Artificial intelligence is no longer a future trend or a luxury reserved for tech giants and mega-cities. It’s the new competitive baseline—and small, nimble destinations are already using it to leap ahead.

While some organizations are still debating chatbot upgrades, others are using AI to transform how they attract visitors, talent, and investment. REDI Cincinnati is adding billions in capital by targeting expansion-ready companies with predictive analytics. Estes Park generates full content calendars in minutes. Covington, Kentucky, built a GPT-powered chatbot for $200 that now handles investor and resident queries 24/7.

Yet most economic development and destination marketing organizations are not applying AI where it delivers the biggest payoff: strategic decision-making, predictive intelligence, and personalized engagement.

We break down five high-impact areas where AI is already reshaping destination marketing and economic development—through verified case studies, measurable results, and tiered frameworks you can start using now. Whether you’re just beginning your AI journey or ready to scale fast, investing 10 minutes in this read will help your destination move from ideas to impact.

Let’s dive into what the smartest destinations already know—and what you’re about to find out.

1. Using Data to Target the Right Investors

Small and mid-sized EDOs can use predictive analytics to identify which companies or sectors are most likely to invest or expand in their region. Rather than casting a wide net with limited resources, predictive platforms can analyze signals—like funding rounds, hiring surges, and M&A activity—to prioritize outreach to high-probability targets.

A leading example is REDI Cincinnati. The 15-county economic development organization employs Gazelle.ai, an AI-powered business intelligence platform, to streamline investment attraction by assigning “Expansion Scores” to companies based on indicators like export activity, job growth, leadership changes, and funding announcements. This enables their business development team to prioritize outreach to companies with the highest expansion likelihood, crafting personalized pitches that align Cincinnati’s regional strengths—particularly in advanced manufacturing and food and beverage—with prospect-specific needs. 

The approach has delivered impressive results, including over 3,400 new job commitments and more than $1.1 billion in capital investment in 2023. This was followed by support for 66 companies in growth or expansion during 2024, resulting in $1.2 billion in capital investment and $325.9 million in new payroll across the region. 

Another mid-sized EDO, Invest Ottawa, integrates AI-driven analytics via Gazelle.ai into its Foreign Direct Investment strategy to identify and attract companies in high-priority sectors such as cybersecurity and clean technology. Their system analyzes venture capital funding, executive movements, and market expansion activities to pinpoint firms with strong international growth potential. This intelligence enables efficient resource allocation, focusing relationship-building efforts on companies exhibiting strong expansion signals. This targeting strategy has proven particularly effective with prospects who previously had no awareness of Ottawa, allowing their limited staff to focus on the highest-potential opportunities.

Framework – From Data to Deals

1. Data Foundation: Inventory all existing datasets, from internal CRMs to external platforms like Crunchbase, PitchBook, or Gazelle.ai. Work with IT or research teams to centralize these sources into a single dashboard.

2. Trigger Identification: Define 5–7 key signals that correlate with company expansion, such as:

• Series B or later funding rounds
• Major executive hires in business development or operations
• New patents or facility lease agreements
• Surge in job postings tied to relocation-prone roles

3. Build or Buy Predictive Tools: Use platforms like Gazelle.ai, Localintel, or custom-built dashboards with low-code analytics tools. For more technical teams, build a scoring algorithm that weights triggers based on historic outcomes in your region.

4. Actionable Intelligence & Integration: Train business development staff to interpret expansion scores and generate highly tailored outreach materials that map a company’s needs to your region’s assets. REDI Cincinnati pairs scores with sector-specific pitch decks built around key differentiators like workforce and logistics.

5. Measure, Share, Iterate: Set clear KPIs like outreach-to-meeting rate, conversion to site visit, total capital attracted—and regularly review signal performance. Some EDOs also use this data to report to boards and funders on ROI by industry vertical.

2. Hyper-Personalized Visitor Engagement

Small DMOs can now deliver personalized experiences at scale using AI— whether through chatbots that serve as 24/7 “virtual concierges” or AI-driven recommendation engines that tailor content to each visitor’s interests. Such tools make even a tiny tourism office feel like it has an army of customer service reps and trip planners available around the clock.

A great example is how Choose Chicago engaged visitors with an AI chatbot named “The Bean” (now you know why we used the header image that we did).  Launched on their website and modeled after the city’s famous Cloud Gate sculpture, The Bean chatbot can answer visitor questions, suggest attractions, and even crack a few jokes—all with a personality crafted by local students (which is a case study all its own). In its first five months, more than 22,000 people chatted with The Bean, with 75% reporting being satisfied with the experience.

Another metropolis DMO, Destination Toronto, recently launched The 6ix—an AI-driven visitor assistant that helps travelers craft personalized itineraries in real time. Powered by OpenAI and trained on the city’s tourism content, the chatbot gives tailored suggestions based on user interests, like food, festivals, or family fun. 

What sets The 6ix apart is its tone: confident, conversational, and unmistakably Toronto. The assistant isn’t just informational—it’s an extension of the city’s identity. This tool makes it easy for curious travelers to explore hidden gems while lightening the load on human staff. By blending destination personality with responsive AI, Toronto demonstrates how major cities can use generative tech to enhance both experience and efficiency.

But this isn’t just big-city ambition. The small mountain town of Estes Park, Colorado, introduced an AI assistant that provides tailored suggestions for lodging, dining, and hiking based on user queries.

Powered by GuideGeek, a white-label AI travel assistant developed in partnership with Matador Network, the DMO worked to create the “Rocky Mountain Roamer,” a tool that interacts with visitors through platforms like WhatsApp, Instagram, and Facebook Messenger, providing real-time assistance and information.

Estes Park’s team rolled it out in phases—first a quiet pilot, then expanding to Facebook, Instagram, WhatsApp, and their website once they were confident in its responses. This phased approach allowed them to train the AI with local knowledge and even let staff jump in on live chats if the AI got something wrong, ensuring accuracy and safety as they scaled up and the Roamer learned.

In Covington, Kentucky, the economic development department launched a chatbot named “Clive” to field questions from businesses and entrepreneurs. Clive, portrayed as a green alien “intern” from a locally loved art sculpture, brings a bit of fun while using a GPT-4 language model to answer queries about zoning permits, available incentives, real estate, and even city job openings. Remarkably, Covington built this with Chatbase, a cloud-based chatbot service for under $200 per year. In the first weeks, Clive was already handling common questions and logging topics to help staff spot what investors or residents care about most.

Framework – Personalization at Scale

• Start with a Chatbot or Virtual Assistant: Identify your top visitor (or investor or resident) questions by reviewing emails, DMs, and FAQ pages. Use this as training data for an AI chatbot. Give your bot some local flair or personality.
• Pilot and Train: Soft-launch the bot on a limited channel and monitor the conversations. Use this period to expand the bot’s knowledge base for edge cases.
• Multi-Channel Expansion: Once confident, deploy the chatbot across popular channels – website, Facebook Messenger, WhatsApp, etc.
• AI-Driven Recommendations: Consider AI recommendation engines on your website or app that suggest attractions or itineraries based on a user’s profile or past behavior.
• Measure Engagement Metrics: Track usage, satisfaction (via surveys or thumbs-up/downs), and conversion metrics.

3. Intelligent Stewardship and Overtourism Management

AI can help manage tourism flows by analyzing data in real time and nudging visitor behavior toward a more sustainable load. For smaller destinations or those within larger cities, this is a way to protect what makes your place special while still encouraging tourism growth.

Prague used an AI-driven digital guide to redistribute tourist traffic. By offering personalized audio tours and recommendations through the SmartGuide app, Prague encouraged visitors to go beyond the crowded city center. Tourists who used the app spent 30% of their time exploring lesser-known neighborhoods. Another Czech city, Pilsen, applied a similar strategy by providing guide content in multiple languages to ensure international visitors didn’t all rush to the town’s handful of bucket list sites.

In the UK, Blenheim Palace partnered with Oxford researchers to develop AI algorithms that forecast visitor numbers and profiles in real time. This lets the Palace adjust staffing, ticketing, and facilities on the fly. The goal is to anticipate needs. For example, if rain is expected on a holiday weekend, the AI might predict a surge in indoor exhibit visits, prompting management to add guides at those points.

In Jackson Hole, Wyoming, the Jackson Hole Travel & Tourism Board collaborated with Datafy, an analytics platform provider, to develop a comprehensive tourism data dashboard. The resulting real-time data (some from IoT sensors and some from AI predictions) tracks not just visitor counts, but also environmental and social indicators like waste levels, traffic congestion, and wildlife sightings. By correlating these with visitation patterns, Jackson Hole can make informed decisions that balance economic gain with conservation.

Framework – Smarter Tourism Management

• Data Collection Infrastructure: Capture visitor data ethically via app tracking, Wi-Fi sensors, ticketing systems, and/or telecom partnerships.
• Analytics & Dashboards: Implement a platform to aggregate and visualize this data. Key indicators include visitor counts, queue lengths, occupancy rates, environmental quality, and sentiment from reviews.
• Predictive Modeling: Train AI models to forecast visitor flows based on weather, events, and historical data.
• Dynamic Visitor Routing: Use visitor-facing technology that suggests alternative attractions in real time.
• Safety and Stewardship Integration: Integrate AI with emergency and conservation protocols for real-time decision-making.

4. AI-enhanced Content Marketing at Scale

Marketing a place requires constant, up-to-date content creation, yet small DMOs (so most DMOs!) often have tiny content and editorial teams. AI tools can amplify a team’s output without a big budget. From generating visuals to writing copy in multiple languages, AI can help.

Visit Estes Park turned to a little-known AI platform to generate on-demand place marketing content. Happy Places is an internal-facing Generative AI model integrated with ChatGPT 4 and designed to create SEO-optimized content such as blogs and social media posts. It was trained using information from VisitEstesPark.com and community partners to ensure content accuracy and relevance. 

The Visit Estes Park marketing team can now ask, “I want a social media plan for next month focused on nature and wildlife safety,” and the AI will produce a full content calendar—captions, images, hashtags and all. They also use AI to translate posts and generate variations of content for different platforms.

Visit Utah implemented an AI-driven content placement and testing tool to automatically experiment with different website layouts and ad placements. The inPowered AI Platform integrated with DV360 (Display & Video 360) to enhance the DMO’s digital marketing efforts. This AI-driven solution facilitated automated experimentation with various website layouts and ad placements, leading to significant improvements, from a 40% increase in engagement time per session, to a 30% reduction in bounce rates. These outcomes underscore the effectiveness of AI in optimizing digital marketing strategies for tourism boards.

But AI can also help destinations be a little whimsical. Lithuania Travel ran a bold campaign using generative AI art in which they fed hundreds of real photos of Lithuania into Midjourney and prompted it to imagine surreal landscapes and cityscapes. The AI produced stunning, otherworldly images that were turned into a series of promotional posters. The tagline invited travelers to come experience the real Lithuania that inspired these AI visions. Hint: landmarks such as St. Anne’s Church in Vilnius and the surreal-already traditional Lithuania cold pink soup definitely do.

Framework – Scalable Content & Campaigns

• Identify Repetitive Content Needs: List time-consuming content types like social media posts, translations, and blog drafts.
• Choose the Right Tools: Use generative text AI, AI image generators, and content optimization tools.
• Pilot a Campaign: Test AI-created content for a specific season or campaign. Human staff should review and polish the content.
• Maintain Quality and Authenticity: Establish a human review process. Ensure cultural and brand accuracy.
• Measure Content ROI: Track engagement, conversion, and production time savings.

5. Talent Attraction and Retention through AI

Economic development also means attracting and retaining workforce talent, and AI tools can provide an advantage here, from smarter job matching to identifying skill gaps.

Michigan launched the “You Can in Michigan” campaign, which included the one-of-a-kind AI-powered Michigan Career Portal. Job seekers upload their resumes and receive personalized job matches and training suggestions. Michigan appointed a Chief Growth Officer and is using the portal’s data to identify skill gaps and inform training programs. As of Oct. 2024, the portal drove nearly 17,000 registered users and helped job seekers with career navigation, and job training and education guidance and placement.

Similarly, Indiana’s Hoosier Talent Network uses an AI engine to connect job seekers to employers by interpreting transferable skills. This helps fill openings and retains talent locally. Not to be outdone, New York City built an AI assistant to attract meeting and event planners. The tool simplified planning in NYC and doubled traffic to their meeting planner website, with a 150% jump in newsletter sign-ups.

Framework – AI for Workforce and Resident Attraction

• Intelligent Talent Platforms: Match skills to jobs using AI analysis.
• Data-Driven Outreach: Use platform data to tailor training and attraction campaigns.
• AI Chatbots for Relocation Inquiries: Engage prospective residents with automated Q&A on housing, schools, and lifestyle.
• Personalized Talent Campaigns: Use AI to micro-target campaigns by profession or life stage.
• Retaining Talent with AI Insights: Monitor early signs of outmigration using AI analysis and act proactively.

Your Turn: From Vision to Action

AI implementation is not a distant future ideal—it’s happening now in small and agile destinations and cities around the world. You don’t need a Silicon Valley budget or Manhattan-sized staff to reap the benefits. What it takes is a proactive mindset, openness to pilot new tools, and a focus on safety and measurability at every step.

Start with a clear goal in each domain. Do you want to increase investment leads? Improve visitor satisfaction? Reduce overcrowding? Attract remote workers? Use that goal to guide a small pilot with an AI solution and define what success looks like. Our tip? Use Perplexity’s free Deep Research tool to craft a blueprint for one of the goals above and roll it out, monitor results, share with stakeholders, and iterate. ChatGPT’s $20 monthly Plus plan offers even better Deep Research capabilities, but your searches are capped monthly until you spring for the $200 per month Pro package.

Equally important is to maintain a human-centric approach. AI can crunch data and automate tasks, but human oversight ensures the outputs are culturally appropriate, inclusive, and aligned with your brand values (and the humans you’re trying to engage in the first place).

With the right frameworks and iterative improvements from your community, even the smallest destination can do more with less in the AI-enabled future of place branding, destination marketing and economic development. 

Want to chat about your place-based AI strategy? Contact us!