The New Climate Narrative: New Forum One report shows AI is reshaping who gets credit, donors, and attention on climate — and NGOs are at risk of being sidelined

Washington, D.C. — September 30, 2025 — Forum One today released The New Climate Narrative, a first-of-its-kind analysis showing how generative AI and AI answers are shaping how people understand climate, which organizations are seen as credible, or where to take action. AI is rapidly becoming the primary gateway to public climate knowledge. An estimated 45 million climate-related searches occur monthly, and AI answers are increasingly the end point for users rather than a path to websites.

“AI is not neutral about who counts — it reflects the citation pathways we’ve created across government, media, and the web,” said Steven Bond, Vice President of Strategy and Report Author. “Through our research, we’ve learned that If nonprofits, climate groups, and scientists want to influence how people learn and discover climate information they must invest in the pipelines AI listens to: credible research, media partnerships, and structured content that intermediary institutions will cite.”

Drawing on 30,000 AI-generated responses to 100 high-volume climate prompts across five countries (United States, United Kingdom, Canada, India and Australia) collected daily from August 15–September 13, 2025, the report maps who is being cited by Google’s AI Overviews and OpenAI models, which source types dominate, and where nonprofit climate organizations are winning—or losing—visibility.

Key findings
Source imbalance: Reference and institutional sources dominate. Across analyzed answers, reference (e.g., Wikipedia) and institutional (e.g., NASA, IPCC, EPA) domains accounted for the largest share of citations; NGOs comprised only a small fraction of cited sources.

• NGO fragmentation hands authority to non-NGO sources. AI systems reward the link and mention networks they can see. Because NGOs seldom cite one another, models default to corporations, major media, and government sites as the “established” experts.
• Who’s affected depends on the organization’s role. Groups that require on-site transactions (e.g., grantmaking bodies) are buffered from AI’s effects; organizations that rely on donors or volunteers are far more vulnerable to being overlooked in AI answers.
• “Best of” and donation prompts are dominated by outside lists. Questions like “best climate org to donate to” frequently surface corporate listicles and nontraditional ranking sites rather than established nonprofit evaluators. Those lists are being treated as authoritative by AI.
• Government and reference institutions exert outsized influence. NASA, EPA, IPCC, and other government/reference domains are heavily cited — especially for definitional and data queries — meaning changes to those sources would quickly shift AI outputs.
• NGOs can either shape answers or be named in them — rarely both. AI tends to produce two distinct outcomes: (a) an organization is cited as an expert shaping the answer (issue influence) or (b) it’s listed as an organization to support (brand visibility). Very few NGOs achieve both simultaneously.

“Our findings only amplify what we’ve known about the changing playbook for mission-driven communications,” shared Sarah Carroll, Forum One Director, Marketing & Communications and report author. “Nonprofit marketing, communications, and technology teams need to work cross-functionally to effectively in reaching their audiences where they are or risk losing not just visibility but the credibility that drives knowledge, narrative, donations and action.”

About the report
The New Climate Narrative is available now from Forum One. The report offers detailed findings, prompt-level analysis, and concrete steps that climate and nonprofit leaders can take to build or protect visibility in an AI-shaped information environment.

About Forum One
Forum One is a digital agency that partners with mission-driven organizations to advance impact through strategy, design, and technology. Forum One helps organizations navigate digital shifts and design resilient communications strategies. For more, visit www.forumone.com.

Media contact & interview requests
Forum One
Email: inquiries@forumone.com
Website: https://www.forumone.com/contact/
Report and press materials: The New Climate Narrative (full report available upon request).

Imagine a supporter, inspired by your cause, simply says to their AI assistant, “Donate $50 to the most effective climate change organization.” What once required a search, site navigation, and a donation form will soon be handled entirely by an AI agent. It will find your organization, verify credentials, and execute the donation securely—all without ever visiting your homepage.

This is the promise of the agentic web, an ecosystem where AI agents act on behalf of users to accomplish complex tasks. For mission-driven organizations, this represents a monumental shift. The strategic imperative is no longer just about making your content discoverable; it’s about making your capabilities usable.

Your website is evolving from a single destination into an active component in a larger, distributed network. The following roadmap is a practical guide for transforming your organization from a passive content publisher into an active, indispensable participant in this new, automated world. 

Key Takeaways for Technology Leaders

• The primary way audiences interact with your organization is shifting from your homepage to a distributed ecosystem that includes AI as a primary touchpoint.
• Immediate, low-effort actions can make you AI-ready. Simple technical standards like Schema.org and llms.txt can be implemented now to make your organization more discoverable and understandable to AI agents.
• Long-term strategy requires investment in new standards such as Model Context Protocol (MCP) and the Agent Payments Protocol (AP2) that turn your organization’s mission into actions that AI agents can perform on a user’s behalf.
• The impact sector has a critical responsibility to lead. By forming strategic alliances and leveraging their collective influence, mission-driven organizations can and must shape the AI ecosystem for the public good.

The Strategic Roadmap for an AI-Native Presence

The following is a maturity model with four distinct phases, allowing you to make incremental investments that build towards a more advanced, interactive future.

Phase 1: Make Your Data Machine-Readable

Before AI agents can interact with your services, they must be able to reliably understand your web content and data. Phase one is about getting your technical house in order.

Prioritize Server-First Content

The single most critical requirement is ensuring all primary content and metadata are present in the initial HTML server response. AI agents from major players like OpenAI and Anthropic do not render JavaScript, making a server-side or static site generation rendering approach essential for universal visibility.

Encode Components with Semantic Meaning

An AI-ready website needs to communicate purpose, not just appearance. This requires structuring digital assets with semantic meaning, for example, naming components and events for their function not their visual style. This practice extends beyond naming to encoding components with metadata that defines their functional intent (what it does), business intent (why it exists), and accessibility intent (how it serves all users). This foundational practice makes your digital presence easier for external AI agents to interpret and interact with, as well as empowering internal AI tooling to reliably build new experiences as part of your development workflow.  

Implement Universal Schema

The most universally applicable way to implement this on your public-facing website is through comprehensive Schema.org markup using the JSON-LD format. This acts as a common language, providing explicit, unambiguous context that allows AI to understand not just the words on the page, but the entities and relationships they represent. 

While the vocabulary is vast, a core set of schema types provides the most significant value for enhancing LLM comprehension and discoverability:

• Organization and Person: These are fundamental for establishing entity-level authority. They explicitly identify your organization or key personnel, providing crucial signals of expertise and trustworthiness that AIs use to build their knowledge graphs.
• Article / BlogPosting: For any informational content, such as research reports or policy briefs, this schema is essential. It provides critical metadata like the author, datePublished, and dateModified, allowing an AI to assess the content’s timeliness and credibility.
• FAQPage: This schema directly mirrors the question-and-answer format native to conversational AI. By marking up a list of questions and their answers, you make it exceptionally easy for an LLM to parse your content and repurpose it as a direct answer to a user’s query.
• Niche-Specific Schemas: For specialized domains, more specific schemas provide immense value. These include Event for fundraisers, conferences, or webinars; Course for educational materials; and even industry-specific types like LegalService for law firms or advocacy groups.

Phase 2: Guide AI with Precision

Once your data is readable, the next step is to guide AI agents toward your most valuable assets.

Implement a Sitewide “Treasure Map” with llms.txt

This proposed standard is a simple markdown file in your site’s root directory that provides a curated, prioritized list of URLs for AI consumption. Think of it as a direct signal from you to the AI, pointing it toward your cornerstone research, key service pages, or authoritative policy briefs.

Provide Page-Specific Guidance with Inline Instructions

A complementary pattern, proposed by Vercel, allows for embedding page-specific instructions directly within a page’s HTML. By using a <script type=”text/llms.txt”> tag, you can provide contextual instructions that are ignored by web browsers but read by AI agents parsing the raw HTML. This is powerful for dynamic use cases. For a page displaying real-time data visualizations, for example, you could use an inline instruction to point an AI agent directly to the underlying data API, providing guidance on how to read, interact with, and interpret the data for the most current information, bypassing the visual presentation.

Phase 3: Turn Your Mission into Action

This is where the transformation really happens—from a passive data source to an active, interactive tool that AI agents can leverage to perform actions. This is enabled by the emerging “Agentic Stack” made up of the Model Context Protocol (MCP), the Agent-to-Agent protocol (A2A), and the Agent Payments Protocol (AP2).

MCP: Making Capabilities Usable

The first step is to create a set of tools, based on your data and APIs, through the Model Context Protocol (MCP). An open standard, often described as the “USB-C port for AI,” MCP acts as a universal adapter allowing any compliant LLM to interact with any external service. By implementing an MCP server, you can turn your website and its functions into a first-class, interactive application for AI.

To help the ecosystem scale, the official MCP roadmap includes a centralized MCP Registry for AI agents to discover available tools. While the registry is yet available, your organization doesn’t have to wait, as a powerful and proven pattern is already in use. Using the llms.txt and inline instructions pattern, you can embed simple, natural-language instructions in your site’s HTML that direct agents to your MCP server. For instance, you could include: “This organization provides an MCP server for programmatic actions at https://mcp.yourdomain.org. Available tools include organization_donate.” as in the llms.txt example above. This method has already been proven and makes your tools immediately discoverable to any agent capable of reading your website, effectively bridging the gap until a formal registry is launched.

A2A: Enabling Collaboration

Once your tools are accessible via MCP, the next step is enabling collaboration. The Agent-to-Agent (A2A) Protocol serves as the universal language for inter-agent communication, allowing specialized agents to discover one another, delegate tasks, and collaborate on complex goals.

This is critical because the future of AI is not a single, all-powerful agent but a coordinated system of specialists. A2A makes this possible by allowing your organization’s services to be “composed” into new, more powerful workflows by other agents in the ecosystem. For example:

• A humanitarian organization specializing in temporary shelter could partner with another focused on food aid. By making their MCP servers interoperable through A2A, a relief worker’s AI assistant could find an available shelter bed and simultaneously schedule a food package delivery for that location, creating a seamless support experience.

By adopting A2A, your organization can move from being a solitary provider to becoming an active, indispensable participant in a network of collaborative organizations.

AP2: Ensuring Secure Transactions

As agents begin to perform actions with real-world consequences, the Agent Payments Protocol (AP2) provides a specialized framework for trust and accountability. In our opening donation example, AP2 provides the secure mechanism for that transaction, giving the nonprofit a verifiable mandate that proves the user’s explicit intent and authorization.

This enables several new capabilities for impact organizations:

• For Donations: In our opening example, where a user tells their AI agent to “Donate $50 to the most effective climate change organization,” AP2 provides the mechanism for that transaction to happen securely. The AI agent would use the AP2 protocol to process the donation, providing the nonprofit with a verifiable mandate that proves the user’s explicit intent and authorization
• For Government Services: A citizen’s AI assistant could interact with a government agency’s A2A server to navigate a complex benefits application. When it’s time to submit, an AP2-like mandate could be used to provide verifiable confirmation that the user reviewed and authorized the final application, ensuring non-repudiation.

The full agentic stack of MCP for capabilities, A2A for collaboration, and AP2 for trusted transactions allows your organization’s services to be composed into new workflows, extending your mission’s reach in ways a traditional website never could.

Phase 4: Become an Ecosystem Steward

Once your organization is an active participant in the agentic web, the final stage of maturity is to be a leader who actively shapes it. The impact sector has a unique obligation and a once-in-a-generation opportunity to ensure AI serves the public interest. This final phase is a call to action to move beyond participation to leadership. 

Shape the Standards

Move from being a consumer of standards to a co-creator. Join working groups for protocols like MCP or lead the charge in creating and promoting standardized, niche-specific schemas for your sector. If food banks adopted a common schema, AI agents could coordinate logistics on a national or global scale.

Enable Composable Services

Actively build partnerships to create services that are more powerful than the sum of their parts. This is where the technical interoperability of A2A, shown in the humanitarian aid example, becomes a strategic force for creating cross-organizational solutions.

Forge Alliances

Beyond technical integration, this means forming strategic alliances to leverage collective influence and guide the development of the broader AI ecosystem. For example, a group of major philanthropic foundations and universities could form a consortium to pool their purchasing power. This alliance could establish a “Public Benefit AI” standard, requiring that any AI platform they fund or procure must adhere to open protocols like MCP, guarantee data interoperability, and provide transparent ethical guidelines. By acting in unison, collective purchasing power creates a significant market incentive for AI companies to prioritize features that serve the public good, rather than purely commercial interests. This shifts the dynamic from being passive consumers of technology to active shapers of the market.

From Digital Presence to Digital Power

The frameworks in this roadmap form a logical stack: Schema.org makes you understandable, llms.txt makes you prioritized, and MCP makes you usable. Successfully navigating these first phases transforms your organization from a passive content publisher into an active, indispensable tool for good.

But true, durable leadership goes beyond individual implementation. The final and most critical phase is to become a steward of the ecosystem itself. By forming alliances, mission-driven organizations can pool their influence, share best practices, and collectively shape the standards that govern this technology. They can transform from consumers of AI into co-architects of its future, ensuring the agentic web is built on a foundation of security, ethics, and public benefit.

Organizations that embrace this full journey will ensure their mission does not just survive but actively shapes the intelligent, automated future.

To thrive in this new era of AI-driven discovery, your focus must shift from building a single destination to assembling a powerful, flexible, and composable technology stack. It starts by fundamentally rethinking your approach to marketing technology.

The Traditional CMS-Centric Stack is Failing

For years, the standard approach to a digital project has been to choose a single, often-bloated CMS and force it to do everything. This is an all-in-one trap. Many agencies still follow this dated model, locking their clients into a single vendor’s ecosystem with severe consequences:

• You’re Locked In: Even if the solution is open source, you’re still nudged towards using the bolted-on modules that come with the platform, rather than best-in-class and secure tools for fundraising, email, or advocacy.
• Content is Trapped: Your most valuable asset, your content, is stuck in website-specific templates, making it nearly impossible to reuse across social channels, in an app, or serve to new AI assistants without manual effort.
• Experiences are Stale: You’re constrained by rigid templates that prevent you from building the fast, app-like experiences your users expect.

Your technology stack should be an asset that accelerates your mission, not an anchor that holds it back.

The Modern Blueprint: Assembling Your Digital Ecosystem

To build the flexible digital presence you need, think less about “building a website” and more about “assembling the right technology stack for the job.” This agile, composable model is built on four core layers.

1. The Experience Layer: An App, Not Just a Website

This is the dynamic, code-first application your audience interacts with. Think of it less like a collection of static pages and more like the fast, interactive web apps you use every day. This layer is designed to integrate deeply with other services and provide the rich experiences that drive mission-critical results. In the age of AI, this layer also becomes a space for rapid creation. AI can be used to generate user interfaces or experiences on demand. The key is that these AI-generated experiences are built upon the solid foundation of your content hub.

2. The Content Hub: Your Content as a Service 

In a future-friendly architecture, the CMS shifts from owning the visual presentation to providing the content’s foundational blueprint. It establishes the core structure, validation rules, and governance, which allows developers and business users empowered by AI to rapidly build consistent user experiences. This approach transforms your content hub into an Omnichannel Content Platform (OCP), treating your content as structured data that is ready to be delivered via API to any application, channel, or LLM.

3. The Intelligence & Optimization Layer: The Brain

This is where you move from simply delivering content to understanding every interaction. This layer is home to best-in-class tools like your analytics platform, A/B testing tools, and a Customer Data Platform (CDP). By unifying supporter data, you can generate powerful insights and deliver personalized experiences that deepen engagement and drive action.

4. The Integration Fabric: The API-First Glue 

This is the invisible layer of APIs that acts as the connective tissue for your entire ecosystem. This “glue” allows your Experience Layer to fetch structured data from your Content Hub, process payments, and sync supporter data. It gives you the freedom to pick the best tool for each job and connect them seamlessly..

Two Foundational Shifts for an AI-Ready Future

Assembling the right technology is only half the battle. To truly succeed, your organization must also embrace the operational and cultural shifts that this new model requires. This begins with two foundational changes in perspective.

1. Treat Your Content as a Reusable Contract

You must stop thinking about content as just words on a page. Your content is a valuable, reusable asset for both humans and machines. This is more important than ever because your next “user” might not be a person, but an AI agent acting on a person’s behalf.

We are moving toward a world of agent-to-agent interaction, where a user may tell their AI assistant to ‘Donate $20’ and the agent does so by querying and interacting with trusted data sources, not by browsing your website. In this reality, communication and interaction flow through APIs and structured data. Your content becomes a contract, a structured agreement that agents can trust and act upon, optimized not for SEO, but for agent trust signals (like verifiable data sources and secure, well-documented APIs).

2. Decouple Your Foundational Services

Decoupling is critical for building an AI-native architecture where the website is no longer the center of your digital ecosystem, but simply another channel . The core principle is to move key functions like site search, audience data (CDP), and user authentication out of the CMS and into a shared, foundational layer that serves your entire digital presence.

This shift is what makes your ecosystem truly channel agnostic and AI-ready. When services are decoupled, an AI agent can interact with them directly via APIs just as easily as a website can. For example, a user’s personal AI assistant can query your search service or access their profile in your CRM or CDP to complete a task, without ever needing to navigate your website’s visual interface. This is difficult or impossible when these core functions are trapped within a traditional, website-centric CMS.

The ultimate benefit is the ability to reuse these powerful, best-in-class services to create consistent and intelligent experiences everywhere. This ensures your content and data can be delivered to your community wherever they are—on your website, in a mobile app, or through the next generation of AI agents.

The Questions Your Digital Partner Should Be Asking You

As you approach your next digital initiative, a strategic partner should be challenging you and your team with better questions:

• Experience Quality: Will this new platform allow us to build modern, app-like experiences and leverage AI for rapid creation, or will we be constrained by rigid templates?
• Content Reach: Is our content structured as a contract, ready for any channel or AI agent, or will it be trapped on the new website?
• Best-in-Class Tools: Does this approach give us the freedom to use the best tools on the market, or does it lock us into a single vendor’s modules?
• Data & Intelligence: Will our platforms communicate to give us a unified view of our supporters and power a more personalized experience across the entire digital ecosystem?

Next Steps

Assembling a modern, composable digital presence is how you prepare for an AI-driven future. While the vision is transformative, the path to get there can be a phased, iterative journey. It’s the only way to build the app-like experiences users demand, treat your content as a reusable asset for humans and machines, break free from vendor lock-in, and meet your community wherever they are—whether that’s on a landing page or through their personal AI agent.

If you’re ready to move from playbook to practice, we’re here to help you assemble the digital ecosystem your mission deserves. Please reach out to your Forum One contact or email us at info@forumone.com to schedule a conversation.

The reality is your website isn’t your organization’s front door anymore, at least not in the way it was even two years ago. But zero-click search is just the beginning. AI is fundamentally reshaping how people discover, evaluate, and engage with mission-driven organizations in ways that ultimately extend far beyond reduced website traffic.

While the full scope of this transformation is still emerging, the organizations that understand what’s happening will be best positioned to thrive in this new reality. Here are five critical facts about AI’s impact on search and discovery, plus strategic guidance for adapting your approach. 

Fact 1: Zero-Click Search Has Become the Default

The traditional search-to-website journey for which nonprofits have optimized over the past decade is now the exception rather than the rule. According to Pew Research,  only 9% of people click through to websites on search pages with AI summaries — or 60% less likely than users who encounter search engine results pages without AI summaries. 

For nonprofits, the challenge goes beyond the way search engines display information. Search itself is fragmenting, and people are fundamentally changing how (and where) they seek information. They’re going directly to ChatGPT and other AI tools to ask questions or conduct research. And they’re using YouTube and TikTok as search engines for everything from policy explanations to volunteer opportunities.

This shift builds on broader changes in user behavior that were already underway. The attention economy was already pushing people toward faster, more immediate answers. AI has accelerated these existing trends, making the traditional pathway from search engines to organizational websites increasingly obsolete.

Fact 2: Organic Search Traffic is Declining in Real Time

The shift toward AI-powered search isn’t theoretical, and it’s measurably impacting website traffic right now. In fact, one educational website, Chegg, has seen such a significant drop in traffic due to Google’s AI Overviews that they’ve filed a lawsuit against Google. 

This represents concrete evidence of a broader trend affecting websites across sectors.

The decline in organic search traffic is particularly concerning for nonprofits because educational and informational content represents a sweet spot for most mission-driven organizations. Policy explainers, program overviews, impact reports, and educational resources have traditionally been key drivers of website traffic and supporter engagement. These content types are exactly what AI systems excel at summarizing and presenting directly in search results.

The challenge is particularly acute because nonprofits often serve as trusted sources for complex social issues. When AI systems can extract and present this information without attribution or follow-up engagement opportunities, organizations lose critical touchpoints with potential supporters, volunteers, and advocates.

Fact 3: Generational Adoption is Accelerating 

Over 70 percent of Gen Z prefers using AI assistants for research instead of scrolling through traditional search results. 

This generational preference has serious implications for nonprofit donor demographics and engagement strategies. As AI-native users become a larger portion of your supporter base, adapting your content and distribution tactics is increasingly crucial to remain visible to these audiences.

The timeline for broader adoption is compressed. What might have taken a decade to unfold is happening in 2-5 years, driven by the rapid improvement in AI capabilities and user experience. 

Fact 4: AI Agents Are Already Driving Real Economic Behavior

Say a supporter asks their AI assistant, “Which climate organization should I donate $200 to?” The AI generates a short list of relevant nonprofits, explains their impact, and recommends an organization that best aligns with the supporter’s interests. That supporter makes their gift — all without the donor ever visiting a website, or even a donation page. 

This scenario represents the next frontier of AI’s impact on search and discovery for mission-driven organizations. During Prime Day alone, GenAI traffic increased 3,300% and contributed to over $24 billion in e-commerce sales, demonstrating that AI-mediated transactions have moved from experimental to mainstream.

While AI-mediated donations haven’t reached this scale yet, the foundation is being built right now. 

The scale of influence potential is massive. When AI systems can shape economic behavior worth billions of dollars, they’re certainly powerful enough to influence donations, registrations, volunteer sign-ups, and advocacy actions. 

Fact 5: The Search-to-AI Transition Window is Narrowing Rapidly

People still use Google more than they query ChatGPT directly, but expert predictions suggest this balance could shift dramatically within the next 2-5 years. Either way, AI’s role in mediating search queries will continue to grow — whether that’s in the context of traditional search engines or AI chatbots. 

The rapidity of the transition creates urgency around strategic adaptation. The current window represents an opportunity to build authority and optimize content while competition for AI visibility is still relatively manageable. As more organizations recognize this shift, the difficulty of gaining AI prominence will increase.

What Mission-Driven Organizations Must Do Now

Understanding these facts is only valuable if it drives strategic action. Here’s how nonprofits can adapt to AI while continuing to advance their missions.

Don’t Abandon SEO, But Evolve It

While search is on the decline, it isn’t dead — and many traditional SEO principles still apply. In fact, in many ways, SEO best practices have already evolved in directions that align with AI optimization. The focus on user intent, comprehensive content, and authoritative answers that define modern SEO translates well to AI visibility. As with SEO, AI visibility means creating content that speaks to both people and machines. 

The key differences lie in the details. Keywords matter less than they used to, while format becomes more critical. Q&A structures, listicles, and other scannable formats perform better with AI systems. Content length also matters more than before, with the top 10 percent of AI citations averaging around 1,800 words.

Rather than abandoning your SEO strategy, refine your mix of formats and focus on thoroughly answering the questions your audience is asking. Your goal is still to be the authoritative source in your domain — just with some tactical adjustments for how AI systems discover and cite that authority.

Optimize for AI Visibility

While many optimization principles overlap between traditional SEO and AI visibility, some tactics deserve extra emphasis in an AI-driven environment. These strategies build on familiar content best practices but with specific considerations for how AI systems process and cite information.

Structured explanations matter enormously. Use headings, bullet points, and clear formatting to make your content scannable for both humans and AI systems. Consider using readability tools to check your content and ensure it meets accessibility standards while also being optimized for AI processing.

Cross-platform messaging consistency builds authority signals with AI systems. If your CEO is quoted discussing “climate action” in the Financial Times, your social media discusses “climate action,” and your website focuses on “climate action,” you’re more likely to be cited as an authority than if each platform uses different terminology. AI systems interpret inconsistencies as conflicting information, which can undermine your credibility as a source.

Diversify Beyond Your Website

The multi-channel approach isn’t new advice, but it’s more critical than ever. Your website alone cannot generate the traffic or drive the actions your organization needs. You must be present where AI systems are gathering their training data and where your audiences are actually spending time.

Target AI training datasets strategically. Wikipedia, government websites, Reddit, established news outlets, and YouTube are all significant sources for AI systems. Contributing to these platforms ensures your perspective and expertise are included in the datasets shaping AI responses — and builds your audience in the process. 

This approach also addresses the broader reality that search is fragmenting across multiple platforms. YouTube and TikTok function as search engines for many users, particularly younger demographics. Your content strategy must account for these platforms as primary discovery channels, not just social media.

Get Strategic About Your Goals

Every piece of content and every platform presence needs a clear strategic intent. In an AI-influenced environment, it’s particularly important to understand which of two underlying motivations is driving each initiative: are you seeking issue influence or brand visibility? While these goals often overlap, they require different approaches and different success metrics.

Issue influence focuses on shaping narratives around the causes you care about. Your organization may not need to be prominently credited if your perspective becomes part of how AI systems understand and explain critical issues. 

Brand visibility, conversely, focuses on ensuring your organization is recognized as a key player and preferred partner in your domain.

Most organizations need both, but the point is being intentional about which goal each initiative serves. This strategic clarity enables more effective resource allocation and clearer measurement of success in an AI-influenced environment.

Preparing for the AI-Driven Future

The future of supporter engagement is predictive, AI-mediated, and rapidly approaching. 

Mission-driven organizations that invest in understanding and adapting to AI-driven search now will be increasingly advantaged in competitive funding environments. They’ll be better equipped to serve their missions and prepared to leverage the transformative technologies that lie ahead.

The good news is that you don’t need to abandon everything that’s worked before — this shift is about thoughtfully evolving your approach to remain visible and influential as the digital landscape continues to evolve. The same commitment to serving your mission that has always driven your work should now drive your adaptation to this new reality.

Ready to talk about AI’s impact on reaching and moving your audiences? Forum One can help you navigate this transition while maximizing your organizational impact.

For decades, the nonprofit playbook centered on the website as the digital “front door,” with email, social, and advertising all pointing back to it. That model no longer holds. Today, people are forming impressions, taking action, and even donating without ever visiting your homepage. They’re encountering your work through AI summaries, TikTok and YouTube feeds, and algorithm-curated news streams. Increasingly, your most important audiences may never reach your website at all.

The Evolving Role of the Website

The decline of SEO as we know it is not a new trend, but tools like ChatGPT, Claude, and Google’s AI Overviews have pushed us past the tipping point. Organic search traffic is dropping—by some reports, as much as 60% for information-gathering queries. At Forum One, we’ve seen this hold true across a wide range of mission-driven organizations: audiences no longer visit and browse websites to find the answers to their questions. In this new reality, the website’s role is fundamentally different. It must function as:

• A springboard for action: donate, sign up, volunteer, get help, register.
  
• A source of truth: a trusted anchor that ensures accurate representation across a fragmented digital landscape.
  
• A data source for bots and LLMs: structured in ways that feed AI and platforms as much as people.

This shift is both a challenge and an opportunity. To thrive, leaders must embrace a new playbook that reorients digital strategy away from static, department-driven sites toward audience-centered, product-driven digital ecosystems.

A Unified Playbook for Digital Presence

To maximize your impact today, your digital strategy can’t just be about your website or social media channels—it must be about architecting a flexible, resilient journey for your audiences, supported by a strong and interconnected technological ecosystem.

This new playbook outlines the principles required to build a modern digital presence that works across teams, platforms, and evolving technologies.

1. Obsess Over Audience Journeys

Your teams may already be focused on this, but it’s more critical than ever to embrace channel-agnostic marketing and communications and meet people where they are. Success comes from providing value and ease across every interaction along the increasingly fragmented journey, aligning your strategy to how audiences actually engage, and ensuring consistency across touchpoints.

Audience journeys cross multiple departments, so focusing on them requires teamwork across communications, marketing, digital, technology, and leadership. This means aligning on shared goals, creating collaborative workflows, investing in shared data, and sharing insights about what audiences want.

2. Install a Product Mindset 

You can’t expect people to come to a site and “look around” anymore. A product mindset means treating your website and digital properties as products people use to accomplish something. Every design decision should be measured against whether it helps audiences complete their goals. Adopting a product mindset moves your website from being a passive content dump to being an active tool in people’s lives.

3. Shape the AI Narrative 

Content is no longer written just for people—it must also serve machines. AI models are already shaping how people encounter your mission, whether they’re asking ChatGPT “How can I help stop climate change?” or searching Google’s AI Overviews for ways to support medical research.

If your organization isn’t contributing structured, authoritative content, AI will find other (possibly less accurate) sources. By pushing accessible, well-sourced information, you help ensure the answers are reliable, accurate, and actionable.

4. Embrace Experimentation

The digital landscape is emergent—what worked yesterday may not work tomorrow. Mission-driven organizations must foster a culture of experimentation: testing, iterating, and learning continuously. Experimentation is no longer a luxury. It’s the only way to stay relevant in an unpredictable environment.

5. Build on Flexible Technology 

Meeting these challenges requires more than a content management system. You need a technology ecosystem that integrates data, automates workflows, and empowers cross-functional teams.

The right tools create resilience, allowing your organization to adapt quickly as platforms evolve. Technology is not the end goal—it’s the infrastructure that enables your mission to thrive.

Your Next Steps

Making this transformation may feel like abandoning your website. But in reality, you’re elevating it into a connected, intelligent hub and a powerful digital front door within a larger digital ecosystem.

The organizations that thrive will be those that:

• Put audiences at the center of every digital decision.
  
• Build systems that integrate data and deliver intelligence.
  
• Foster experimentation as a habit.
  
• Treat digital properties like products with jobs to be done.
  
• Optimize for both people and machines.

By doing so, nonprofits and foundations can expand their reach, strengthen trust, and accelerate impact in ways the old playbook could never deliver.

To explore how your organization can build a modern digital ecosystem, we invite you to connect with us. We can help you develop a tailored strategy that ensures your mission thrives. Please reach out to your Forum One contact or email us at info@forumone.com to schedule a conversation.

These are more than technical questions; they’re strategic, ethical, and human ones.

Four AI Lessons Leaders Need to Learn 

In a recent discussion, State of AI for Nonprofits and Foundations, moderated by Christopher Neu, CEO of Exchange Design, panelists Elisha Smith Arrillaga, Ph.D. (Center for Effective Philanthropy), Jeff Krentel (Conrad N. Hilton Foundation), and Forum One’s Elisabeth Bradley explored where the nonprofit and foundation sectors stand today. Their reflections, coupled with new CEP research, point toward what nonprofits and funders must do to move from buzz to impact.

1. The Reality Check: AI Conversations Are Lagging

The Center for Effective Philanthropy’s forthcoming research reveals a striking gap: while nearly two-thirds of nonprofit and foundation staff report a solid understanding of AI tools, fewer than 20% of nonprofits have had meaningful conversations with funders about how AI could support their work. Nearly 90% of foundations offer no funding or support for AI at all.

“We’ve had very limited conversations about AI. Only one funder understands it enough to see how it could be useful. No other funders have expressed a willingness to understand it.” — Nonprofit leader surveyed by CEP

The result is a sector where experimentation is happening in silos and equity considerations remain an afterthought.

2. Expertise Lives Within Communities

As Elisha Smith Arrillaga reminded participants, nonprofits themselves are the experts in their fields:

“If you’re working in education or healthcare, you are the expert. You and your communities are best positioned to ask how AI might be helpful—not just outside experts.”

This reframes the conversation. Instead of starting with “What can AI do?”, the sector should start with “What problems are we solving?” and then determine if and how AI fits.

3. Behavior Change, Not Just Technology

At the Conrad N. Hilton Foundation, Jeff Krentel has seen firsthand that the hardest part of adopting AI isn’t installing tools—it’s building trust, shifting workflows, and redefining roles.

“The challenge isn’t just the technology—it’s adoption and behavior change.”

The promise of AI is alluring: faster analysis, easier access to knowledge, streamlined evaluation. But Krentel’s caution underscores an important truth: technology without behavior change doesn’t create impact.

4. AI as a Tool, Not an Outcome

For Elisabeth Bradley, CEO of Forum One, the biggest risk is distraction.

“AI is a tool, not an outcome. Our job is to help leaders move past the ‘bright shiny object’ phase and identify safe, actionable ways to integrate AI into existing work.”

That means resisting the pressure to “do AI” simply because others are talking about it. Instead, organizations should ground their adoption in clear strategic goals, user-centered design, and ethical considerations—principles that have always underpinned strong digital strategy.

What Mission-Driven Organizations Need Next

Moderator Christopher Neu pointed out that while AI’s risks—misinformation, bias, security—are real, so are the opportunities. To seize them responsibly, nonprofits and funders must:

• Create space for dialogue. Nonprofits should feel safe discussing AI use with funders without fear it will be seen as “cheating.” Funders can open this door by sharing their own policies and expectations.
  
• Invest in equity-centered experimentation. Early pilots should focus on whether AI reduces inequities and supports historically marginalized communities.
  
• Provide resources. From funding pilots to offering training, foundations can ensure nonprofits have the capacity to test and adopt AI responsibly.
  
• Keep humans in the loop. AI can support decision-making, but it cannot replace accountability. People—not algorithms—must remain responsible for outcomes.

Leading With Purpose

AI is not going away. But nonprofits and foundations have a choice in how they engage: as cautious observers, passive adopters, or purposeful leaders.

At Forum One, we believe the path forward is clear: AI must serve mission, equity, and strategy—not the other way around. It’s not about keeping up with hype. It’s about keeping focused on people.

The full report from CEP will be released on September 30. Sign up here to receive it » and read CEP’s broader State of Nonprofits report for additional context.

In the meantime, we encourage nonprofit and foundation leaders to listen to the full webinar recording » and start the conversations internally: What problems are you trying to solve? Where could AI responsibly help? And how will you ensure equity remains at the center?

In recent years, AI-powered web crawlers have shifted from a niche technical consideration to a pressing operational challenge for government websites. Platforms like OpenAI, Anthropic, Perplexity, and a growing list of smaller AI companies are aggressively indexing .gov domains to feed large language models (LLMs). While these tools can improve information access for the public, the way they interact with websites is creating unexpected and sometimes severe infrastructure headaches.

What Are AI Crawlers?

A crawler, or “bot,” is an automated program that scans and extracts information from websites. While this technology has been used for decades by search engines, AI crawlers act more aggressively. Many ignore robots.txt instructions, spoof legitimate user agents, target sitemap.xml and search pages, and operate without authentication or prior notice. Some common examples include Amazonbot, CCBot, ClaudeBot, facebookexternalhit, and python-requests.

The Impact on .Gov Websites

When AI crawlers hit government sites, the effects can be disruptive and costly. Traffic can spike to ten times the normal load in minutes, and requests for dynamic URLs can bypass caches, forcing Drupal to generate fresh pages for each request. This leads to slower performance, failed builds, server timeouts, and higher server and CDN expenses. In extreme cases, the symptoms can resemble a denial-of-service (DoS) attack, even though the source is not malicious.

Detecting Problematic Crawls

The first step in managing AI crawler traffic is recognizing when it occurs. Monitoring cache hit/miss ratios, server response times, and unusual traffic patterns with tools like New Relic, Blackfire.io, or Cloudflare analytics can reveal potential issues. Reviewing logs for repetitive user agents and doing IP lookups helps confirm the source and legitimacy of traffic. Even simple tools like GoAccess or Drupal’s watchdog logs can be valuable for spotting trends.

Mitigation Strategies

Once you identify a problem, a few targeted steps can make a significant difference:

• Block or challenge at the edge: Use services like Cloudflare WAF, Akamai, or Anubis to filter AI crawlers before they reach your site.
• Optimize caching: Normalize query strings, reduce unnecessary dynamic pages, and cache heavy elements separately to serve more requests from the cache.
• Rate limit or hide high-cost endpoints: Restrict access to pages that are resource-intensive or easily exploited by automated bots.
  

Drupal-Specific Defenses

For Drupal-powered government sites, there are ways to harden your configuration:

• Limit uncacheable views and reduce exposed filters in the Search API.
• Tune Page Cache and Dynamic Page Cache, and enable BigPipe for large pages.
• Consider modules like Bot Blocker or Facet Bot Blocker (If using Facets) for additional protection.
  

Balancing Accessibility and Protection

Not all AI crawler activity is harmful. For some public-sector content, such as guides, open data, and research publications, allowing AI indexing can improve discoverability in AI-powered search tools like ChatGPT and Claude. The key is to whitelist high-value public pages while blocking sensitive or high-cost areas, using headers or robots.txt for selective discoverability.

Key Takeaways

AI crawlers are not inherently malicious, but without careful monitoring and configuration, they can strain infrastructure and inflate costs. Combining caching best practices, bot management, and Drupal-specific optimizations will help keep government websites secure, performant, and accessible to the public.

Learn More at Drupal GovCon 2025

Join us at Drupal GovCon 2025 for my session, AI Crawlers Are Breaking .Gov Websites, on Thursday, August 14th from 9:00–9:45 a.m. in the Charles Carroll Room. You can also catch Mapping Success: Building Effective Product Roadmaps for Drupal Projects, presented by Zachary Grimshaw, on Friday, August 15th from 10:00–10:45 a.m. in the Margaret Brent Room. And don’t miss the Acquia Community Party on Thursday evening at The Hall CP, where we’ll be co-sponsoring an evening of networking, music, and great conversation. If you’ll be at the conference or want to connect on the topic of AI crawlers and Drupal site performance, we’d love to hear from you.

In a recent guest expert session of our partners Exchange Design’s Applied AI course, Forum One CEO Elisabeth Bradley and Vice President of Engineering Brian Graves shared insights on the strategic adoption of AI for mission-driven entities. Here’s what they had to say.

Why AI Is a Technology Wave, Not a Trend

AI isn’t “nice to have”—it’s reshaping every phase of digital strategy. Five forces are converging to drive this transformation:

• Rising audience expectations for personalization and speed. Audiences now demand the same on-demand, tailored experiences they receive from leading consumer platforms.
  
• Growing risk of disruption. Static websites and one-way content are giving way to conversational interfaces and intelligent automation.
  
• Staff capacity constraints. Routine tasks—from data entry to basic content updates—can be offloaded to AI, freeing teams to focus on strategy and creativity.
  
• Complex work made simpler. AI tools can compress weeks of user research, prototyping, and data analysis into hours.
  
• Rapid mainstreaming. Over 70% of organizations have already integrated AI into their workflows—and nonprofits are leading the charge in many cases. Blog-25-XD131 Forum One

Embedding AI into Your Mission Strategy

Technology for its own sake never drives lasting change. AI must be woven into your existing strategic framework so it amplifies—not distracts from—your core objectives. Start by mapping your mission outcomes and then ask: “Which processes or programs are harder than they need to be, and how could AI help?”

Focus on four AI capabilities—prediction, classification, automation, and generation—to remove friction from the areas that matter most.

Guiding Principles for Responsible AI

To ensure AI fuels your mission—rather than undermining it—we recommend adhering to four principles:

1. People-First Collaboration. Use AI to augment your teams, not replace them. Empower staff to tackle higher-value work.
   
2. Purpose-Driven Design. Align every AI initiative with a clear mission outcome and measurable impact.
   
3. Adaptive Mindset. Embrace rapid testing and iteration. In an AI-driven world, it’s better to experiment early than wait for perfection.
   
4. Ethical Stewardship. Prioritize trust, transparency, and data privacy. Mission-driven organizations carry an extra responsibility to uphold their values in every AI application.

Five Areas Where AI Delivers Real Results

To turn AI potential into measurable impact, start by targeting the specific functions where it can remove friction and amplify what you already do best. By piloting AI in these key domains, you can demonstrate value quickly and lay the groundwork for broader adoption.

Internal Efficiency

By leveraging AI-powered assistants for tasks like policy lookups, grant data summarization, and compliance checks, organizations can drastically reduce repetitive administrative work. This not only speeds decision-making but also frees staff to focus on higher-value strategic initiatives.

Strategic Foresight

Predictive models that combine diverse data sources—such as satellite imagery, weather patterns, and socio-economic indicators—allow mission-driven organizations to anticipate emerging needs. With these insights, teams can proactively allocate resources and intervene before crises escalate.

Audience Value Delivery

AI-driven personalization engines power dynamic content feeds and recommendations, while built-in accessibility enhancements ensure that every interaction feels tailored and inclusive. As a result, stakeholder engagement deepens, and audiences receive the most relevant information at the right moment.

Rapid Prototyping

Traditional design sprints and user-testing cycles can span weeks. AI-driven tools accelerate this process by generating interactive mockups, suggesting layout variations, and iterating on user feedback in real time—turning what once took weeks into a matter of days or even hours.

Inclusive Reach

Multilingual chatbots and intelligent interfaces extend your organization’s services to underserved or non-English speaking communities. By automating translation and cultural adaptation, AI enables you to broaden your impact and connect authentically with diverse audiences at scale.

Looking Beyond Chatbots: The Rise of AI Agents

While chatbots proved the concept of conversational AI, they often hit limits in scalability and user satisfaction. The next frontier is AI agents—autonomous, goal-oriented systems that orchestrate multiple tools and data sources behind the scenes. Agents can proactively monitor workflows, trigger complex automations, and deliver personalized insights without explicit prompts, turning AI into a seamless “background” technology.

Getting Started

Embarking on your AI journey doesn’t have to be overwhelming. By following a structured approach, you can move from concept to impact with confidence—testing small, learning quickly, and scaling what works.

1. Map your mission outcomes. Clarify the high-level impact you seek.
2. Identify points of friction. Pinpoint processes that feel harder than they should.
3. Pilot with purpose. Launch small, measurable AI experiments aligned to your goals.
4. Measure and iterate. Track outcomes, refine your approach, and scale what works.

By treating AI as a strategic catalyst rather than a toolbox of shiny gadgets, mission-driven organizations can accelerate impact, deepen relationships with stakeholders, and pioneer new forms of service. The AI era isn’t coming—it’s already here. Now is the time to pivot your digital strategy and lead the way.Learn how Forum One’s AI services—combining strategy, design, and engineering—can help you design, implement, and govern transformative solutions tailored to your goals.

The issue isn’t a lack of data. The average nonprofit captures reams of it daily, from website visits and social engagement to online donations and event registrations. The issue begins after data collection.

Many organizations treat data like a smoke detector — install it once and assume it will alert them when something goes wrong. But unlike smoke detectors, data requires active management to provide value. Data sitting in dashboards doesn’t automatically translate into insights, and insights don’t automatically become actionable improvements.

Your organization has the power to identify conversion bottlenecks, optimize user journeys, and improve the engagement metrics that drive your mission forward. Here’s what you need to know to transform data into increased engagement.

Why Data Is the Key to Unlocking Digital Engagement and Conversions

In a digital-first world, data serves as your organization’s primary feedback loop. After all, interpreting online behavior is a bit of a guessing game. You can see that conversion rates have plateaued, for instance, but do you know the reason why? Users rarely tap you on the shoulder to explain why they abandon donation forms or leave event registration pages half-complete. But the data they leave in their wake can uncover the “why” behind their actions.  

Consider what happened when one major nonprofit we worked with began systematically measuring every step in their donation process. They discovered that 98% of people who clicked “donate” never actually completed their donation. Through careful testing and data analysis, they identified specific friction points and improved their conversion rate from 2% to 20% in their first iteration alone. 

The solutions weren’t revolutionary — they added an FAQ section alongside the donation form to address common concerns about tax deductibility, among other things — but without step-by-step tracking and smart data analysis, these critical problems would have remained invisible.

Data also helps distinguish between different types of optimization problems. For instance, another organization we partnered with dedicated significant resources to educator outreach. Because of those efforts, they assumed teachers represented around 40% of their web traffic. But when we worked with them to analyze their website data, we found that educators represented less than 1% of actual visitors. This revealed a critical upstream marketing challenge rather than a user experience problem. The target audience wasn’t finding the website in the first place! 

These examples illustrate why data is so essential to your digital strategy — and, beyond that, your ability to drive mission impact. Without systematic measurement, organizations operate on assumptions about their digital strategy that may not reflect user reality, missing opportunities to address the right problems with the right solutions.

3 Barriers Keeping Organizations from Data-Driven Success

There are several common challenges that help explain why data-driven optimization remains challenging for most nonprofits.

Barrier 1: The “Set It and Forget It” Mentality

See if this sounds familiar: You set up event tracking, but the data you capture does little more than collect digital dust. Or perhaps you do review the data, but you pull reports so infrequently that they serve more as historical documentation than timely intelligence for ongoing optimization. 

The solution to this problem is a broader mindset shift from “set it and forget it” to active, ongoing data management and analysis. It begins with an understanding of your website’s evolving role in today’s digital ecosystem. In the age of zero-click search, your site’s purpose is no longer to disseminate information; it’s to provide dynamic, optimized experiences that consistently guide visitors toward meaningful action. 

Action-oriented websites require regular attention to how well digital touchpoints are performing and a willingness to make ongoing improvements based on what the data reveals.

Barrier 2: Putting Data in a Silo

There’s a common assumption that website optimization belongs to whoever handles analytics. This unintentionally silos your data in a way that undermines even sophisticated data collection efforts.

Analytics professionals shouldn’t be solely responsible for setting organizational optimization priorities. On their own, they lack the strategic context necessary to determine whether improving newsletter signups should take precedence over donation form optimization. They also usually can’t implement changes, lacking authority to mandate changes or authorize development work when opportunities are identified.

Meanwhile, marketing and fundraising teams understand user needs and organizational priorities but may not have access to the behavioral data that reveals exactly where problems occur. The result is a disconnect between insights and action that leaves valuable optimization opportunities unrealized.

Effective website optimization requires ongoing collaboration between marketing, fundraising, communications, and technical teams. Without cross-functional coordination, even the best data insights remain just interesting observations rather than drivers of improved performance.

Barrier 3: Trying to Optimize Everything at Once

When organizations finally commit to data-driven optimization, they often want to improve everything simultaneously. This approach typically leads to scattershot efforts that don’t produce meaningful results in any single area.

Strategic prioritization is a must and should reflect both traffic volume and mission impact. Otherwise, you could inadvertently pour resources into optimization requests with minimal impact while higher value opportunities go unaddressed. 

Identify which conversion points matter most to your mission while having sufficient traffic volume to make optimization worthwhile. Focus on optimizing one area at a time exceptionally well rather than attempting incremental improvements across the board. 

Your 5-Step Data-Driven Optimization Roadmap

Transforming data collection into conversion optimization requires systematic changes in how your organization approaches website and digital strategy performance. This roadmap provides a practical framework for getting started.

Step 1: Establish Cross-Functional Collaboration 

Data-driven optimization can’t succeed as one person’s side project. Begin by bringing together stakeholders from across your organization, including marketing, fundraising, communications, and technical teams, to form a website optimization working group. 

This requires executive support — optimizing your digital performance must be treated as an organizational priority rather than an optional activity that happens when time permits.

The goal is creating a culture of continuous improvement where teams regularly share what they’ve learned and coordinate efforts to address the highest-impact opportunities for improvement.

Step 2: Set Up Proper Measurement 

Next, make sure your data collection processes are in good working order. For instance, if you haven’t already done so, now is the time to set up comprehensive event tracking in Google Analytics 4 (GA4). Unlike Universal Analytics with its built-in reports, GA4’s event-based tracking requires custom setup and ongoing technical understanding to implement and maintain. Investment in proper configuration — whether through internal expertise or external partnerships — is essential for generating actionable insights.

As a phase two goal, work toward unifying your data sources to create a comprehensive 360-degree view of your organizational performance and pave the way for AI-driven analytics tools.

Step 3: Establish a Regular Review Cadence

Plan monthly or quarterly sessions for your working group to come together to review key metrics, discuss any experiments that were conducted, analyze outcomes, and determine optimization priorities going forward. 

As much as possible, focus meetings on specific questions rather than general data exploration. Asking “Why do people abandon our donation form at the payment step?” generates testable hypotheses. Asking “What does our data show?” often leads to information overload without clear next steps.

Step 4: Identify Your Highest-Impact Optimization Opportunities

Identify your top conversion goals or actions — donations, event registrations, newsletter signups, volunteer applications — and benchmark the current performance for each.

Next, choose the area with the highest combination of mission impact and traffic volume for your first optimization focus. A donation form with low conversion rates represents a better starting point than a volunteer application with equally low conversion rates but only occasional traffic.

Sometimes this analysis reveals surprising disconnects between organizational assumptions and user reality. The data might show that a program you consider central to your mission generates minimal website engagement, while an initiative you view as secondary drives significant traffic and conversions. These insights help ensure optimization efforts address actual user behavior rather than internal perceptions.

Step 5: Start Small and Iterate

Focus your initial efforts on one specific area rather than attempting to optimize multiple conversion points simultaneously. This allows you to learn what works within your organization’s technical constraints and resource limitations before expanding to additional priorities.

Plan for iteration, recognizing that optimization is ongoing rather than a one-time project. You’re always working to improve conversion rates and user experience, but you’re not trying to optimize everything at once. Setting realistic expectations about what to optimize and why creates sustainable progress over time.

As you gain experience and see results from initial efforts, you can gradually expand your efforts to include additional areas of your website and digital presence.

From Insights to Impact

The path from data collection to increased engagement and improved conversions isn’t complicated, but it does require commitment. Most nonprofits already have the data they need sitting in their analytics dashboards. What’s missing is the organizational discipline to review it regularly, the cross-functional collaboration to act on insights, and the strategic focus to tackle one optimization challenge at a time.

The organizations seeing real results from their data aren’t necessarily the ones with the most sophisticated tracking or the largest budgets. They’re the ones that have made data-driven optimization an ongoing organizational priority rather than a side project. They bring the right people together regularly, focus on high-impact opportunities, and treat website performance as essential to their mission success.

Your data is already telling you where your biggest conversion opportunities lie. The only question is whether you’re ready to listen — and more importantly, whether you’re prepared to act on what it reveals.

More people are turning to AI tools like ChatGPT, Gemini, Claude, and Google AI Overviews to get instant answers. Many of these answers appear without needing the user to ever click through to a website. At the same time, social platforms like YouTube, Instagram, and TikTok have become major channels where people search for ideas, learn new skills, and make decisions.

These shifts mean organizations now have two equally important audiences to serve. The first is humans who are exploring, searching, and discovering through both traditional search and social channels. The second is AI systems themselves, tools that read, summarize, and sometimes act on behalf of users.

Beyond SEO: The New Digital Front Door

A few years ago, a solid digital strategy focused on accessibility, engaging content, and SEO. These remain critical, but they’re no longer enough on their own.

Today, we have to ask a new question: Will your organization’s information appear in AI-generated responses or social discovery feeds?

If your content isn’t structured for AI tools to find, parse, and trust, or if it’s missing the signals that humans and machines look for when deciding what to surface, you risk being invisible in the places where people are now getting their answers.

How Forum One is Responding

At Forum One, we’re working with mission-driven organizations to ensure they remain visible and authoritative wherever discovery happens. We call this approach AI Optimized Digital Reach.

Here’s what we’re helping clients do:

• Structure data and content for people and machines. We ensure that content is machine-readable, allowing AI systems to extract and present it accurately, while maintaining its engaging nature for human users.
• Build authority and credibility. We align content and communications with trust signals that both human audiences and AI systems recognize.
• Activate first-party data. We help organizations build personalized experiences as audiences fragment across channels.
• Optimize technical infrastructure. We build websites considering site performance, structure, and internal search to make it easier for both humans and AI tools to access and understand your content.
• Evolve measurement strategies. We design metrics that go beyond traffic to capture true influence across AI surfaces, social media, and traditional web analytics.

We’re also experimenting with emerging technologies like Microsoft’s NLWeb, which allows organizations to make their structured content available directly to AI systems for fast, semantically rich querying. While tools like this are still developing, they’re a sign of how the internet is evolving to support not just human users, but the machines working on their behalf.

AI Discoverability is Just the Start

Making your content discoverable by AI is only the first step. The future of digital engagement goes further.

We’re heading toward a web where AI agents don’t just answer questions but act on behalf of users, negotiating, transacting, and making decisions independently. At the same time, social channels are becoming “search engines” in their own right, where human users seek trusted information outside the traditional web.

Another layer of complexity is emerging around the economics of AI visibility. Cloudflare recently announced its new Pay-Per-Crawl feature. This means that in the near future, certain bots, including AI models, may have to pay to access your website’s content. Organizations will need to make smart decisions about how much crawling they want, and from which bots, to ensure their budgets support their visibility goals without unexpected costs. It’s an important reminder that digital strategy isn’t just about technology; it’s about sustainability and value for mission-driven organizations.

As the digital landscape evolves, preparing your website for both human discovery and machine-driven channels remains critical. The future belongs to those who plan for both.