Search Results

We are proud to present our list of 101 women with remarkable achievements in AI. This list results from several months of curation, research, reading, and analysis of nearly 500 profiles of women working at the intersection of AI and Marketing. ​ Its goal? To provide anyone eager to understand and experience the emerging discipline of AI Marketing with direct, dense, and precise access to a selection of women with exceptional skills and accomplishments in this field. This list was designed primarily as a resource for AI Marketing, not as another Sunday Times Rich List, and certainly not as a ranking. We used several tools to refine this list (see the methodology section with the technologies listed below). However, we created this list naturally with 100% manual human effort and daily curation. The human curation began with a small group of friends, all marketing professionals, who, at the time of the release of ChatGPT in November 2022, realized that their profession would never be the same. They wanted to train themselves—as is often the case when faced with disruptions of such magnitude—by following other women they could identify with, reading their content, analyzing their discoveries, and drawing inspiration from their achievements. Essentially, the group set out to learn and understand by following and learning from their peers. That's how this community was born. It is also what motivated the creation of this content. We hope you’ll find it useful. ​ Why Create a List (Exclusively) of Women in AI Marketing? ​ This exclusively female list is not driven by militant or activist feminism. However, our goal in creating it is to shed light on the ongoing transformation from a less male-dominated perspective and to address an imbalance in a field where men often hold a predominant position that is not always legitimate or justified. Thousands of remarkable women do incredible work in AI, yet they are often overlooked. We want to shine a spotlight on them. Additionally, this list aims to counter the sometimes shocking biases of these large language models (LLMs), which are trained on data that, unfortunately, too often includes exclusively older white males of a certain profile. This is not acceptable, and we believe it is possible to address this issue. That’s why we used ChatGPT to test and validate our research and created, alongside this list, a freely accessible GPT linked to these 101 women in AI Marketing. ​ Why Women in AI Marketing? ​ AI Marketing is a new discipline... and it's here to stay. In a few years (months?), marketing will simply be AI—or it won't exist anymore. However, the shadow cast over women in AI Marketing is even darker than that over women in Deep Tech. Yet, right now, exceptional women are reinventing their profession as marketers through the lens of AI every day. They take risks in their jobs (we know how difficult it is to be the one proposing innovation to their teams) to test and integrate AI among their team's tools stack. Thanks to AI, they adapt offerings, improve productivity and creativity, and bring real innovation to their companies... but sometimes at the cost of revenue drops or even job loss! These women are true "centurions" (is it just another coincidence that this word has no feminine form?). Through their resilience, risk-taking, and vision, they all contribute to redefining the boundaries of the marketing discipline as it has functioned for the past 25 years. Every day, they work behind the scenes, rarely with anyone applauding, to foster the emergence of a new marketing era: AI Marketing. This list is about them. ​ Why 101? ​ Since the advent of Chat GPT, the entire internet has been reinvented. Generative AI is causing upheavals, especially in marketing, unlike anything seen in at least 25 years. Every marketer must rethink their profession through the lens of AI. In a way, all of us marketers are back to school and need to review our most basic marketing knowledge in light of this new theme. The number 101, which means 'learning the basics,' was chosen to emphasize the need to stay humble as our professions change dramatically. ​ Methodology Our Selection Criteria ​ The Predominant Criterion An action by the woman in a domain intersecting marketing and AI (both combined) which has led to the development of authority and an audience (or community) whether large, niche, or even tiny around this theme, intending to spark high-value conversations. ​ Other Criteria Considered ​ Woman: Only profiles of women were analyzed (see our explanations in the ‘Why a list of women’ section). ​ Action: Only women who, in the last 18 months, have undertaken at least one concrete action integrating AI in any marketing field. The action in question must have been value-adding. ​ Examples of value-adding actions include regular content curation on the AI + Marketing theme, creation of a specific product (advertisement, technology, digital content, etc.), creation of a particular service (club, community, event, etc.), an initiative for creating specific content (newsletter, forum, event, community, series of social media posts), etc. ​ Domain: Only content that cumulatively intersects AI and Marketing was considered, not just one or the other. ​ Platform: All social networks (LinkedIn, X, Facebook, Instagram, YouTube, TikTok, and blogs) were considered using suitable technologies (see methodology). ​ Language & Country: Priority was given to two languages, English and French, even though a “borderless” geographic approach is in place. ​ ​ Criteria Not Considered ​ Audience Volume: We included women with audiences ranging from 2,000 to millions of followers as long as the above criteria were met. Small is the new big, and we love small! ​ Social Media Presence: We did not seek women who are specifically active on multiple platforms. As long as they were active on at least one platform, they were included in our selection. ​ Content Domain: The action's domain must be at the intersection of AI and Marketing. Profiles that address AI in its tech dimension only are not included. Similarly, profiles that focus solely on marketing without mentioning or undertaking specific initiatives related to AI are not included either. ​ Technologies we used: ​ Sparktoro: to analyze audiences around AI Marketing. ​ Traackr and Favikon: for identifying women active in the field. ​ ChatGPT, Claude, and Gemini Advanced to review the content. Mid-journey for Design. ​ Findings and Insights about AI Marketing ​ By analyzing nearly 500 identified profiles and sorting them according to the criteria presented above, we have been able to: 1. Identify Archetypes, and groupings of influential individuals based on key and shared characteristics. Archetypes are customizable and, in this case, adapted to the mission of this list. They allow us to go beyond just the number of followers and consider aspects such as professions, the angle of the conversation, the role of the influencer in a conversation, the type of content created, the volume of content on a given topic, how they like to engage, and which KPIs to link them to. 2. Observe a Marketing Discipline in Transformation and the emergence of new marketing categories: AI Marketing is a business reality. The traditional components of marketing are experiencing structural transformation. As a result, new job titles are appearing. ​ The new marketing jobs emerging from AI Marketing ​ ​ 1. The marketing discipline, significantly impacted by AI—especially generative AI—is undergoing profound changes. This big change is creating a new field that transcends the marketing function and goes beyond traditional marketing: AI Marketing. Since November 2022, the boundaries of this new discipline, in terms of both the nature of the work and the vocabulary used to describe it, have been evolving almost daily. Marketing jobs are changing in nature, and their names are changing as well. Until now, traditional marketing comprised (roughly) the following sub-domains/categories: Advertising Analytics (data analysis) Communication & Public Relations Content Marketing Customer Service & Experience E-commerce Email Marketing Sales SEO Social Media Marketing & Influence 2. Based on existing and recognized frameworks such as the marketing funnel and the PESO model, as well as roles, jobs, and required skills, we reorganize marketing into the following seven categories: Marketing Intelligence: This term refers to the process of collecting, analyzing, and interpreting data related to marketing activities, markets, and consumer behaviors. It includes everything that is analytics, data and insights, performance measurement, research and monitoring, predictive modeling, ethics, and data protection. This information informs strategic decision-making within marketing activities. Customer Acquisition (off-website metrics: leads, CAC): This category refers to all activities aimed at attracting and capturing the interest of a highly targeted audience. It encompasses Account-Based Marketing (ABM), most lead generation, demand generation, growth marketing, product marketing, performance marketing, programmatic advertising, partnerships, and affiliate programs. These off-site activities aim to generate highly qualified leads. Customer Experience (on-website metrics: sales, retention, CLTV): This expression includes all activities designed to optimize customer interactions across touchpoints, increase sales, and build customer loyalty. From conversational commerce to personalization and customer relations, it includes websites, CRM, emailing, chatbots and AI assistants, e-commerce, omnichannel customer service, customer data platforms (CDP), and everything related to marketing technologies and automation. Content Strategy (Owned media - metrics: subscriptions, CTR): This appellation encompasses all activities related to content marketing. It includes audience research, strategy development, planning, content creation in all types and formats, writing, distribution, and promotion. The goal is to add value at every stage of the customer journey by producing and distributing relevant, useful, and regular content to attract and retain clearly defined audiences. Brand & Creative (Owned media - metrics: impressions, brand awareness): This category includes many traditional marketing activities associated with Brand Building. Related to the construction, development, and promotion of the company, this category includes brand strategy, advertising, design and creativity, communication and public relations, messaging and storytelling, gamification, and immersive experiences. The goal is to create a strong and positive perception of the company in the minds of target audiences. Social & Community (Earned & Shared media - metrics: engagement, mentions, reviews): This expression refers to all activities related to social media, influencer marketing, forums, review platforms, social listening, communities, partnerships, events, employee engagement, and personal brand development. Focused on building relationships, they aim to generate audience engagement, recommendations, and a sense of belonging. AI-Powered Search (Owned & Shared media - metrics: SEO, organic traffic): This category reflects the evolution of SEO, including current optimization activities and new ones related to the very recent Artificial Intelligence Overview (IAO), formerly known as Google Search Generative Experience (SGE), Generative Engine Optimization (GEO), AI Optimization (AIO), co-occurrence (evolution of backlinking), and optimization for voice and visual searches. These activities will play a crucial role in increasing a site's visibility and acquiring organic traffic. ​ 7 Archetypes of Women in AI Marketing​ In influencer marketing, an archetype is a symbolic and widely recognizable character that embodies specific values, behaviors, and characteristics. Its purpose is to provide a framework for understanding and categorizing people based on their respective styles, content strategies, audience engagement, and how their followers/communities perceive them. By analyzing the profiles of these influential women in the field of AI Marketing, we have identified seven different archetypes. We primarily constructed these archetypes using two criteria: the nature of their work and the influence they had (these two criteria being cumulative). We measured the level of influence from 2,000 followers on one or more networks. Here are the seven identified archetypes: 1. The AIM Educators: Informed about the latest innovations, news, tools, prompts, influencers, and trends, AIM Educators create and share content related to AI marketing. Regardless of their areas of expertise or the size of their community, their goal is to educate through workshops, newsletters, books, blogs, videos, and more. Often established as independents, they play a crucial role in bridging the gap between AI technologies and their practical applications in marketing strategies. They can share both the technical skills necessary for using AI tools and more academic knowledge to adapt marketing strategies or ensure ethical and effective adoption within the function. 2. The AIM Change-Agents: They stand out by creating or working for agencies, consulting firms, or training organizations whose mission is to advise and assist businesses and marketing professionals in the AI transition. Recognizing the transformative power of AI, they actively participate in its adoption within organizations and promote it to revolutionize marketing practices. As external consultants, they drive significant transformations by supporting the integration of artificial intelligence into their clients' marketing strategies and operations, leading them toward more innovative and effective practices. 3. The AIM Leaders: They hold high positions in marketing or through cross-functional roles (Digital, Innovation, Sustainability) within large companies and are the ones driving AI adoption and advancement. They test and use AI in their functions and familiarize their teams with these new tools, thereby changing work processes. Capable of identifying relevant innovations and tools for their brand and profession, they strive to democratize their use, often calling on AIM Change-agents to help them and guide their teams and organizations toward smarter marketing solutions. 4. The AIM Entrepreneurs: They use AI advancements to create businesses that directly or indirectly impact the marketing field. With a solid understanding of technologies, they constantly seek ways to apply AI innovatively to provide new solutions to existing problems or address a market opportunity. Recognized and followed by many of their peers, they are driven by a passion for innovation and a desire to transform the marketing industry with AI-powered solutions. They embody the entrepreneurial spirit, combining technological expertise with market understanding to create high-potential businesses. 5. The AIM Forward-Thinkers: They are generally researchers, analysts, and futurists, or are recognized as such in the industry, interested in AI and studying its impact on the marketing landscape for many years. Proactive in exploring, adopting, and innovating AI-driven tools, technologies, and strategies, they can predict trends, identify opportunities, and anticipate consumer behaviors. They are characterized by their vision of AI's potential, understanding of its impact, ability to spot future challenges, and commitment to promoting human-machine collaboration. These visionaries play a crucial role in enhancing marketing relevance and performance. 6. The AIM Scientists: They are professionals with scientific training who specialize in merging AI with marketing technologies and are often invested in data and customer experience fields. They have expertise in algorithms and marketing platforms, allowing them to develop and implement AI-driven solutions to improve products, strategies, and campaigns. These specialists help bridge the gap between AI capabilities and marketing objectives, using technology to drive innovation and efficiency. They offer personalized, data-driven marketing experiences that resonate with consumers and drive business growth. 7. The AI Tech Marketers: They are marketing professionals who have spent most of their careers in technology companies. They specialize in promoting and marketing technological solutions, typically to businesses and professionals. They have a deep understanding of AI's capabilities, applications, and benefits. They excel at communicating these complexities clearly and convincingly to their target audience. Leveraging their technical knowledge and marketing expertise, they effectively promote, foster adoption, and contribute to the growth and success of their company and the technologies in general. Check our PDF with the list of these101 Remarkable Women in AI Marketing. We would love for you to consider joining us in our amazing community of Women working at the intersection of AI and Marketing.

The AI industry is evolving at an unprecedented pace, revolutionizing sectors and creating new opportunities. As we move further into 2024, understanding AI's current landscape and future potential is more critical than ever. This blog post delves into over 63 crucial statistics highlighting the scope, segmentation, and impact of AI across various industries to help you conceive your marketing strategy accordingly. Market Size Statistics for the AI Industry Current and Future AI Market Size, Growth Rates, and Projections 1. The global AI market size was valued at $150.2 billion in 2023 (Source: Fortune Business Insights Report). 2. The global AI market was close to $208 billion by the end of 2023 (Source: MarTech). 3. The global AI market is projected to reach approximately $500 billion by 2024, demonstrating a compound annual growth rate (CAGR) of around 20.1% from 2020 to 2024 (Source: MarketsandMarkets, 2021). 4. The global AI market is expected to exceed $1 trillion by 2028, with an expected growth of 40% from 2023 to 2028 (Source: Exploding Topics Blog). 5. The global AI market size is projected to reach $1.345 trillion by 2030, with an expected growth of 36.8% from 2023 to 2030  (Source: Fortune Business Insights Report). 6. The generative AI market size reached $44.89 billion globally and $16.19 billion in the U.S. in 2023 (Source: Exploding Topics Blog). 7. The generative AI market is expected to show an annual growth rate of 24.4% from 2023 to 2030, resulting in a market volume of $207 billion by 2030 (Source: Exploding Topics Blog). Regional & Worldwide Market Insights 8. North America held the largest market share in the AI market in 2023 (Source: Fortune Business Insights Report). 9. The North American AI market is expected to reach approximately $200 billion by 2024 (Source:  Grand View Research, 2021). The presence of major tech companies and high adoption rates of AI technologies contribute to this dominance. 10. The Asia-Pacific AI market is projected to grow rapidly, reaching $120 billion by 2024, with significant investments in AI infrastructure by countries like China, Japan, and South Korea (Source: IDC, 2021). 11. The AI market in Europe is expected to reach $80 billion by 2024, driven by government initiatives and investments in AI research and development (Source: European Commission, 2020). AI Market Segmentation Which segment dominates the AI market by component? 12. The software segment is expected to dominate the AI market by component due to the rising adoption of AI services and government initiatives promoting AI technology (Source: Fortune Business Insights). 13. The AI software segment alone is expected to generate revenues of about $126 billion by 2024. This includes applications in various domains such as machine learning, natural language processing, and robotic process automation (Source: Statista, 2023). 14. The machine learning segment is forecasted to dominate the AI market, accounting for around $100 billion by 2024. This includes applications in predictive analytics, autonomous vehicles, and smart robots (Source: Allied Market Research, 2021). 15. The Natural Language Processing (NLP) market within AI is expected to reach $30.5 billion by 2024, fueled by the rising demand for virtual assistants, chatbots, and speech recognition systems (Source: Research and Markets, 2021). 16. The computer vision segment is projected to grow to $50 billion by 2024, driven by its applications in sectors such as automotive (autonomous vehicles), healthcare (medical imaging), and retail (visual search) (Source: MarketsandMarkets, 2021). AI and Job Market 17. By 2030, 11.8 million workers will need to change occupations due to job losses in roles like clerks (down 1.6 million), retail salespersons, administrative assistants, and cashiers, with an increasing demand for higher-skilled jobs (Source: McKinsey). 18. AI is expected to automate 30% of hours worked today by 2030, potentially impacting 300 million full-time jobs globally. However, AI will also create new job roles and opportunities, leading to a net gain in employment in many sectors (Source: McKinsey - Generative AI and the future of work in America). 19. New job roles expected to emerge due to AI adoption include AI ethics officers, machine learning engineers, AI trainers, data scientists, and AI project managers. These roles will be critical in managing, developing, and implementing AI technologies across various industries (Source: World Economic Forum). 20. Approximately 35% of employees will need reskilling and training to adapt to new AI tools and technologies as automation increases and the nature of jobs evolves (Source: O'Reilly). AI adoption per industries and Use How do different industries compare in terms of AI adoption rates? Different industries show varying levels of AI adoption: 21. Financial Services and Banking: 70%. This industry also has a high adoption rate, using AI for fraud detection, customer service, and personalized financial advice (Sources: McKinsey). 22. Retail and E-commerce: 55%. Retailers use AI for personalized marketing, inventory management, and customer service (Sources: McKinsey). 23. Healthcare: 60%. AI adoption is growing for diagnostics, patient care, and operational efficiency (Sources: McKinsey). 24. Marketing: In 2023, the adoption rate of generative AI in marketing saw significant growth. 65% of organizations were regularly using generative AI in at least one business function, with a notable increase in marketing and sales applications (Source: McKinsey). 25. Manufacturing: 50%. AI is increasingly used for predictive maintenance, quality control, and supply chain management (Sources: McKinsey). 26. Technology and Telecommunications: 45%. These sectors have the highest AI adoption rates due to their intrinsic focus on innovation and digital transformation (Sources: McKinsey). AI in Healthcare 28. The AI market in healthcare is projected to grow to $45.2 billion by 2024, with a CAGR of 44.9% (Source: Markets & Markets). 29. Key applications driving this growth include diagnostic imaging, personalized medicine, and drug discovery, patient management systems, and robotic surgery, (Source: Frost & Sullivan, 2021). 30. AI in the healthcare market is expected to reach $68 billion by 2032 (Source: Fortune Business Insights). 31. AI-powered diagnostics use patient history to flag health conditions needing further investigation (Source: PwC Global FinTech Report, 2020). 32. Around 60% of healthcare providers are implementing AI in various Capacities (Source: Accenture, 2021). 33. AI systems have shown to improve diagnostic accuracy by 30-40% in radiology and pathology (Source: Accenture, 2021). 34. AI has helped reduce hospital readmission rates by 15-20% (Source: Accenture, 2021). AI in Retail 35. AI applications in the retail sector are expected to reach $20.05 billion by 2024. The growth is driven by demand for enhanced customer experiences, supply chain optimization, and personalized marketing (Source: PR Newswire, 2021). 36. The retail AI market is projected to grow at a CAGR of 30% from 2023 to 2030 (Source: Global Market Insights). 37. Retailers use deep learning to predict customer orders in advance (Source: PwC Global FinTech Report, 2020). 38. About 55% of retailers are leveraging AI to enhance various operations. 39. AI Applications in retails are personalized marketing, inventory management, price optimization, customer service, and supply chain logistics. 40. Retailers using AI for personalization have seen a 20% increase in customer satisfaction and a 15% boost in sales (Sources: McKinsey & Company, 2020). 41. Driven inventory management systems have reduced out-of-stock situations by 30-40%. 42. 58% of U.S. adults are familiar with ChatGPT, but only 14% have tried it (Source: Hootsuite). 43. 21.4% of all generative AI users in the U.S. are aged 25 to 34 (Source: Hootsuite). AI in Financial Services & banking 44. The AI market in financial services is anticipated to be worth $35.4 billion by 2024, with an expected growth of 23.4%. Major uses include fraud detection, risk management, and customer service automation (Source: Business Insider, 2021). 45. AI is expected to increase banking industry revenue by $1 billion by 2035 (Source: Accenture). 46. Robo-advice enables customized investment solutions for mass-market consumers (Source: PwC Global FinTech Report, 2020). 47. Approximately 70% of financial services firms use AI in some form. 48. AI Applications in the Financial services and banking industry are fraud detection, risk management, personalized banking, chatbots, and algorithmic trading (Source: PwC Global FinTech Report, 2020). 49. 80% of banks are projected to have deployed chatbots for customer interactions by 2024 (Source: PwC Global FinTech Report, 2020). 50. AI-powered fraud detection systems have reduced false positives by 50% and improved detection rates by 90% (Source: PwC Global FinTech Report, 2020). AI in Manufacturing 51. Approximately 50% of manufacturing companies have adopted AI technologies (Source: Boston Consulting Group, 2021). 52. AI applications in the manufacturing industry are predictive maintenance, quality control, supply chain optimization, and robotics. 53. AI-enabled predictive maintenance has reduced maintenance costs by 10-20% and downtime by 30-50% (Source: Boston Consulting Group, 2021). 54. AI systems have improved defect detection rates by 90% (Source: Boston Consulting Group, 2021). AI in Telecommunications 55. The AI telecommunications market was worth $2.5 billion in 2022 (Markets and Markets). 56. Google Assistant has an accuracy rate of 98% for navigation queries (Loup Ventures). 57. Around 45% of telecom companies are utilizing AI (Source: Gartner, 2021). 58. AI’s applications in the Telecommunication industry are network optimization, customer service automation, predictive maintenance, and fraud prevention. 59. AI has helped improve network efficiency by 15-20% (Source: Gartner, 2021). 60. AI-driven customer service solutions, including chatbots and virtual assistants, have increased response times by 30% and customer satisfaction by 25% (Source: Gartner, 2021). AI Ethics and Trust 61. Only 39% of U.S. adults believe current AI technology is safe and secure (Source: MITRE). 62. 56% of executives are unsure if their organizations have ethical standards for AI use (Source: Deloitte). 63. 22% of executives cite data privacy as their top concern about generative AI (Source: Deloitte). Conclusion AI is taking over many industries. From healthcare to retail, it's improving how things work and making customers happier. The AI market is growing fast. Big advancements and investments are pushing it to new heights. This isn't just small progress; it's a big change that's transforming businesses. Sundar Pichai said it best: "AI is one of the most important things humanity is working on. It is more profound than electricity or fire." This shows how crucial AI is. If you're a business leader, policymaker, or tech fan, these insights help you understand AI better. AI is just starting, and it's set to change our world in a big way.

The real estate industry has historically lagged in embracing new technologies; however, the advent of generative artificial intelligence (AI) presents an unprecedented opportunity to revolutionize the sector. Zillow’s Journey Mapping illustrates the emotional rollercoaster renters experience throughout their apartment search, from initial excitement to eventual relief, often tarnished by stress and frustration. The disjointed tech in the real estate industry exacerbates these emotions, leaving customers overwhelmed and exhausted. From Zillow Rentals “Today’s Renter Journey” By embracing AI, we can do better. Our customers deserve better. The time is now. A recent report by McKinsey & Company shares that in their experience working with residential operators, those who create memorable brand experiences using data and technology, including generative AI, experience a premium of up to 15%. Additionally, a second report shows that in their work with AI, real estate companies enjoy NOI gains of more than 10% by creating efficiencies, superior decision-making, and enhanced customer experience. Getting caught up in the hype and excitement of future possibilities is easy. Daily, we hear about tools emerging that can handle the most tedious tasks and free up time to tackle the most rewarding parts of our roles. We are still in the early days of AI adoption in the real estate industry. My research indicates that while there is much discussion about AI's potential benefits, concrete case studies, and practical applications are scarce. This doesn't mean companies aren't utilizing AI—examples throughout this article demonstrate that they are. However, the lack of widespread, data-backed examples presents a unique opportunity for your company to explore AI's potential and gain a competitive edge. Before diving in, it’s essential to understand where to start and how to avoid common pitfalls. Current AI Marketing Use Cases in Real Estate 1. AI Chatbots AI-powered chatbots enable property managers to provide 24/7 personalized interactions through chatbots and email campaigns backed by large language models (LLMs). This ensures that prospective renters receive timely and relevant information at every stage of their decision-making process. Today’s renter expects almost immediate responses, yet CRM provider Knock shared that the average response time for the multifamily industry is around 39 hours! With AI chatbots, communication with prospective residents is available around the clock, significantly increasing the likelihood of converting leads into leases. Remember, many renters are at work while your office is open and are actively apartment hunting when your office is closed. Using Respage Chatbot by Respage nationwide property management company Legacy Partners saw impressive results in just one month with a 50% lead-to-tour conversion. During the first month with the Respage Chatbot, 301 prospects engaged after hours, which might have been missed otherwise, and the chatbot saved the onsite team 83 hours of work. 2. Lead Nurturing Leveraging advanced AI tools for lead nurturing can significantly enhance your communication with prospective renters, guiding them seamlessly through the decision-making process. These AI-driven systems ensure continuous engagement, providing immediate and accurate responses to inquiries, carrying on meaningful conversations, and persistently following up with prospects. This approach not only increases the likelihood of conversion but also ensures that leads are nurtured efficiently until they are ready to take action, such as scheduling a tour or applying for an apartment. Once a prospect reaches this stage, the lead is then handed over to a human team member. This transition allows your team to focus on high-value activities that drive occupancy and maximize revenue, thereby boosting overall productivity. For example, PERQ’s AI Leasing Assistant Solution has proven to be highly effective. In a case study with Unified Residential, the company experienced a remarkable increase in website traffic conversion, from 2% to 6.26%, and improved its lead-to-tour conversion rate by 67%, from 50% to 83.49%. Over a 60-day period, their leasing agents saved 162 hours of work, allowing them to concentrate on higher-impact activities. 3. AI For Deliquenceny Follow-up Automating the follow-up process for late payments can improve collection rates and reduce the administrative burden on property managers. Tools like Elise AI can schedule reminders and send personalized rent collection messages to residents. This ensures that delinquent payments are addressed promptly and professionally, improving cash flow and resident relationships while freeing your human team for more impactful tasks and engaging with residents. Elise AI has seen delinquency reductions as high as 52% per quarter when companies use their platform. 4. Custom GPTs for Brands At Scully Company, my team and I manage marketing and leasing for over 40 unique brands across the Northeast and Florida. Each property boasts its own unique personality and distinctive features that attract residents to choose it as their home. To enhance our marketing efforts, we leverage ChatGPT to create content that truly resonates with our customers. By training a GPT on specific details about each community, such as messaging, personas, and psychographic interests, we can craft compelling campaigns and content tailored to what makes each brand unique and appealing to our target audience. Free accounts can benefit from GPT’s in the GPT store. Try the Copywriter GPT - Marketing, Branding, Ads to create on-brand content for your audience. 5. AI Images and Video Generation AI image-generation tools like Midjourney and Dall-E can convert an idea into reality. Using text prompts, you can create a scene to show prospective or current residents what a future space will look like. As AI video tools enter the scene, these visualizations will become even more dynamic, allowing you to create short lifestyle videos, neighborhood walkthroughs, and more. The linked neighborhood walkthrough is an example of what you can create in less than two minutes with one simple prompt sentence using Runway. My prompt was: “Create a realistic video showcasing a group of diverse young professional friends in their 30s enjoying an evening out in Midtown Village, Philadelphia.” You can use a paid account to make longer videos or several short scenes that connect to create a longer lifestyle video. With tools like Archivinci, you can use drawings or text prompts to bring a sketch or simply a vision to life, visualize remodeling ideas, and even test various color palettes for a space. 6. Overcoming Language Barriers Recent Open AI and Google demos showed their new voice-to-voice capabilities, which are equipped with sophisticated natural language processing to facilitate two-way conversations. While translation tools already exist, this technology smoothly translates conversations between people who speak different languages in real-time, allowing seamless communication and even real-time interruptions, as shown in this demo. Picture an English-speaking maintenance technician entering a French-speaking household with a dishwasher issue. ChatGPT 4o’s translation capabilities will allow them to have a fluid and thorough conversation about the problem, quickly giving the maintenance technician the necessary information. 7. Predictive Analytics AI provides actionable insights that help property managers make informed decisions. There is no shortage of data aggregation tools in multifamily; however, these tools still require manual analysis. Marketing teams often must analyze countless dashboards and reports, a manual and time-consuming process. AI tools like Remarkably can automate this burden, prescribing steps to optimize returns and improve the health of campaigns, similar to how a doctor prescribes treatments for better health outcomes. 8. AI Copilot AI chatbots, which traditionally engage prospective residents, are beginning to offer innovative solutions for resident platforms, transforming how we interact and manage our communities. AI chatbots like STAN can assist residents with booking amenities, troubleshooting issues, and responding instantly to common questions. By handling routine inquiries, appointment scheduling, and room booking, AI allows staff to focus on more complex tasks and provide better service. In the near future, I expect chatbots to integrate with property management systems, enabling them to understand each prospect or resident's unique renter journey. These chatbots will then be capable of coaching employees on handling each specific communication or interaction to achieve the optimum outcome. 9. Enhanced Search and Evaluation AI-powered natural language search options like Sunny.com allow potential renters to describe their ideal apartment in their own words. This makes the search process more intuitive and efficient, leading to higher satisfaction rates, more qualified prospective renters, and higher conversions. Renters can search for properties using phrases like “two-bedroom furnished apartment in New York City with lots of natural light” and have their perfect apartment delivered to them. 10. Geo-Targeting and Heat Maps Companies like location intelligence provider Placer.ai analyze geographic data to understand where potential renters are searching from and moving to. This helps in better-targeted marketing efforts and efficient resource allocation. For example, AI can identify trends in migration patterns, allowing property managers to adjust their marketing strategies and investment decisions accordingly. AI Marketing in Real Estate: Near-Future Use Cases 11. Predictive Maintenance AI can identify patterns and forecast when equipment will likely fail by analyzing data from various sensors and maintenance logs. This allows property managers to perform proactive maintenance, reducing downtime and avoiding costly emergency repairs. For example, if data showed that a particular brand of dishwasher has a part that historically fails at 15 months, the platform could alert the maintenance team to check that part at the 13—or 14-month mark, reducing potential damage to your asset and enhancing customer satisfaction. 12. Personalized Resident Experiences AI can gather and analyze data about residents' preferences, habits, and interests, enabling property managers to offer tailored experiences. Understanding resident preferences can help plan community events, provide personalized services, and improve overall satisfaction. This data-driven approach is similar to how websites use cookies to enhance user experience but with the potential for even deeper personalization. Grace Hill quotes an average resident survey response of 10%—30 %, with 50% or higher considered to be excellent—but what about the rest of your residents? What do they want? AI also gives us the power to hear more from quiet voices. 13. Early Prediction of Lease Renewals AI can analyze resident behavior and historical data to predict lease renewals. This allows property managers to proactively address potential issues and engage with residents early, improving retention rates. For example, if AI identifies a resident unlikely to renew their lease, managers can reach out to address concerns, increasing the likelihood of renewal. 14. Enhanced Customer Experience AI-powered apps become a personalized guide for optimizing each individual resident’s day for maximum enjoyment. Think notifications for HVAC recommendations, smart tech that pairs with AI to create grocery lists, based on what’s in the apartment, sending recipe suggestions at the perfect time of day before a resident leaves their office so they can pick up ingredients on their way home, sending proactive reminders to book spaces for special occasions simultaneously increasing opportunities for ancillary income, or reminders to register for community events the resident would enjoy. These features will enhance the overall resident experience, creating life satisfaction they can’t imagine living without and making your community sticky. 15. Customer-Driven Design AI can invite residents to contribute to design choices, feeding their preferences into the system to make informed decisions. We already have virtually staged models. It won’t be long until residents can toggle different furniture or design styles within an image and select their preferred design. An AI system to capture this information could inform architects, developers, and management companies about what selections to make for renovations or other projects under construction with a similar resident base. This also opens ancillary revenue opportunities for a company that might want to partner with a furnishing company. Working in AI Marketing Real Estate? 3 Pitfalls to Avoid Fair Housing Concerns LLMs are trained on content created by humans, and unfortunately, we live in a world where bias exists. Before selecting a generative AI tool, you must question the provider on how the tool will uphold fair housing requirements. Implementing oversight mechanisms and regularly reviewing AI outputs is crucial to ensure compliance, fairness, and equity. In recent news, Zillow has taken an industry-leading step by releasing its open-source Fair Housing Classifier. This tool aims to address the crucial issue of fairness in housing by setting clear boundaries for responsible and unbiased conversations with large language models, such as those used in generative AI tools like chatbots and lead nurture technology. If the classifier identifies a conversation that falls outside of compliance, the system developer can intervene. Most notably, the open-source nature of the classifier makes it freely accessible, allowing companies to easily adopt and contribute to its continuous improvement. AI Hallucinations AI’s primary goal is to achieve user satisfaction- so much so that if an AI does not know the answer, it will make one up. Human oversight is imperative to verify AI outputs and manage misinformation risks. Property managers should know AI's limitations and ensure humans review content and critical decisions. You are liable if your AI provides inaccurate information! In a notable example with Air Canada, the airline’s chatbot gave a customer inaccurate information about bereavement fares. When the customer requested the refund the chatbot described, the airline refused, claiming their chatbot was a separate legal entity and the company was not liable. The case went to court, and the Canadian tribunal found otherwise, requiring the company to reimburse the customer for the difference in fare quoted by the chatbot. Employees Using AI on Autopilot Over-reliance on AI without human oversight can lead to issues. Employees should use AI as a tool to enhance their capabilities rather than as a replacement for their judgment and expertise. I am still waiting to get something from AI that does not need adjusting. You spend so much time, effort, blood, sweat, and tears developing your brand and gaining resident trust. Don’t let improper tool use steal that away. Continuous training and development are essential to ensure staff can effectively collaborate with AI systems and leverage their full potential. Unlocking the Future of Real Estate with AI AI can revolutionize the real estate industry when appropriately used to increase efficiency, enhance the customer experience, and increase revenue. However, innovation in this space requires significant change management and an investment in a team of professionals to craft the customer experience and develop the tools needed to deliver it. Working collaboratively with generative AI requires some trial and error. Think of these tools like a new intern. The more specific directions and follow-up guidance you provide, the better the output. More importantly, even if the output is not perfect, today is the worst AI will ever be. Recognize the future possibilities, and get acquainted with how to use these tools now. Companies that see the value in this approach have an opportunity to strike gold, gain an unparalleled competitive advantage, and position themselves as industry leaders. Remember... 1000 steps start by 1. And today is the best day to start ;).