first-time donors give again.
Yet the opportunity is equally significant. By handling rote, administrative tasks, AI can free fundraisers to do what machines can't: listen, connect, solve problems, and build genuine relationships with donors. Collaborative AI tools that treat fundraising as a human-centric craft, not a transactional process, will become the new standard. Fundraisers will increasingly need to be both data-savvy and tech-savvy, proactively adjusting strategies based on real-time insights.
What changes: Routine tasks like prospect research, initial outreach drafting, acknowledgment letters, and campaign optimization become heavily AI-assisted or automated. Data analysis that once took weeks happens in moments.
What becomes more valuable: Relationship building, donor cultivation, strategic thinking, ethical judgment about AI use in donor relations, and the ability to work alongside AI tools effectively.
What leaders should do: Invest in relationship skills alongside technical training. Help fundraisers understand they're evolving into relationship specialists supported by AI rather than being replaced. PwC's research shows workers with AI skills command wage premiums up to 56% higher—the path forward is skill development, not resistance.
Program Management and Service Delivery
From administrative burden to human-centered impact
Program staff often spend excessive time on documentation, data entry, and administrative tasks that pull them away from direct service. Research indicates that social workers, for example, spend up to 65% of their time on paperwork rather than clients. AI offers the possibility of dramatically reducing this administrative burden.
AI-powered documentation tools can automate case notes, intake summaries, and progress reports. Scheduling and coordination tasks can be handled by AI systems. Outcome tracking and analysis that once required manual data compilation can happen automatically. This frees program staff to focus on what drew them to the work: direct human connection and service delivery.
What changes: Documentation, scheduling, routine communications, data entry, and basic analysis become increasingly automated. Intake processes may involve AI triage that helps staff prioritize and prepare for interactions.
What becomes more valuable: Complex judgment, trauma-informed practice, cultural competency, relationship building, crisis intervention, and the ability to handle situations AI can't manage. Oversight of AI-assisted processes becomes a new skill.
What leaders should do: Position AI as liberating staff from paperwork burden rather than threatening jobs. Involve program staff in designing AI implementation to ensure it serves their needs. Train staff on human-in-the-loop practices where they oversee AI-assisted processes.
Operations and Administration
From manual processes to strategic efficiency
Operations roles face some of the most significant transformation potential. Many administrative functions—payroll processing, accounts payable, scheduling, procurement, compliance tracking—involve routine, rule-based tasks that AI handles well. The World Economic Forum specifically notes that roles built around rote, manual tasks are likely to decline precipitously.
However, this doesn't mean operations staff become unnecessary. Instead, their roles evolve toward managing automated systems, handling exceptions and edge cases, strategic planning, and ensuring that efficiency gains serve mission objectives. The demand for operational expertise remains, but its application shifts.
What changes: Routine processing, data entry, standard report generation, basic compliance checking, and repetitive coordination tasks become automated. The volume of manual work decreases substantially.
What becomes more valuable: Systems management, exception handling, strategic operations planning, vendor relationships, change management, and translating operational efficiency into mission impact. Understanding how to configure and oversee automated systems becomes essential.
What leaders should do: Begin cross-training operations staff in adjacent skills. Help them develop strategic capabilities that complement automated processes. Be honest that some roles may shrink but emphasize pathways to evolution rather than elimination.
Communications and Marketing
From content production to strategic storytelling
Communications roles are already experiencing significant AI transformation. Most nonprofits using AI report employing it for content creation—drafting emails, social posts, newsletters, and marketing materials. AI writing tools help teams produce first drafts in minutes instead of hours. Staff still review and personalize everything, but AI dramatically reduces the effort of starting from blank pages.
The evolution isn't toward eliminating communications staff but toward expanding what they can accomplish. Hybrid communication-plus-tech roles are emerging that blend storytelling, social media expertise, and AI-assisted content creation. The communications professional of 2030 likely manages AI tools as part of their workflow while focusing human creativity on strategy, voice, and connection.
What changes: First-draft creation, basic content variations, routine posting schedules, and standard reporting become AI-assisted. The bottleneck shifts from content production to content strategy and quality control.
What becomes more valuable: Strategic communications planning, brand voice guardianship, community engagement, crisis communications, ethical judgment about AI-generated content, and the ability to infuse human authenticity into AI-assisted work.
What leaders should do: Invest in both AI tool training and strategic communications skills. Help staff see AI as amplifying their capabilities rather than threatening their relevance. Establish clear guidelines about AI use in communications that protect brand authenticity.
Emerging Roles and Skills in Demand
As some roles evolve, new positions are emerging that didn't exist a few years ago. Understanding these emerging roles helps organizations plan workforce development and helps individual staff members chart career paths. Current nonprofit job market analysis shows several categories of new positions gaining prominence.
New Roles Emerging in Nonprofits
Positions that barely existed five years ago
Data Analysts with AI Capabilities
Professionals who can extract insights from large datasets to inform decisions on programming, fundraising, and operations. Unlike traditional analysts, these roles require comfort with AI tools and the ability to translate data insights into actionable recommendations for non-technical colleagues.
Digital Fundraising Strategists
Specialists who leverage AI for donor targeting, campaign optimization, and personalized messaging. These roles combine traditional development skills with technical fluency, bridging the gap between fundraising strategy and AI-powered execution.
AI Ethics and Compliance Professionals
Staff who ensure responsible AI use and maintain data privacy. As AI adoption increases, organizations need people who understand both the ethical implications and the regulatory landscape—a role that combines policy knowledge, technical understanding, and values-based judgment.
Hybrid Communication-Tech Specialists
Professionals who blend storytelling, social media expertise, and AI-assisted content creation. These roles require creative skills alongside technical comfort, managing AI tools as integral parts of communications workflows.
AI Implementation and Training Leads
Internal champions who guide organizations through AI adoption. These roles require both technical literacy and change management skills, helping colleagues develop AI capabilities while ensuring responsible implementation.
Skills That Gain Value Across All Roles
Capabilities that become more important regardless of function
The World Economic Forum reports that employers expect 39% of workers' core skills to change by 2030. While AI and big data top the list of fastest-growing technical skills, human skills remain critical—and in some ways become more valuable as AI handles routine tasks. The following skills gain importance across nearly all nonprofit roles:
- Creative thinking: As AI handles routine work, human creativity in strategy, problem-solving, and innovation becomes more valuable
- Resilience and flexibility: The ability to adapt to changing technology and evolving role expectations
- Leadership and social influence: Human connection and team leadership remain distinctly human capabilities
- AI and big data literacy: Understanding how to work with AI systems and interpret data-driven insights
- Ethical judgment: Determining appropriate AI use, recognizing bias, and ensuring responsible implementation
- Emotional intelligence: Human relationship skills become more valuable as routine interactions become automated
The Changing Shape of the Nonprofit Workforce
One of the more striking predictions about AI's impact on workforce structure involves the potential shift in organizational shape. As AI agents take on more "midlevel" work—tasks that once required experienced professionals but can now be automated—differentiation increasingly comes from senior professionals who excel at strategy and innovation. Some analysts predict the knowledge workforce may evolve toward an "hourglass" shape: more talent concentrated at junior and senior levels with a smaller mid-tier.
For nonprofits, this has significant implications for career pathways and organizational structure. The traditional progression from entry-level to middle management to senior leadership may become less linear. Staff may need to develop strategic capabilities earlier in their careers or find specialized niches that AI can't address. Organizations may need to rethink how they structure teams and develop talent.
Implications for Organizational Structure
How nonprofit teams may need to evolve
Flatter Hierarchies with Specialist Depth
Organizations may move toward flatter structures where AI handles coordination tasks that once justified middle management layers. This shifts middle managers toward either specialist expertise or broader strategic roles. Staff at all levels take on more direct responsibility while AI provides support that once came from supervisors.
Project-Based Teams Over Static Departments
As AI enables more fluid resource allocation and coordination, organizations may shift toward project-based structures where teams form and reform around specific initiatives. This requires staff to develop adaptability and collaboration skills while reducing the importance of departmental boundaries.
Hybrid Human-AI Teams
Team structures may explicitly include AI systems as team members with defined roles and capabilities. Human team members manage AI tools, handle exceptions, provide judgment, and focus on tasks requiring human connection. Understanding how to orchestrate human-AI collaboration becomes a core competency.
The nonprofit sector's workforce growth projection—approximately 142,000 additional jobs by 2028, representing a modest 1.1% increase—masks significant churn beneath the surface. Some roles will grow substantially while others contract. The net job numbers tell only part of the story; the transformation of what jobs entail is equally important. For guidance on developing your organization's strategic approach to these changes, explore our article on creating an AI strategic plan.
What Nonprofit Leaders Should Do Now
Understanding the future of work is valuable only if it translates into action. Nonprofit leaders face the challenge of preparing their organizations for transformation while managing current operations and often limited resources. The following framework provides practical guidance for workforce preparation.
Invest in Continuous Learning Infrastructure
Build organizational capacity for ongoing skill development
The most important investment isn't in any specific AI skill but in your organization's capacity for continuous learning. The skills needed in 2030 may differ from those we can predict today. Organizations that develop cultures of ongoing skill development will adapt more readily than those that treat training as periodic events.
- Allocate dedicated time for staff learning—not as extra work but as core job responsibility
- Create structures for peer learning and knowledge sharing
- Establish AI literacy baselines while developing deeper expertise in key staff
- Budget for professional development even during tight fiscal periods
Have Honest Conversations About Job Evolution
Address job security concerns directly and compassionately
Staff have legitimate concerns about how AI will affect their jobs. Avoiding these conversations doesn't eliminate anxiety—it increases it. Leaders need to have honest discussions that acknowledge uncertainty while providing clear pathways forward. Hiring decisions continue to emphasize mission alignment and prior experience while soft skills and emotional intelligence have risen sharply in importance—communicate this to staff.
- Be honest about which tasks may be automated while emphasizing evolving roles rather than elimination
- Provide concrete pathways for skill development that prepare staff for evolution
- Involve staff in AI implementation decisions so they shape change rather than have it imposed
- Commit to supporting staff through transitions even if some roles change significantly
Develop Internal AI Champions
Build distributed expertise throughout the organization
Rather than relying solely on external consultants or IT staff, develop AI champions across departments who can guide colleagues, evaluate tools, and ensure responsible implementation. These internal experts become bridges between technology and mission. Learn more about this approach in our article on building AI champions in nonprofits.
- Identify staff with interest and aptitude for AI and invest in their development
- Create formal roles or responsibilities for AI champions
- Ensure champions are distributed across functions, not concentrated in IT
- Connect champions to external networks and learning communities
Plan for Multiple Futures
Build adaptive capacity rather than betting on single predictions
Given uncertainty about exactly how AI will evolve, avoid betting everything on a single scenario. Instead, build adaptive capacity that serves your organization across multiple possible futures. This means developing broad AI literacy, creating flexible organizational structures, and maintaining relationships with various technology partners.
- Develop scenario plans for different paces of AI transformation
- Avoid over-investing in specific AI tools that may become obsolete
- Focus on transferable skills that remain valuable across scenarios
- Build relationships with technology partners who can help navigate change
Embracing Transformation with Purpose
The future of nonprofit work will be shaped by AI in ways both predictable and surprising. What we can say with confidence is that organizations that prepare their workforces will navigate the transition more successfully than those that don't. The investment in AI literacy, continuous learning infrastructure, honest conversations, and adaptive planning pays dividends regardless of exactly how the future unfolds.
It's worth remembering that nonprofits exist to serve missions, not to preserve specific job structures. The purpose of workforce transformation should be enhancing your organization's ability to create impact—serving more people, achieving better outcomes, advancing your cause more effectively. When staff understand that AI is a tool for mission advancement rather than a threat to their livelihoods, they become partners in transformation rather than obstacles to it.
The nonprofit sector has adapted to previous technological revolutions—from typewriters to computers, from direct mail to digital fundraising, from paper files to cloud databases. Each transition felt threatening at the time, and each ultimately enabled the sector to accomplish more. AI represents a more fundamental shift than most previous technologies, but the adaptive capacity that carried nonprofits through earlier transformations remains available.
Countries and organizations that deploy policies to help workers adapt and acquire new skills will see those workers remain engaged and productive while spreading new capabilities more quickly. Social protection systems that support difficult job transitions become increasingly important. For nonprofit leaders, this means both preparing your own workforce and potentially advocating for broader workforce development policies that serve your communities.
The choices nonprofit leaders make now about workforce development, organizational culture, and AI adoption will shape their organizations for the next decade. Those choices can either position your team to thrive amid transformation or leave them struggling to adapt. The future of nonprofit work isn't something that happens to your organization—it's something you help create through the decisions you make today.
Ready to Prepare Your Team for the Future?
We help nonprofits develop workforce strategies that prepare teams for AI-enabled futures while maintaining mission focus. From AI literacy programs to organizational transformation planning, we can help your team navigate change with confidence.