Is Launching an AI Business in 2024 Worth It?

I’m going to spoil the ending of this blog to start: the answer is yes. Launching an AI business in 2024 is one of the biggest opportunities available to entrepreneurs tight now. AI has completely transformed nearly every industry over the last year. Many of the largest tech companies have pivoted their entire business model to deploying Large language models (LLMs) on top of their existing products. If you are an online entrepreneur right now, the cost of missing out on claiming your piece of the AI revolution will almost certainly be high — perhaps higher than any other technological transformation in the past.

Trends and Predictions

It can be hard to determine where exactly you might fit into this ever changing landscape. New tools are being introduced almost constantly. Many fear that they’ve already missed their opportunity to claim their slice of the pie. However, we think there are some trends which disprove this thinking.

Adoption

According to McKinsey, the largest users of AI tools are (predictably) in the technology, media, and telecom industry — and still, only 33% of survey respondents reported “regularly” using these tools for work [1]. This means that (at least) 2/3rds of workers have yet to find the killer use case for these tools in their day to day life. This is an incredibly huge opportunity for entrepreneurs who are committed to uncovering what this massive group of middle-adopters are looking for out of these tools.

Agents

One of the biggest trends for AI in 2024 is the creation of agents, a blend of AI and automation, significantly propelled by advancements in Large Language Models (LLMs). These AI agents, akin to skilled individuals mastering specific tools, are evolving through distinct phases towards autonomous functionality. The journey starts with the accessibility of LLMs, advancing through prompt engineering and the integration of internet and APIs, leading to skill-connecting agents capable of selecting and applying various skills to solve problems.

Future phases envision comprehensive build agents that autonomously assemble necessary components for tasks, incorporate episodic memory for long-term projects, and ultimately evolve into primitive Artificial General Intelligence (AGI) systems. This progression highlights a move towards continuous self-learning agents, marked by their ability to independently acquire new skills and knowledge, showcasing the potential for AI to autonomously execute tasks of increasing complexity and versatility.

 OpenAI has released an agent-like service through their “assistants”, which are bots capable of performing multi-step actions. 

Integrations

GenAI is set to revolutionize the way businesses innovate, particularly as all tools begin to integrate the technology in some way. This transformation is being accelerated by the rise of "no code" platforms (like Make.com or Webflow), which allow for domain experts and creatives to directly harness AI and data analytics without the need for complex coding, provided there is effective governance in place.

To capitalize on this shift, businesses are advised not to merely adapt but to overhaul their existing processes and technologies in favor of AI-centric models that can rapidly transform ideas into tangible outcomes. This entails a comprehensive upgrade of technological infrastructures and data models to accommodate AI's expanding role. As AI becomes increasingly woven into the fabric of daily operations and product offerings, maintaining vigilant oversight and governance becomes crucial to navigating the evolving tech landscape and unlocking the full potential of AI-driven innovation.

5 AI Business Ideas for 2024

Because the use cases are so varied right now, it can be hard to imagine where exactly you might fit in. This is reasonable, especially because there isn’t a playbook for this industry yet. Here are some business ideas which are especially well-positioned to see an explosion in the coming years.

As an important context, you’ll need to understand the difference between agents and automations. As mentioned above, agents are AI-enabled “entities” which can perform tasks semi-autonomously, integrating knowledge and tools depending on what it determines is the best course of action. Agents are still rudimentary technology, and will undoubtedly improve over time. Automations are more fixed in what they do. They apply generative AI consistently at a predetermined place within a workflow. Both offer major opportunities to online entrepreneurs.

1. Customer Support Agents: agents which can take customer requests and systematically categorize or respond to them.
2. Lead Generation Agents: agents which can find sales leads from LinkedIn or elsewhere and engage in meaning lead generation over time.
3. Talent Management: for companies trying to hire employees right now, job listings often receives hundreds (or not thousands) of applications. Talent Management automations can help reduce the effort required to sort through applicants by setting clear parameters which applications must meet.
4. Automated Content Management: the process of generating content requires the coordination of a lot of things, including SEO optimization and writing talent. An automated process can help streamline this process while also guiding the actions of writers.
5. Automated CRM: AI-enabled customer management can allow you to glean new insights from data and create actionable plans for growing your business.

Major Tools

The AI landscape is constantly changing, with the new state-of-the-art technologies being released almost weekly. Almost every major technology company has pivoted towards some sort of AI-powered tool, with some releasing entirely new projects while others have augmented their existing tools with AI features. The landscape can be broken down into two general categories: the LLMs underlying these applications, and the applications themselves. Some companies (like OpenAI) are involved in both, while others have built only one or the other. 

Large Language Model (LLM) Providers: 

OpenAI: a research and development company, and potentially the most significant AI company, it is home to some of the most widely adopted AI technologies today. 

• ChatGPT: a popular chatbot known for its creativity and accessibility (offering a free tier).
• Dalle3: a text-to-image generation engine which has been fully integrated into the ChatGPT program. 
• Whisper: a text-to-speech engine which is accessible through the OpenAI API. 
• Sora: one of the newest releases from OpenAI, this is a text-to-video engine which has produced some incredible results (although it is not available to the public yet). 

Anthropic: Founded by ex-OpenAI members, Anthropic focuses on safe and reliable AI. It is often seen as a major competitor to OpenAI. 

• Claude: a chatbot with a strong focus on factual accuracy, used by companies like Notion and DuckDuckGo.

Google:

• Gemini: recently rebranded from “Bard”, Google’s chatbot offers new features including integration with Google Search, allowing for new ways to avoid hallucinations and factual inaccuracies. Its free version boasts impressive context size, making it powerful for research and information retrieval.

Cohere: Cohere provides various AI tools, including GPT-like language models for different use cases. Their focus is on customization and fine-tuning for specific tasks, offering flexibility for developers.

• Coral: an AI chatbot which can search the web to cite sources. Great for research and citations. 

Applications:

• Microsoft Copilot: described as a “processing and orchestration engine”, it is powered by OpenAI’s latest models. It can be thought of more as an AI personal assistant, meant to integrate with other Microsoft 365 apps to help streamline productivity. 
• Jasper: An AI writing assistant that helps with marketing copy, blog posts, scripts, and more (uses various large language models like GPT-3).
• Github Copilot: Similar to Microsoft Copilot, an AI assistant for programmers that completes code and suggests functions directly within Github (also uses OpenAI's Codex).

Creative Tools:

• Runway: A platform for creating AI-powered videos and images, offering tools for photorealistic editing, text-to-video generation, and more (leveraging various AI models)
• Synthesia: Creates realistic AI-generated videos with people speaking your script, ideal for marketing, e-learning, and communication (based on deep learning technology)
• Tldraw: an experimental image and UI generation tool. Checkout makereal.tldraw.com to watch UI drawings come to life (with copyable HTML!) ‍
• Dreamwave: An AI research lab building next-gen AI creative tools. Dreamwave has a multitude of product offerings, including a next-gen AI headshot generator, corporate headshots for teams, a creative AI photo generator and a free AI headshot generator.

Productivity Tools:

• Grammarly: An AI-powered writing assistant that checks grammar, spelling, plagiarism, and suggests stylistic improvements.
• Todoist: A task management app that uses AI to predict user behavior and prioritize tasks accordingly.

Conclusion

Launching an AI business in 2024 not only represents a massive opportunity but is also a call to action for entrepreneurs to be at the forefront of technological innovation. The trends and tools mentioned above illustrate the vast potential for new ventures in this space. Whether through the development of AI agents, leveraging major AI platforms, or innovating with AI-driven business ideas, the landscape is ripe for those ready to dive in. Embracing AI now could very well define the future success of your entrepreneurial journey.