Like many others, I made several predictions regarding the landscape of technology investing in 2023 towards the end of 2022. Nonetheless, the Federal Reserve anticipated that 2023 would signify the commencement of a “new norm” for the markets, with a significant portion of the process software operators employ today being impacted by machine learning, influencing aspects such as curbing inflation and revitalizing the fundraising market.
As we find ourselves in the second year post-pandemic market, rapidly approaching another year, the state of venture capital investment and technology confronts a myriad of factors. Some of these factors echo those of 2023, while others are novel, such as the escalation of interest rates not solely within the market. This scenario necessitates a more robust product-market alignment and underscores the swift evolution of AI technology.
The question arises: Does the landscape we entered in 2023 persist as we reach the conclusion of 2024? Numerous projections abound regarding what we can anticipate in the forthcoming year, ranging from the sluggish first quarter of 2023 to the explosive growth of AI in the subsequent quarter:
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The IPO market remains dormant for the initial half of the year, with a few notable issuances mid-year prompting a resurgence, culminating in the completion of 7 venture-backed software initial public offerings (IPOs). Despite the widespread belief that Klaviyo’s exit would catalyze the public markets, the prevailing environment of elevated prices and geopolitical tensions continues to exert pressure on valuations, delaying IPOs and fostering a tranquil setting in 2024 reminiscent, in some aspects, of 2023. Notwithstanding, a few standout enterprises are likely to propel others forward, particularly in primary software, showcasing commendable device economics and cash flow.
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The momentum of M&A activities intensifies throughout the year, spurred either by enthusiasm or the inevitability of price adjustments due to the anticipated inflation hike. Over the past two years, the average M&A consolidation totaled approximately \(49 billion, a figure set to surpass \)60 billion, predominantly driven by AI acquisitions. Private equity firms have emerged as pivotal acquirers of businesses exhibiting growth rates between 10 and 25%. The stagnation in M&A consolidation value witnessed a decline akin to the dotcom crash and the global financial crisis in Q4 2022. However, as technology markets exhibit resilience and valuations rebound, a subtle shift in the market dynamics ensues, fostering increased M&A activities. In 2023, take-private transactions amassed a total of $50.2 billion, with Coupa and Qualtrics leading the pack.
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The financial landscape remains dominated by AI and data. AI has transcended being a mere entity and has become an integral component or foundation of every product, akin to how smart technology permeated all startups. While Large Language Models (LLMs) are still nascent with substantial room for growth, they have already revolutionized data processing in myriad ways, driving continued demand for VC funding to further enhance data-related advancements. Businesses within this sector will continue to attract investment opportunities. LLMs have revolutionized data manipulation, escalated the demand for data, and fundamentally reshaped organizational frameworks. As technology progresses, we anticipate a surge in novel data materials and data teams.
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The resurgence of interest in web3 funding has been reignited by the Bitcoin ETF. Anticipate witnessing the emergence of the first widely successful tokens offering dividends (likely outside the U.S.) and a proliferation of ARR-based web3 enterprises achieving scalability. The crypto winter compelled numerous companies to pivot towards revenue generation. The forecasted continuation of the heightened web3 activities from 2022 into 2023 materialized, with a projected upswing this year following regulatory decisions in the U.S. regarding Bitcoin ETFs. This development signals a pivotal juncture for web3, affirming the integration of digital assets into traditional finance.
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The value of U.S. venture capital deals plummeted from \(275 billion in 2022 to 2023, stabilizing within the range of \)200 to $230 billion in the ensuing year. With the exception of AI firms, commanding a premium of 10 to 15% over the market, prices are expected to remain relatively steady. While the drastic decline in the number of VC deals between 2022 and 2023 won’t be as pronounced in 2024, the imperative for liquidity and the substantial price drop in 2023 will continue to impede LP reallocation across diverse asset classes.
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The escalating urgency surrounding AI regulation, propelled by swift developments in German regulations, has catapulted the debate on AI regulation to the forefront in the United States. This discourse has emerged as a pivotal focal point in the electoral debates, particularly as machine-generated content and deepfakes fuel escalating media skepticism. The EU AI Act’s implementation may trigger a ripple effect on American enterprises, influencing the broader AI discourse in the U.S. The impending presidential election debates are poised to intensify over President Biden’s executive order on AI, probing the extent to which privately held companies should be subject to regulation, potentially exacerbating partisan divisions.
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As consumer behavior patterns, particularly on mobile platforms, steer innovations, the prevalence of AI-enabled searches is projected to encompass 40% of all consumer searches. The preceding year witnessed a surge in chatbots, personalized content, AI-driven searches, and other AI applications, catalyzing significant transformations on the consumer front. The continued uptick in AI-enabled searches will be propelled by evolving consumer behavior patterns, predominantly in the ecommerce realm, where consumers leverage technology to curate more personalized interactions.
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Businesses, especially startups, report substantial efficiency gains from AI implementations, resulting in diminished workforce expansion while concurrently boosting revenue. The value per worker escalates by 10%, doubling the average growth rate over the past decade. In 2013, the average revenue per worker stood at \(200,000. Presently, for a cohort of publicly traded applications and infrastructure firms, this figure has surged to \)470,000, reflecting a remarkable 135% enhancement. While most enterprises do not experience linear growth in annual revenue per employee, the advent of AI is poised to expedite this growth trajectory, fostering enhanced efficiencies as AI adoption and applications proliferate.
