In the early days of Silicon Valley, VCs maintained control over their portfolio companies by securing a handful of favorable provisions that allowed them to force liquidation events or replace founders when disagreements arose. Flaws in this model were certainly evident. Imbalance and potential misalignment issues existed — VCs could, for example, prioritize their interests over common stockholders. While imperfect, this model curtailed the ‘agency’ issues endemic to public companies. There was little divergence between ownership and control. VCs had the majority financial stake and the ultimate say in decisions, while founders executed their ‘vision’ and led daily operations.
As the checkbooks of more nontraditional investors flooded VC over the past ten years, this governance model succumbed to supply and demand. Between 2010 and 2021, the amount of money flowing into VC more than tripled, and firms competed more with a growing number of venture funds as well as new venture investors, like hedge funds and corporates. Hot competition to get the best deals drove up valuations and investors across the spectrum settled for smaller ownership stakes. With more available capital and investors lining up with their checkbooks in troves, founders got the upper hand in deal negotiations, often securing greater control over decision-making.
Most commonly, this involved investors yielding control through dual-class share structures, giving founders ‘super-voting power’ with Class B shares (typically ten votes per share) while investors held Class A shares (with one vote each). However, as investors vied for deals, some unicorns were able to grant extremely powerful voting rights to founders and insiders, with certain companies issuing shares carrying 30x to even 10,000x votes as ordinary stock.
From a governance perspective, dual-class share structures have attracted some criticism, as founders can gain complete board control despite owning a minority financial stake, creating potential agency conflicts. With more voting power than skin in the game, incentives between founders and VCs can become misaligned. Such risks grew more acute in the run-up to 2021 as many companies accumulated large amounts of venture funding with minimal oversight, leading certain enterprises to veer into dubious territory with financial decision-making, with FTX perhaps emerging as the poster child for such behavior.
However, advocates would argue that visionary founders possess an innate capacity to see around corners, often in a board’s blind spot. Despite several VC governance fiascos (often tied to founders with unleashed control), founder-led companies have experienced immense success. Further, startup lore is rife with tales of hostile takeovers that illustrate the shortcomings of the original VC model. For example, Steve Jobs’ ousting from Apple provides a poignant example of how traditional board dynamics can stifle innovation.
Additionally, many venture firms, like Andreessen Horowitz (a16z) and others, have championed the founder-led approach, emphasizing the freedom to pursue ideas, build great products, and innovate without excessive board interference is necessary for unlocking the outsized value creation potential the asset class is distinguished for. Top-quartile VC IRRs require ‘swinging for the fences.’ Perhaps a tradeoff exists between giving founders the freedom to pursue growth and idiosyncratic ideas and investor control.
While valid arguments support the prevailing governance and voting structure in VC dealmaking of the past decade, governance was largely able to take a back seat as LPs, GPs, and founders benefited from an up-and-to-the-right period of fundraising, valuations, and exits. However, the post-Covid venture landscape has sharply illuminated governance structures’ material implications for stakeholders across the venture ecosystem.
For one, abundant and accessible capital in the private markets means VC-backed companies have ballooned to stratospheric valuations without needing to tap into the IPO well for cash. Today, many private companies with multi-billion dollar valuations arguably inhabit a hybrid place between public and private markets.
The substantial size and economic influence of these companies start to make them look like quasi-public entities. Yet, staying private affords them the luxury of operating under opaque governance structures. For LPs and GPs with large exposures to these unicorns, it should raise questions about the internal controls and processes that exist behind the curtain.
Further, when interest rates reached historic highs in 2022, valuations crashed back down to earth, and many VC-backed companies found themselves quenched for capital as the never-ending cash stream from the ZIRP era abruptly dried up. With many unable to grow into their 2021 valuations and lacking the financials, growth trajectories, and profitability to attract financing at a step-up, boards and founders were (and still are) left with tough decisions to make. Strong governance and board leadership really matter here.
Additionally, as generative AI stands to unlock a major economic paradigm shift, VC funds are flocking to prime opportunities, with capital raised for generative AI startups outpacing all other sectors. However, with many AI startups experimenting with governance structures intended to balance harnessing AI’s potential with mitigating societal risks, it’s crucial to examine the governance dynamics of these companies and their implications.
In Q1 of 2024, down rounds consumed 23% of fundraising activity, up from the 5% low of 2022. As many companies resort to down rounds for capital infusion, a spotlight has shone on the governance dynamics that surface in these transitions, including stakeholders’ fiduciary responsibilities.
Down rounds often entail significant revisions to companies’ economic and governance structures, which can severely impact the equity positions of existing investors, founders, and employees. Conflicts of interest can quickly surface, particularly between VC investors holding preferred shares and founders and employees holding common shares. VCs, in these scenarios, must balance their incentives to maximize returns to their investors with ensuring that other stakeholders are also appropriately aligned to create company value.
For example, reckoning with overcapitalized balance sheets often means navigating capitalization tables stacked with investors and founders with different return horizons and divergent perspectives on the company’s path forward — particularly around exit strategy.
Take the seed investors and late-stage investors of a company last valued at $1 billion. Even if the company’s valuation gets a $500 million haircut, seed investors can still realize significant gains and might have strong convictions about future growth. Investors who came in at $1 billion with protective provisions and a very low chance of realizing a return, however, might prefer to cash out and move on to the next round of bets.
With the disproportionate allocation of capital towards generative AI startups, it becomes important for stakeholders in the space to understand how these entities are recalibrating governance frameworks to balance safety apprehensions, societal impacts, and the need to generate and distribute financial returns.
In a manner consistent with the innovation of their products, AI businesses have pushed the envelope with respect to how a startup can configure its governance structure. Leaders of AI businesses such as OpenAI and Anthropic recognized the extraordinary potential of their new technologies and how it is inseparable from extraordinary responsibility to harness that potential positively. These leaders asked themselves questions like:
OpenAI’s answer to these questions primarily fell into two categories: 1) to put OpenAI beneath the control and ownership of a 501(c)(3) Public Charity and 2) to cap the financial profits of OpenAI to 100x any investment.
These decisions enable OpenAI to theoretically be subject to the nonprofit’s mission: to build artificial general intelligence (AGI) that is safe and benefits all of humanity. The board of directors which governs OpenAI is therefore subject first and foremost to executing this mission rather than pure rapid (and potentially reckless) expansion of OpenAI’s for profit arm.
Secondly, this configuration is careful to hand out financial incentives. OpenAI’s directors are independent and own no financial incentive in the upside of the technology. Further, the for-profit arm caps all returns to investors at 100x. Thus, these incentives recognize the potential of this technology and seek to distribute the value maximally to society as a whole.
OpenAI’s governance choices have been partly blamed for last year’s abrupt ousting of CEO Sam Altman. This highlights the true tension between the mission of creating safe AI and the traditional objective of growing fast and maximizing profits.
Anthropic aimed to solve the same risks and questions but did so through different means. Anthropic structured its business directly as a public benefit corporation, enabling it to balance the maximization of shareholder value alongside the public benefit purpose the Anthropic hopes to see through.
Moreover, Anthropic does not rely solely on the public benefit corporation structure to uphold its mission. To add another layer of governance, it created a Long-Term Benefit Trust governed by five financially independent trustees. These trustees are responsible for appointing and/or removing members of Anthropic’s board of directors and providing more checks and balances.
While these are still new models — even referred to as an “experiment” in Anthropic’s corporate governance documentation — they mark a massive departure from traditional governance structures, forging new frameworks to reflect how transformative technology impacts stakeholders and society. And equally, despite these new and innovative governance structures, venture capital’s unrelenting interest in these companies has unlocked a new way of investing.
With an abundance of unicorns and decacorns on the books of LPs and GPs amid a dearth of exits, proactively identifying and understanding any governance risks becomes essential. Particularly at the late stage, grasping a portfolio company’s board composition, voting rights, the absence of key governance policies, deficiencies in basic internal controls, abnormal senior team turnover, or unconventional accounting practices is paramount for identifying material risks to returns.
However, due to its qualitative and quantitative nature, systematically collecting and aggregating governance data has traditionally posed challenges for sponsors and LPs. For instance, documenting qualitative text describing an incident and policy change over time is necessary to detect patterns or anomalies but can be challenging to aggregate in an efficient, memorialized manner.
Typically stored in email or Excel, this information can easily become siloed, with significant governance risks hidden across various files and systems. By utilizing technology to centralize governance data collection alongside financial and operating reporting, venture capital investors can enhance risk identification across their portfolios.
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