In technology and business, buzzwords du jour continually float in and out of everyday vocabularies. Just as “data-driven” dominated professional conversations and sales pitches a few years ago, the terms “AI-enhanced,” “AI-enabled,” and “AI-first” have become buzzwords in the wake of generative artificial intelligence’s explosion in 2023. Often, these phrases are used interchangeably. However, they carry distinct meanings that significantly reflect a company’s trajectory.
As companies continue finding ways to use AI to enhance business operations, business leaders and investors alike must understand the difference between AI-enhanced, AI-enabled, and AI-first companies.
AI-Enhanced, AI-Enabled, and AI-First Classifications
When we talk about AI-enhanced, we refer to the integration of artificial intelligence as a supplementary feature to improve existing systems, products, or services. The core functionality remains intact, but AI is harnessed to enhance performance, user experience, or capabilities. For instance, consider an AI-enhanced customer service platform utilizing chatbots or AI analysis; AI enhances the service as an operational efficiency but doesn’t define its essential functions.
AI-enabled solutions imply that the systems, products, or services can function with AI, but AI isn’t intrinsically tied to the basic operation. AI-enabled business models use AI to offer additional features or capabilities, providing an enhanced user experience. Consider a smartphone with AI-enabled photography features, showcasing how AI can augment an established product without becoming its focal point.
In contrast, AI-first companies place AI at the core of product development, decision-making, or business processes. AI isn’t merely an add-on; it becomes a fundamental component of the product or system. Companies adopting an AI-first strategy design their offerings with AI as a central element, driving innovation and value from the ground up.
Understanding the differences between AI-enhanced, AI-enabled, and AI-first is critical for various reasons across industries, especially among investors looking to invest in AI-first companies.
Why These Distinctions Matter
For businesses, the differences in these terms influence strategic planning and investment decisions. Research from 2022 found that 51% of executives planned to use AI to increase profit through better use of data or forming new revenue streams, and 67% believed it would transform how they do business. Choosing the right approach impacts resource allocation, product development, and the overall direction of the company. Each approach carries different implications for investment, risk, and organizational skill sets.
In technology and product development, recognizing these differences aligns the role of AI with a product’s goals. An AI-enhanced approach may be suitable for products where AI adds significant value, while an AI-first approach leads to more innovative and disruptive solutions. Additionally, accurate representation of a product’s capabilities is crucial for marketing and consumer communication.
From a consumer standpoint, understanding these terms helps set realistic expectations regarding the functionality and capabilities of solutions that incorporate AI. The better consumers understand what’s included in a product or service, the better decisions they can make about whether or not they want to purchase or use the solution. Transparent communication about the role of AI ensures realistic expectations and builds trust with consumers.
Finally, investors need to grasp these distinctions to assess potential risks and rewards associated with funding AI ventures. Different approaches imply varying levels of innovation, market disruption potential, and resource requirements. Additionally, AI-first companies can face more regulatory scrutiny than their AI-enabled counterparts, impacting privacy, data security, and ethical use — all important considerations for investors.
Noteworthy AI-First Companies
To better understand the significance of these distinctions, let’s explore two AI-first companies in practice. You’ll notice that AI is clearly the core value driver behind their business models.
StoryFit
StoryFit stands out as an AI-first company revolutionizing the storytelling landscape. Using natural language processing and machine learning algorithms to analyze vast amounts of textual data, StoryFit extracts valuable insights for content creators, publishers, and filmmakers.
This approach empowers storytellers to make data-driven decisions, enhance creativity, and optimize their works for specific target audiences. With its AI-first engine at the forefront, StoryFit transforms storytelling into an optimized, AI-first experience.
MetaSoul
MetaSoul pioneers emotion synthesis for AI, pushing boundaries with its AI-first approach. At its core, MetaSoul utilizes advanced AI algorithms to analyze and interpret individual experiences, emotions, and patterns of behavior.
With these artificial emotion conditions, MetaSoul dynamically guides the behaviors of agents, bots, virtual assistants, and generative AI tools to express the AI’s emotional state. This AI-first approach enables MetaSoul to delve deep into the intricacies of artificial emotional intelligence, offering a unique experience for users.
From an investor’s perspective, the allure of data-centric companies is undeniable. These AI-first companies possess a durable competitive advantage and are transformative for entire industries.
If you’re eager to get involved with data-centric and AI-first companies like these while they’re still in the startup stage, Ascend Venture Capital can help. Download one of our informative whitepapers, sign up for our newsletter, or schedule an appointment to talk with our GP and data-centric expert, Dan Conner.
Image by Alessio Ferreti