10 Business Models to Consider When Commercializing Your AI Products

The evolution of Artificial Intelligence (AI) represents not only a technological revolution but a significant shift in how businesses think about their products and services. Just as the steam engine, electricity, and the internet catalyzed new economic structures and business models, AI's transformative power compels us to rethink how we bring products to market.

AI products aren't static; they are dynamic, always learning, and refining their output. Given this, traditional business models may not suffice. Additionally, there may be multiple ways to monetize your machine learning (ML) model. You could be missing opportunities by not exploring what’s possible.

Let’s delve into the heart of AI commercialization, offering you ten business models tailored for AI products. As we venture into this, keep in mind the underlying ethos of these models is adaptability, continuous learning, and providing sustainable value.

Overview of Key Considerations

The allure of bringing AI products to market is the potential for a massive upside. Be forewarned, the costs in additional resources could derail your ambitions. It’s important to explore possible business models to ensure you’ll be able to capitalize on the opportunity.

Before we get into the 10 business models to consider when commercializing your AI products, here are some key considerations:

The Pace of Change

AI technologies are evolving at a staggering speed, making it difficult for static business models to keep up. Imagine building your business on a model that struggles to accommodate the rapid iterations and advancements characteristic of AI. By testing different business models, you open the door to the agility required to navigate the dynamic AI landscape enabling you to have staying power.

Data as the Cornerstone

AI feeds on data, and data, as they say, is the new gold. To harness AI's capabilities, you must center your business model around data collection, analysis, and utilization. Your data strategy is a key component of harnessing the full potential of your AI product.

Value Creation vs. Product Sales

Here's where the paradigm truly shifts. Traditional business models often revolve around selling products or services, whereas AI's value lies in the insights, personalization, and the efficiency it brings to the table. An AI product isn't merely a static offering; it's an evolving entity that continuously learns and adapts. This demands a shift from transactional thinking to a focus on sustained value creation.

Monetization Redefined

Monetizing an AI product isn't a one-size-fits-all endeavour. The intricacies of AI's value proposition requires innovative monetization strategies that go beyond conventional pricing models. Subscription-based services, pay-per-use structures, and even data-sharing partnerships present opportunities to explore revenue streams that align with the unique attributes of AI.

Building Trust Through Transparency

AI products often operate as a black box, leaving customers and stakeholders uncertain about the decision-making process and capabilities. Addressing this requires a novel approach, one that places explainability, accountability, and ethics at the forefront of your business model.

Embrace the Uncertainty

The AI journey is a venture into uncharted territory. Experimenting with business models might seem daunting, but it's essential to remember that AI's potential lies precisely in its ability to challenge and reshape norms. By acknowledging the uncertainty and embracing the dynamic nature of AI, you position yourself to create adaptable, future-ready business models.

10 Business Models to Consider

Let's dive into these business models and discover how they can work for you. Here are 10 examples of business models that can be applied to your AI products:

1. Pay-Per-Outcome Model

Instead of charging customers for usage or subscriptions, this model charges based on the actual outcomes achieved by the AI product. Here are a few examples:

AI-Powered Supply Chain Optimization: Offers AI solutions that optimize supply chain operations, reducing costs and improving efficiency, with revenue generated through a percentage of the cost savings.

Example - Kinaxis provides an AI-driven supply chain platform that helps organizations with demand planning, response management, and supply chain visibility. Their platform enables real-time decision-making and risk management.

AI-Powered Environmental Solutions: Develops AI products that monitor and optimize energy usage or resource allocation for businesses, generating revenue through energy savings or resource efficiencies.

Example - Ceres Imaging utilizes AI and aerial imagery to monitor crop health and optimize irrigation in agriculture. Their solutions help farmers reduce water usage and improve crop yields.

Crowd Sourced Solutions: Users provide the service.

Example - CrowdANALYTIX offers a platform for companies to run AI competitions to solve business problems. Compensation is based on the quality of solutions.

2. Data Monetization

AI products can offer customers free or discounted access in exchange for their data, which is then anonymized and aggregated for resale to third parties, such as research institutions or advertisers.

Examples - Social media platforms, search engines, e-commerce platforms, streaming services, healthcare apps, traffic and navigation apps, fitness trackers, and more.

3. Platform as a Service (PaaS)

A platform that allows other businesses to build and deploy their AI solutions using your infrastructure, tools, and APIs, which can generate revenue through usage fees.

Example - Heroku is a cloud-based PaaS that simplifies application deployment and management. It supports multiple programming languages and offers a marketplace of add-ons for extending functionality.

4. Partnerships

Revenue sharing, affiliate partnerships, or commissions on purchases can be a great way to go. You’ll want to ensure there are clear expectations and agreements in place.

Behavioural Change Incentives: Develops AI products that focus on behaviour modification or habit-building and generating revenue through partnerships with healthcare providers, insurance companies, or employers aiming to improve employee wellness.

Example - Virgin Pulse offers a comprehensive employee well-being platform that encourages employees to engage in healthier behaviours through challenges, rewards, and personalized content. The platform aims to improve overall well-being, including physical health, mental health, and financial wellness of employees of their partner companies.

AI-Powered Personal Styling: Offers AI-driven fashion or design recommendations based on user preferences and body measurements, generating revenue through affiliate partnerships or commissions on purchases.

Example - Stitch Fix is a well-known online styling service that combines AI with human stylists. Users provide input on their style preferences, and an algorithm matches them with a personal stylist who selects clothing items to send to the customer. Users can try on the items at home and purchase what they like, providing feedback to refine future selections.

Ecosystem Enabler: Builds an AI product that supports and enhances other products or services within a larger ecosystem. This can involve revenue sharing or partnerships with other businesses.

Example - Microsoft's Azure platform provides various AI and machine learning services that enable partners to build and deploy AI-powered solutions. This includes Azure Machine Learning and Cognitive Services. Partners can create AI-driven applications and services that integrate with Azure and share in the revenue generated from these solutions.

5. Freemium Model

Offers a basic version of the AI product for free while charging for premium features, advanced analytics, or enhanced customization options.

Example - Canva (one of my favourite platforms!) offers an AI-powered graphic design platform that assists users in creating visuals for various purposes. The free version provides access to basic design tools, templates, and stock photos, while the premium subscription unlocks additional design elements and collaboration features.

6. Licensing AI Models

Licensing out your AI models to other businesses that can integrate them into their own products, thereby diversifying revenue streams.

AI-Powered Creativity: Offers creative AI tools, like AI-generated art or music, that artists can use to enhance their creative process, with revenue generated through licensing or royalties.

Example - Aiva is an AI music composition platform that offers AI-generated classical music compositions. They provide licensing options for various use cases, including film, television, advertising, and video games. Users can access a catalog of AI-composed music and license tracks for their projects.

AI-Powered Content Creation: Develops AI tools that assist content creators, such as writers or designers, in generating high-quality content efficiently, and charge for access to these tools.

Example - The ubiquitous OpenAI offers the GPT-3.5/4 (Generative Pre-trained Transformer) model, which is a powerful AI language model. They provide licensing options to businesses and developers to access and use GPT-3 for various content generation tasks, including natural language text.

7. Data Subscription Services

Providing customers access to high-quality, curated datasets for training their own AI models on a subscription basis.

AI-Powered Subscription Boxes: Curates personalized products or services for customers using AI algorithms that analyze their preferences, delivering a unique subscription box experience.

Example - Churn Buster is a subscription retention platform that uses AI to analyze subscriber data and reduce churn rates. By identifying at-risk customers and implementing strategies to retain them, businesses can maximize the value of their subscription box services.

AI-Enabled Personal Finance: Develops AI tools that provide personalized financial advice, investment strategies, and budgeting recommendations, with revenue generated through subscription fees.

Example - Addepar provides a wealth management platform with AI-powered analytics and reporting tools. Their platform offers insights into investment portfolios and financial performance.

AI in Gaming and Entertainment: Creates AI-enhanced gaming experiences that adapt to players' behaviour, preferences, and skill levels, with potential revenue from in-game purchases or subscriptions.

Example - Newzoo offers data and analytics services for the gaming and esports industries. They provide market intelligence, player behavior insights, and forecasts, powered by AI and data analysis. Subscribers can access reports and dashboards for data-driven decision-making.

AI-Driven Mental Health Support: Offers AI-powered mental health apps that provide personalized coping strategies, mindfulness exercises, and emotional support, generating revenue through subscriptions or partnerships with mental health professionals.

Example - Ginger provides AI-powered mental health support services to individuals and employers. Their platform includes access to behavioural health coaching, therapy, and psychiatry services, often offered through subscription-based plans.

Advisory and Insights: Offers AI-powered advisory services that provide real-time insights to businesses, helping them make informed decisions. Revenue could be generated through a consultancy or subscription-based model.

Example - CB Insights offers AI-driven market intelligence and insights for businesses, investors, and professionals. They provide subscription-based access to data, research reports, and analytics to help users track trends and make strategic decisions.

8. AI-Based Marketplaces

Offers a platform for AI developers to showcase their skills, connect with potential clients or collaborators, and monetize their AI models and services. Businesses, on the other hand, can access a wide range of AI solutions and expertise to address their specific needs and challenges.

Example - DataRobot's AI Marketplace connects AI developers with organizations looking for AI solutions. Developers can list their AI models, and businesses can access and integrate them into their projects.

9. AI-Powered Upselling

Implements AI to analyze customer behaviour and preferences, automatically suggesting relevant upsells or complementary products at checkout.

Example - Netflix uses AI to analyze user viewing history and behavior to recommend movies and TV shows that users are likely to enjoy. This keeps subscribers engaged and encourages them to continue using the service.

10. Volume

AI-Enhanced Customer Service: Provides AI-driven chatbots or virtual assistants that enhance customer service interactions, charging businesses based on the volume of customer inquiries or successful resolutions.

Example - Zendesk offers AI-powered customer support solutions, including AI-driven chatbots and virtual assistants. They charge businesses based on the number of support agents and the volume of customer inquiries.

AI-Enhanced Recruitment and HR: Provides AI tools for companies to optimize their hiring processes, screen resumes, and conduct initial interviews, charging businesses based on the number of hires made.

Example - Greenhouse offers AI-enhanced recruiting software that includes applicant tracking, interview scheduling, and candidate assessment tools. Pricing is often based on the number of hires and the features required.

In Conclusion

The era of AI demands a departure from the comfort of traditional business models. Embracing AI's potential requires a reimagining of how value is created, data is utilized, and trust is built. It calls for a shift from rigid structures to agile frameworks that can accommodate the AI revolution's rapid pace of change. As AI product managers and business leaders, the challenge lies not just in commercializing AI but in pioneering the future of business itself.

Let's dare to challenge the norm, venture beyond the familiar, and pave the way for AI-driven transformations that transcend convention. The path less traveled might just be the one that leads to unprecedented success in an AI-powered future.

This guide was designed to help you understand the different ways you can bring your AI products to market successfully. In my research I came across many AI product companies that no longer exist while also coming across many that were acquired. As I mentioned at the beginning, the opportunities abound, but the risk is high. Mitigate the risk to your AI products by testing different business models.

To learn about how to set up business model tests for your AI products reach out out to me at Miche Priest