As artificial intelligence (AI) gains momentum, a wave of profound change is rippling through businesses and society. With its ever-evolving capabilities, the revolutionary nature of AI is propelling us into an era where AI-driven advancements are set to permeate every aspect of our lives. Its disruptive capabilities offer latest avenues for a wide range of startups which require investment, but not with out a range of emerging risks and unprecedented challenges that require thoughtful management and adaptation.

Initial, standard AI systems learn and adapt to their environments by synthesizing information from large data sets to make decisions and predictions. Lots of these AI systems are limited to performing specific tasks to succeed in a selected end result. Generative AI systems, then again, design latest content in the shape of text, images, or music by creating content much like examples from an information set. Moreover, the recognition of ChatGPT has ignited a world fascination with the facility of generative AI, resulting in its rapid adoption.

The recent surge within the efficiency of AI will be attributed to remarkable advancements in computational power, data availability, and machine learning techniques. The decreased cost and time related to storing, transferring, and processing massive amounts of knowledge have made each standard AI and generative AI economically viable. Coupling this phenomenon with advanced tracking of knowledge and accessibility to diverse data sets has created countless use cases for AI in every industry. In actual fact, using AI models has greater than doubled from 2017 to 2022.¹ This growth is generated as business leaders use AI to alleviate skill shortages, boost productivity, and innovate services.² As an example, corporations like Glossai, a NECP portfolio company, are revolutionizing marketing by automating content creation and enabling personalized experiences at scale. One other NECP portfolio company, aiOla, uses voice recognition to convert speech into digestible data to expedite and elevate tasks starting from food inspections to customer support.

This transformative potential has not gone unnoticed by business leaders and entrepreneurs, who recognize generative AI’s ability to revolutionize software development, marketing, and data evaluation. The investment landscape reflects this growing interest, with enterprise capital funding in generative AI increasing by 425% since 2020, reaching a powerful $2.1Bn.³ Tech giants like Microsoft and Google have also made substantial investments, further validating the immense market potential. In 2023, Microsoft invested $10Bn in OpenAI, while Google invested $300M in Anthropic, a number one generative AI developer.⁴ With the generative AI market projected to succeed in $60Bn by 2025⁵, investors are desirous to capitalize on this emerging field.

Nevertheless, this surge in generative AI investments has risks that closely resemble those of past technological boom-bust cycles just like the 2000 dot-com bubble. In the same manner, valuations of generative AI corporations often hinge on assumptions surrounding the widespread implementation of AI, overlooking the indisputable fact that some applications are still unproven. Moreover, AI startups are commanding a 15%-50% premium over other startups, driving valuations even higher. Despite this, 40% of corporations classified as AI startups in Europe don’t actually use AI technology in a big way.⁷ This poses a big risk to investors who may pay a premium for an organization that’s mistakenly described as an AI startup.

One other risk around generative AI surrounds bias, incorrectness, and mental property infringement.⁸ As an example, one study⁹ highlights that 97% of DALL-E 2’s images depicting positions of authority, corresponding to “CEO” or “director,” featured white men, while real-world statistics indicate that 88% of Fortune 500 company CEOs, CFOs, and COOs are white men in line with a 2022 survey. One other MIT study estimates significant error rates throughout the top 10 AI data sets, highlighting concerns over the impact that flawed testing data can have on real-world deployment.¹⁰ Finally, there are lawsuits underway alleging unauthorized use of copyrights to coach AI systems which can result in substantial infringement penalties. Waves of regulation are starting to crack down on these missteps which poses a risk for AI corporations. For instance, the EU’s AI Act will issue fines and forestall the sale of AI technology that’s discriminatory, fails usually data protection, and makes biased decisions about lifestyle points corresponding to employment or healthcare. As considered one of the primary pieces of AI regulation, many non-EU corporations will comply with the law making it the world’s de facto AI regulation.¹¹

To navigate these risks, Recent Era Capital Partners developed an AI assessment framework to enrich current due diligence processes. This AI framework helps distinguish between add-on features which leverage AI and fully fledged AI businesses. It also assesses an AI company’s ability to generate revenue in a highly dynamic, nuanced, and competitive market. Using a six pronged approach, NECP is capable of determine the vitality of AI startups:

By employing this framework, NECP invests in AI startups that display tangible use cases, comply with emerging regulatory frameworks, and utilize AI in durable and progressive ways. This approach enables them to harness the transformative power of AI while mitigating associated risks. With this in mind, NECP invites you to hitch us through a series of articles that delves into the AI landscape in each the US and Israel. As we explore the impact of AI on business and society, and showcase real-life examples of NECP’s AI investment framework in motion, we hope to listen to your worthwhile insights as we navigate the frontiers of AI together.

This blog post was co-authored by John Malloy, intern at Recent Era Capital Partners, and Ziv Conen, Partner at Recent Era Capital Partners.

The authors want to thank Avi Kapadia, Shira Gershon, Eugenio Sabbadini, Ran Simha, and Gideon Argov for his or her contributions to the post.

1 What’s AI? | McKinsey
2 AI Adoption Skyrocketed Over the Last 18 Months (hbr.org)
3 Generative AI: The Recent Frontier For VC Investment (forbes.com)
4 Google Pronounces Bard, Its Rival To Microsoft-Backed ChatGPT (forbes.com)
5 What’s Generative AI and How Does it Impact Businesses? | BCG
6 VCs attempt to parse through the ‘noise’ of generative AI | PitchBook
7 Forty Percent of “AI Startups” in Europe Don’t Actually Use AI | HEC Paris
8 FTC Report Warns About Using Artificial Intelligence to Combat Online Problems | Federal Trade Commission
9 Stable Bias: Analyzing Societal Representations in Diffusion Models (arxiv.org)
10 AI datasets are full of errors. It’s warping what we find out about AI | MIT Technology Review
11 Our quick guide to the 6 ways we will regulate AI | MIT Technology Review