Investing in Generative AI: Opportunities, Risks, and Future Trends

“Write me an 800-word article about ‘How to train a brand new puppy’ and include a CTA for my dog bed at the end.”

“Change the photo of a purse in my hand to a book about finance tips.”

“Check my code and point out any bugs.”

Within minutes, you can receive what you asked for with those prompts.

If someone would have told you it was possible a few years ago, it would have seemed like a sci-fi fantasy.

Generative AI has made it a reality right now.

Generative AI has transformed hundreds of tasks from research to writing to data analytics and coding, the use cases are endless. These tools are transforming processes and productivity in every industry, which is why they’ve also caught the attention of so many eager investments.

But every generative AI investment is not a smart one, there are some critical factors to know before jumping in.

Generative AI: A Growing Segment

The world of generative AI is booming, and it’s catching the eye of investors everywhere. Picture this: by 2030, the generative AI market is set to hit a whopping US$207 billion, growing at a speedy rate of 20.80% each year from 2024.

Now, let’s talk numbers. According to the latest available data, there are around 67,200 artificial intelligence companies worldwide as of 2024.

Many were quick to realize that AI technology was the future, and generative AI is playing a major role. They’re pouring money into it like there’s no tomorrow. A few of the largest generative AI investments in 2023 included:

  • OpenAI received a $10 billion investment from Microsoft.
  • Anthropic raised nearly $7 billion in funding, including a $4 billion round from Amazon.
  • Inflection AI secured a $1.3 billion round led by Microsoft, Reid Hoffman, Bill Gates, Eric Schmidt, and Nvidia.

What Makes Generative AI a Great Investment Opportunity?

Savvy tech investors are referring to AI as the next “it” tech investment opportunity because of its immense promise.

Many investors have already jumped on the opportunity, especially for generative AI. Globally, AI (including generative solutions) has raised over $354.5 billion in funding, with $67 billion coming from the U.S. alone.

Here are a few of the most exciting reasons why:

Impact on Productivity

Generative AI boasts a major opportunity to improve productivity. According to insights from McKinsey, generative AI could impact productivity in a way that adds trillions of dollars to the economy globally. Across the 63 use cases they assessed, it could add between $2.6 and $4.4 trillion per year.

The two primary ways that generative AI can increase productivity are by 1. addressing over 60 organizational use cases (like crafting personalized emails for marketing) and 2. handling 2,100 detailed work activities in over 850 occupations (like communicating with team members about upcoming operational adjustments).

Both ways of viewing generative AI’s potential lead to the same end result: improved labor productivity. The economic benefits of these tools make them extremely valuable to organizations, and thus great investment opportunities.

Impact Across All Industries

Not only does generative AI provide powerful productivity promises, but it also transcends numerous industries and types of tasks.

The industries it will most dramatically impact with productivity improvements include:

  • Banking: 2.8%-4.7% of all industry revenue
  • High tech: 4.8%-9.3% of all industry revenue
  • Pharmaceuticals and medical products: 2.6%-4.5%
  • Education: 2.2%-4.0% of all industry revenue

Within those industries (and many others) 75% of all value comes from improving these functions:

  • Customer operations
  • Marketing and sales
  • Software engineering
  • Research and development

The key, and most exciting, takeaway here is that generative AI has a massive ability to improve numerous core functions across many industries. Its diversity only amplifies its value for investors.

Long-Term Growth Potential

Perhaps one of the most compelling reasons to invest in generative AI is its vast potential for improvement. As AI algorithms and computational power continue to improve, generative AI will become more sophisticated

Given the impact it’s already having globally and across diverse sectors, investing feels urgent. With improvement, it will only become more accurate and able to provide more diverse outputs for image generation, language processing, and more.

AI Wrappers Entering the Marketplace

The rapid and immense success of generative AI tools has excited many investors. Of course, the main name of the game is ChatGPT.

Within two months of its November 2022 release, ChatGPT had already hit over 100 million active users by January 2023.

Unsurprisingly, OpenAI (founders of ChapGPT) was one of the most funded machine learning startups on the planet. They had secured over $1 billion dollars by then.

ChatGPTs incredible success worldwide opened up the possibility for exciting competition. Many tech companies sought to replicate its success with unique consumer-facing applications.

However, instead of working on making a truly unique, bigger, better option, many simply fell into the trap of creating AI Wrappers.

Essentially, AI wrappers operate on the same technology as OpenAI’s ChatGPT. They leverage its technology to offer a specific service or simply craft a more user-friendly UI.

The Faux Pas of AI Wrappers

Many generative AI startups taking the AI wrapper route set themselves up to fail. The main problem is that one simple update from the original company can shatter its unique value proposition.

ChatGPT adding plugins is a prime example. You don’t need a unique AI wrapper anymore to make a spreadsheet, for example. With the doc maker plugin, ChatGPT can handle that for you.

Essentially, when an AI wrapper gains traction, it gives the original company a way to improve its product and reclaim market space.

Investors who excitedly turned to fuel AI wrappers mostly learned the hard way that it’s not the smartest way to invest in generative AI.

Jasper Case Study

A prime example of the AI wrapper faux pas is Jasper.ai. It invested heavily in creating Jasper Chat, a conversational, generative AI (not surprisingly) much like ChatGPT.

In October of 2022, Jasper raised $125 million for a generative AI tool. The tool wrote content based on prompts and later converted text to images as well. At the time, that investment contributed to Jasper’s impressive valuation of $1.5 billion.

Just 9 months later, in the summer of 2023, Jasper laid off an unknown number of employees. They removed positions on LinkedIn and eliminated full-time employees and contractors. During that time, Dave Rogenmoser, Jasper’s CEO shared “difficult news” and articulated Jasper’s plan to re-focus on assisting marketing teams while “reshaping” his team.

Ultimately, Jasper’s problem was that it was just another AI wrapper. It didn’t have anything unique or new, it just sat on another company’s models. As that company (OpenAI) continues to evolve itself, it pushes AI wrappers like Jasper out of the market.

Basically, those who invested in Jasper are probably kicking themselves. They saw something that looked exciting and promising on the surface, but when you dig deeper into what the tool is and how it works, the risk was clear.

A Balanced View on AI Wrappers

While stories like Jasper.ai often cast AI wrappers in a negative light, it’s important to present a counter perspective for a holistic view.

The integration of existing AI models into technology has its time and place, and much depends on the founders’ resources, go-to-market strategy, and ultimately how they communicate to investors.

The Strategic Use of AI Wrappers

AI wrappers, when used strategically, can be a key asset for technology companies. Instead of developing AI models from the ground up, leveraging platforms like GPT-4 allows for focusing on unique applications that set a company apart.

This approach, far from being a mere replication, can bring innovative solutions to the market more quickly and cost-effectively.

Transparency and Accurate Messaging in AI Startups

The responsibility falls on the founders to communicate what their technology is and isn’t. Labeling a company as an ‘AI startup’ can be misleading if it primarily utilizes existing AI models.

A more accurate description might be a technology company that leverages artificial intelligence to achieve specific outcomes. This transparency in messaging helps establish trust and sets realistic expectations with both investors and consumers.

Finding Unique Value in AI Integration

The key for startups using AI wrappers is to demonstrate how they use generative AI models to achieve outcomes more effectively or innovatively than existing consumer-facing applications. The focus should be on the unique value proposition: how their particular use of AI makes a difference, fills a gap, or improves upon what’s already available in the market.

Navigating the AI Wrapper Landscape

The Jasper.ai story serves as a cautionary tale, but it doesn’t represent the entire spectrum of AI wrapper applications. For startups, the successful use of AI wrappers lies in strategic integration, clear messaging, and a strong focus on delivering unique value. As the generative AI field evolves, discerning and innovative use of existing AI technologies, coupled with transparent communication, will be key to carving out a niche in this competitive landscape.

How to Determine The Best Generative AI Investments

Hindsight is always crystal clear, but you don’t need a major loss to inform generative AI investments.

With proper due diligence, you can reduce the chances of a poor AI investment and opt for truly promising tools.

Evaluate Proprietary Data Sources

Question: Does the application have proprietary data sources?

Very few AI startups have proprietary data sources. Without a unique data source, the tool does not have a strong unique value proposition. In essence, other tools can replicate its offering, rendering it unnecessary.

AI “wrappers”, or tools that leverage another tool’s data source/model are more likely to fail in the long run, even if they garner attention initially. For this reason, investors should carefully assess the data source, and opt for tools that leverage a proprietary data source.

Original AI vs Reliance on Existing Models

Question: Has the company built a unique model?

In addition to assessing the data source, investors should also consider the model that the tool uses. It’s possible for a generative AI tool to provide unique value while using a previous data source if that tool leverages a unique model.

Cost-Efficiency

Question: Is it more cost-effective than models like GPT-4 or Claude 2?

Generative AI tools offer a major opportunity to improve productivity and save money on many tasks in endless sectors. But they are by no means cheap to produce or maintain.

Cost efficiency is a major concern for these tools. Analysts estimate that it could cost over $4 million to train a large language model like Chat GPT-3, for example.

Therefore, all investors should consider how cost-effective the tool is. Is it less expensive to develop and maintain than big players like GPT-4? Or is it more expensive?

Assess Unique Differentiator

Question: Is there a strong enough differentiator and supporting market to attract consolidation with another AI lab or enterprise?

The big quality that investors must assess is the unique differentiator that a tool offers. A unique differentiator helps to ensure longevity and a greater likelihood of success.

Furthermore, the tools with a stronger unique differentiator and supporting market are more likely to be attractive options for consolidating from other AI enterprises or labs.

Strategic Considerations for Investment

In addition to selecting the right tool, investors must also consider other strategic considerations for investing in generative AI.

Leveraging an External Technology Counsel in Investment Decisions

One of the simplest ways to ensure a smart investment strategy in generative AI is to consult experts. An external technology counsel can help you better understand how the tool works, and if it offers a unique value proposition.

Without specific AI experience, it can be hard to determine if the tool operates in a unique way or via a proprietary data source. Technology experts bring the knowledge you need to evaluate potential tools.

Assessing the Potential for Acquisition and Market Consolidation

As mentioned, AI tools with a unique value proposition offer an important potential for acquisition and market consolidation. Investors should consider opportunities for acquisition and consolidation.

Strategic partnerships in AI offer many critical benefits including:

  • Combine diverse expertise
  • Foster innovation
  • Enhance product development
  • Enable risk-sharing
  • Expand market reach
  • Provide access to unique datasets

Ultimately, the right partnerships can ensure better returns in the AI industry the same way they do in other forms of investments.

Evaluating the Long-Term Viability and Scalability of AI Technologies

Investors must also evaluate the long-term potential of AI technologies. The best investment strategies aim to tap into the full long-term potential of the tool.

Consider how the AI system can adapt to evolving data, and how to integrate it with emerging technologies. Sustainability is a key consideration for operational models, as the tools must handle increasing data volumes and user demands without compromising performance.

Ethical considerations also play a role in long-term viability, including regulatory compliance and the ability for continuous learning.

You must ensure that the tool remains relevant and effective in addressing future challenges and opportunities.

The Era of Generative AI is in Its Infancy

As the McKinsey report outlines, “the era of generative AI is just beginning.”  The untapped potential is brimming, and savvy investors must always think ahead.

In the future, generative AI will be part of new businesses and services that do not yet exist. For example, before there was electricity, there were no computers. No stores selling lighting for homes or Christmas trees. No blow dryers or refrigerators or clothes dryers.

Electricity completely changed the world as we know it, sparking so many new inventions, products, and services. Generative AI will do the same.

Investors must aim to get ahead of this, to invest in solutions that do more than improve existing workflows. The best generative AI investments are those that push past our current boundaries and begin to uncover brand-new opportunities.

Expert Guidance for Investors and Founders in AI

Are you an investor seeking to conduct thorough due diligence on AI applications, or a founder aiming for standout product differentiation to attract funding? Contact us for expert guidance and insights to navigate the generative AI landscape successfully.