82% of nonprofits are now using AI. But 76% have no policy governing it.

That gap should terrify you.

It means the vast majority of organizations, including those serving vulnerable communities across Denver, Aurora, and rural Colorado, are flying blind with technology that could transform their impact or expose them to serious risk.

What is the current state of AI adoption for nonprofits in Colorado? It’s a paradox: widespread adoption, minimal strategy, and a regulatory landscape that’s about to get very real on June 30, 2026.

This guide gives you the complete picture. Where we are. Where we’re headed. And exactly what you need to do about it.

The Current State of AI Adoption in the Nonprofit Sector

Let’s start with the numbers. They tell a story of rapid adoption outpacing readiness.

What the Data Shows

According to the TechSoup and Tapp Network “State of AI in Nonprofits: 2025” report, based on insights from over 1,300 nonprofit professionals:

Adoption is widespread:

82% of nonprofits now use AI in some capacity
85.6% are actively exploring AI tools
Only 1% oppose AI adoption outright

But strategy is lacking:

Only 24% have a formal AI strategy
76% have no AI policy governing use
40% say no one in their organization is educated in AI

And a digital divide is emerging:

Larger nonprofits (budgets over $1 million) adopt AI at nearly twice the rate of smaller organizations (66% vs. 34%)
Organizations with 15+ staff are significantly more likely to have technical capacity for AI
Rural and under-resourced communities face the steepest adoption barriers

What Colorado Nonprofit Trends Tell Us

Colorado sits at a unique intersection. We’re home to a thriving tech ecosystem in Denver and Boulder. We have progressive consumer protection legislation with the Colorado AI Act. And we have significant populations in rural areas and diverse communities across Aurora and the Front Range who stand to benefit most from nonprofit services, but face the highest risks from poorly implemented AI.

The Colorado nonprofit trends mirror national patterns, but with added urgency: Colorado nonprofits must prepare for regulatory requirements that don’t exist anywhere else in the country.

For a deeper understanding of the opportunity, read why AI matters for nonprofits: building capacity for greater impact.

How Are Nonprofit Organizations Using AI?

Let’s get specific about how nonprofit organizations are using AI right now.

The Most Common AI Applications

According to the 2024 Nonprofit Standards Benchmarking Survey and other industry research:

Financial Management (Most Adopted):

Budget forecasting and projections
Payment automation and processing
Financial reporting and analysis
Cash flow prediction

This makes sense. Financial tasks offer immediate, measurable benefits while building organizational confidence with AI.

Program Operations (Growing Fast):

36% now use AI for program optimization and impact assessment
Case management recommendations
Service delivery routing
Outcome tracking and reporting

Fundraising and Development:

Donor research and wealth screening
Gift amount recommendations
Appeal letter drafting and personalization
Grant opportunity matching
30% report AI has boosted fundraising revenue in the past 12 months

Communications and Marketing:

Newsletter and email drafting
Social media content creation
Website chatbots for FAQs
Translation services for multilingual communities

Administrative Tasks:

Meeting transcription and summaries
Email management and responses
Document creation and formatting
Calendar coordination

What’s Working (And What’s Not)

The research reveals important nuances:

High comfort, low commitment: 82% of fundraisers are comfortable using AI for donor research, but 63% are unsure about using it for donor communications because it seems “less personal.”

Donor expectations vary by giving level: The more generous the donor, the more likely they support nonprofits using AI. 30% of high-value donors support AI use, compared to 19% of medium donors and only 13% of small donors.

The technology gap is real: Only 4% of nonprofits use smart donation forms, and less than 1% use real-time fundraising intelligence.

What Are the Risks of AI for Nonprofits?

AI isn’t magic. It’s a tool that amplifies whatever you point it at, including your blind spots.

Here are the risks of AI for nonprofits that Colorado leaders must understand:

Risk 1: Algorithmic Bias and Discrimination

AI systems learn from historical data. If that data reflects historical inequities (and it usually does), the AI will perpetuate them.

Real examples:

Resume screening tools that disadvantage candidates from certain zip codes
Program eligibility algorithms that disproportionately deny services to communities of color
Donor scoring systems that undervalue relationships with lower-income supporters

For nonprofits serving diverse communities in Denver, Aurora, and across Colorado, this isn’t theoretical. It’s an operational and ethical imperative.

Risk 2: Privacy and Data Security

According to research, 70% of nonprofit professionals are concerned about data privacy and security with AI use.

The concerns are valid:

Client information entered into AI tools may be stored or used to train models
Donor data shared with AI systems could be exposed in breaches
Health and social service information requires special protection

Risk 3: Accuracy and Hallucinations

63% of nonprofits worry about AI accuracy. They should.

AI systems can generate confident-sounding content that’s completely wrong. In nonprofit contexts, this could mean:

Incorrect grant application information
Inaccurate program statistics
Fabricated donor histories
Wrong compliance guidance

Every AI output needs human verification.

Risk 4: Representation and Cultural Bias

57% of nonprofits are concerned about representation and bias in AI outputs.

AI systems are trained primarily on English-language, Western-centric data. They often fail to:

Capture cultural nuances in communication
Represent diverse communities accurately
Account for Indigenous knowledge systems
Reflect the values of the communities being served

Risk 5: Regulatory Non-Compliance

Colorado nonprofits face unique regulatory risk. The Colorado AI Act (SB24-205) takes effect June 30, 2026, with penalties up to $20,000 per violation.

If your organization uses AI for “consequential decisions” about employment, services, housing, or healthcare, you may be subject to compliance requirements that most nonprofits aren’t prepared for.

How Do We Comply With the Colorado AI Act (SB24-205)?

This is the question keeping Colorado nonprofit leaders up at night. And it should be.

What the Law Requires

The Colorado AI Act (SB24-205) targets “high-risk AI systems” that make or substantially influence “consequential decisions” about:

Employment (hiring, firing, assignments)
Education (enrollment, opportunities)
Healthcare services
Housing
Financial services
Legal services
Government services

If your nonprofit uses AI in ANY of these areas, you’re likely subject to compliance requirements.

What Deployers Must Do

Organizations that use (deploy) high-risk AI systems must:

Implement a risk management program
Complete annual impact assessments
Notify individuals when AI makes decisions about them
Provide human appeal processes for adverse decisions
Report discrimination to the Attorney General within 90 days
Post public statements about AI use and risk management

The Small Business Exemption

There’s a partial exemption for small deployers, but it’s narrower than most realize:

To qualify, you must meet ALL criteria:

Fewer than 50 full-time employees
NOT use your own data to train or customize the AI
Only use AI for its intended purposes
Provide consumers with the developer’s impact assessment

Even if you qualify, you still have a “duty of care” to prevent algorithmic discrimination.

For complete compliance guidance, read our detailed breakdown of Colorado AI Act (SB24-205) compliance requirements.

How Can AI Help With Grant Writing and Fundraising Optimization?

Now for the opportunity. AI for grant writing and fundraising optimization is where most nonprofits see immediate ROI.

AI for Grant Writing: What Actually Works

AI won’t write your grants. Funders can spot AI-generated proposals. But AI can dramatically accelerate the process:

Research and Prospecting:

Scan grant databases for matching opportunities
Analyze funder priorities and giving patterns
Identify alignment between your programs and funder interests
Surface Colorado-specific funders you might have missed

Drafting Support:

Generate first drafts of boilerplate sections
Repurpose language from previous successful grants
Create outlines based on funder requirements
Edit for clarity and compliance with word limits

Quality Control:

Check for consistency across sections
Verify that all requirements are addressed
Identify claims that need more evidence
Flag jargon that might confuse reviewers

The Human Still Matters:

Customize to specific funder relationships
Add authentic stories and specific data
Ensure voice matches your organization
Make the final judgment calls

AI for Fundraising Optimization

The data shows AI is already boosting fundraising results:

Donor Research:

Wealth screening and capacity analysis
Giving history pattern recognition
Engagement scoring based on interactions
Lapsed donor reactivation identification

Ask Amount Optimization:

AI can analyze giving patterns to suggest appropriate ask amounts
Some organizations report 15-20% increases in average gift size

Communication Personalization:

Draft personalized appeals at scale
Customize messaging based on donor interests
A/B test subject lines and content variations
Automate thank-you sequences with personal touches

Campaign Analysis:

Real-time performance tracking
Predictive modeling for campaign outcomes
Segmentation recommendations
ROI analysis by channel and audience

For specific prompts you can use today, check out Top 10 Questions Nonprofits in Colorado Ask About How to Implement AI.

What Are the Ethical Risks for Rural and Indigenous Communities?

This is where Colorado’s diversity demands particular attention. AI ethics for rural and Indigenous communities isn’t an abstract concern. It’s a practical imperative for any nonprofit serving populations outside Denver’s urban core.

The Digital Divide Is Real

Rural Colorado faces significant technology access challenges:

Lower broadband availability and reliability
Fewer technical staff and resources
Less access to AI training and education
Greater distance from urban tech ecosystems

When nonprofits adopt AI without considering rural access, they risk widening the gap between communities they serve.

Indigenous Data Sovereignty

For nonprofits serving Indigenous communities, AI raises profound questions about data ownership and cultural protection.

Key concerns identified by Indigenous researchers and advocates:

Data extraction without consent: AI systems are trained on data often collected without meaningful consent from Indigenous communities. This includes cultural knowledge, languages, and practices scraped from the internet.

Bias in training data: Most AI systems are trained primarily on data that excludes or misrepresents Indigenous voices. The United Nations has noted that AI can “reinforce harmful biases, exclusion, and lead to further appropriation of Indigenous Peoples’ culture and knowledge without their consent.”

Historical data reflects historical discrimination: When AI systems use government data to make predictions, they often amplify existing disparities. Research has shown child welfare AI systems, for example, disproportionately flagging Indigenous families due to biases in underlying administrative data.

Cultural insensitivity: AI systems trained on Western-centric data fail to account for cultural nuance, Indigenous knowledge systems, and community-specific values.

Specific Risks for Aurora and Denver Metro Nonprofits

Aurora, Colorado has one of the most diverse populations in the state. Nonprofits serving these communities must be especially careful about:

Language access: AI translation tools often miss cultural nuance and may be inadequate for languages with limited training data.

Immigration-related services: Using AI for case management or eligibility screening in immigration contexts raises particular sensitivity.

Refugee and immigrant communities: These populations may have heightened concerns about data collection and surveillance.

Healthcare navigation: AI recommendations must account for cultural health practices and community-specific needs.

How to Mitigate These Risks

Involve communities in AI decisions: Before deploying AI that affects specific populations, seek their input on concerns and priorities.
Audit for bias: Regularly review AI outputs for differential impacts across communities.
Maintain human oversight: Never let AI make final decisions about services to vulnerable populations.
Be transparent: Let community members know when and how AI is being used in their services.
Respect data sovereignty: Understand what data you’re contributing to AI systems and who benefits.

For a complete ethical framework for nonprofit AI implementation, see our dedicated guide.

How Do We Integrate AI With Our Existing Nonprofit CRM?

The practical question: How do we integrate AI with our existing nonprofit CRM without disrupting operations or breaking the bank?

Start With What You Already Have

Most major nonprofit CRMs now include AI features. Before adding new tools, activate what you’re paying for:

Salesforce Nonprofit Cloud:

Agentforce AI capabilities for donor engagement
Einstein Analytics for predictive insights
Automated workflows and recommendations
Extensive AppExchange for AI add-ons

Bloomerang:

AI-assisted campaign creation
Donor generosity scoring
Behavioral tracking and engagement analysis
Integration with DonorSearch for wealth insights

Blackbaud Raiser’s Edge NXT:

Built-in analytics for donor identification
Data enrichment services
Cultivation recommendations
Prospect research tools

Virtuous:

Responsive fundraising AI
Personalized donor journeys
Predictive giving analysis

Integration Best Practices

Step 1: Audit your current state Before integrating AI, understand what data you have, where it lives, and what condition it’s in. AI amplifies data quality issues.

Step 2: Clean your data first AI on dirty data produces dirty results. Invest in deduplication, standardization, and enrichment before layering on AI tools.

Step 3: Start with native features Use AI features built into your existing CRM before adding third-party tools. This minimizes integration complexity.

Step 4: Test with low-risk use cases Begin with internal productivity (meeting summaries, email drafts) before moving to donor-facing applications.

Step 5: Create feedback loops Track AI recommendations against actual outcomes. Are the “high-potential” donors actually giving more? Are suggested ask amounts performing better?

Step 6: Train your team CRM AI features are worthless if staff don’t know how to use them. Budget for training as part of any integration.

Common Integration Pitfalls

Adding tools without strategy: Collecting AI tools without a clear use case creates shelfware and wasted money.

Ignoring data quality: AI on bad data produces confident-sounding bad recommendations.

Skipping human review: Automating donor communications without human oversight damages relationships.

Underestimating training needs: Staff need time and support to adopt new AI features effectively.

For hands-on support with CRM and AI integration, consider an AI implementation assessment tailored to your organization.

What Should Our Internal AI Acceptable Use Policy Look Like?

76% of nonprofits have no AI policy. That’s a liability waiting to happen.

Here’s exactly what your internal AI acceptable use policy should look like.

Essential Elements of a Nonprofit AI Policy

Your policy should fit on one page and answer these questions clearly:

1. What AI tools are approved for use?

List specific tools staff can use (ChatGPT, Claude, your CRM’s AI features, etc.). New tools require approval before use.

2. What can we use AI for?

Clearly state approved use cases:

Drafting internal communications
Meeting transcription and summaries
Research and information gathering
First drafts of newsletters and social posts
Data analysis and reporting

3. What should we NEVER use AI for?

Draw clear bright lines:

Final decisions about client eligibility
Employment decisions without human review
Publishing content without human editing
Processing confidential client information
Legal, medical, or financial advice

4. What data can enter AI systems?

Specify what’s allowed and forbidden:

Allowed:

Publicly available information
General organizational data

Forbidden:

Client names and personal details
Health information
Donor financial data
Immigration status or sensitive demographics

5. What review is required before publication?

All AI-generated content must be:

Reviewed by a human before sending/publishing
Fact-checked for accuracy
Edited to match organizational voice
Attributed appropriately when required

6. Who approves exceptions?

Designate a person or role who can approve use cases not covered by the policy.

7. How do we handle mistakes?

Outline the process when AI produces errors or causes harm.

Sample Decision Tree

Include a simple flowchart staff can follow:

Should I use AI for this task?

Is this task on our “never use AI” list? → If yes, STOP. Do it manually.
Will I put confidential information into the AI? → If yes, STOP. Remove sensitive data first.
Will I review and edit the output before using it? → If no, STOP. Commit to review first.
Am I comfortable explaining this AI use to our community? → If no, RECONSIDER.
If all answers are acceptable → PROCEED with AI assistance.

Making the Policy Stick

A policy on a shelf is useless. To make it work:

Train all staff on the policy within 30 days of adoption
Include in onboarding for new hires
Review quarterly and update as needed
Lead by example with leadership using AI appropriately
Create safe spaces for questions and uncertainty

The Path Forward for Colorado Nonprofits

Here’s the reality: AI for nonprofits isn’t optional anymore. The question isn’t whether to adopt it. It’s how to adopt it responsibly.

What to Do This Week

Audit your current AI use. List every tool your organization uses that has AI features. You’ll probably be surprised.
Assess your policy gap. Do you have written guidelines for AI use? If not, that’s your first priority.
Identify your compliance exposure. Are you using AI for any “consequential decisions” that might trigger Colorado AI Act requirements?

What to Do This Month

Create or update your AI policy. Use the framework above. Keep it simple. Get it done.
Activate AI features you’re already paying for. Your CRM probably has AI capabilities you’re not using.
Start one pilot project. Pick a low-risk use case (internal productivity, first-draft writing) and test it.

What to Do This Quarter

Train your team. AI adoption without training creates frustration and wasted investment.
Build compliance infrastructure. If you need impact assessments or risk management programs, start now. June 2026 will arrive faster than you think.
Engage your community. If you serve populations with specific concerns about AI, involve them in your implementation decisions.

Stay Ahead of Colorado Nonprofit Trends

The state of AI for nonprofits in Colorado is evolving rapidly. Regulations are being finalized. Best practices are emerging. New tools are launching constantly.

Subscribe to Monday Motivational Minute: The #1 free newsletter for nonprofit leaders who want to leverage AI without the overwhelm. One minute. Every Monday. Strategies you can implement immediately.

Follow Regis Arzu on LinkedIn: Daily insights on AI implementation, compliance updates, and practical guidance for Colorado nonprofits. Free advice. No gatekeeping.

Schedule a Consultation: Ready for personalized guidance on AI strategy, compliance, or implementation? Let’s talk about your specific situation.

The Bottom Line

What is the current state of AI adoption for nonprofits in Colorado?

Widespread. Strategic. And increasingly regulated.

82% are using AI. 24% have strategy. 0% can afford to ignore what’s coming.

The nonprofits that thrive will be the ones that adopt AI intentionally, implement it ethically, and prepare for compliance before the deadline hits.

The ones that wait will scramble, stress, and potentially face penalties.

You know which one you want to be.

Now it’s time to act.