Most LPs in venture capital funds are yet to develop a full understanding of the ESG risks related to AI, according to research from VentureESG.
VentureESG conducted interviews with 26 asset allocators with significant exposure to VC and a combined AUM of more than $1.5 trillion. It also surveyed a further 13 allocators with a combined AUM in VC of almost $80 billion.
Despite AI start-ups receiving 22 percent of VC financing in 2024, only 19 percent of investors consider themselves to have sufficient knowledge of the ESG risks posed by AI and data, the survey found.
While understanding is lacking, investors are at least aware that such risks exist: 75 percent of survey respondents acknowledged that negative externalities caused by data and AI technology pose a significant long-term investment risk.
VentureESG also found respondents frequently confused the ESG risks of AI companies with the potential for positive impact.
Private markets participants across all asset classes are getting up to speed on the ESG issues associated with AI. Delegates at last year’s Responsible Investment Forum: West heard about the risks GPs and LPs are anticipating and evaluating as AI is incorporated into their firms’ operations and their portfolios. IP infringement, data privacy, bias and discrimination in algorithms, as well as the carbon footprint associated with AI’s heavy energy requirements, were all cited as areas to consider.
The rapid advance of AI is already impacting the environment through the proliferation of data centers, which consume massive amounts of electricity, very little of which comes from renewable sources. Global data center energy consumption is expected to rise from 500 terawatt hours in 2023 to as much as 1 petawatt hour by 2026 — more energy used than France and Germany combined, as Venture Capital Journal has previously reported.
To assist ESG teams, there are several voluntary frameworks that can be used to manage these risks, such as the EU’s AI governance framework and the framework by the US’s National Institute of Standards and Technology.
Decision-useful
Venture capital is generally considered to have less developed ESG practices compared to asset classes focused on more mature companies or projects. VentureESG’s research suggests that this is still the case.
While ESG reporting has become commonplace, particularly in Europe, comparatively few LPs are using the data collected to inform their future decision making. Almost two-thirds (63 percent) of respondents require fund-level ESG reporting from their GPs, but only 30 percent are using the data collected to influence investment strategies or re-upping decisions.
VentureESG is a non-profit focused on helping VC firms integrate ESG practices into their processes. Its merger with ESG_VC, another organization pursuing similar goals, was announced last month.
Most LPs in venture capital funds are yet to develop a full understanding of the ESG risks related to AI, according to research from VentureESG.
VentureESG conducted interviews with 26 asset allocators with significant exposure to VC and a combined AUM of more than $1.5 trillion. It also surveyed a further 13 allocators with a combined AUM in VC of almost $80 billion.
Despite AI start-ups receiving 22 percent of VC financing in 2024, only 19 percent of investors consider themselves to have sufficient knowledge of the ESG risks posed by AI and data, the survey found.
While understanding is lacking, investors are at least aware that such risks exist: 75 percent of survey respondents acknowledged that negative externalities caused by data and AI technology pose a significant long-term investment risk.
VentureESG also found respondents frequently confused the ESG risks of AI companies with the potential for positive impact.
Private markets participants across all asset classes are getting up to speed on the ESG issues associated with AI. Delegates at last year’s Responsible Investment Forum: West heard about the risks GPs and LPs are anticipating and evaluating as AI is incorporated into their firms’ operations and their portfolios. IP infringement, data privacy, bias and discrimination in algorithms, as well as the carbon footprint associated with AI’s heavy energy requirements, were all cited as areas to consider.
The rapid advance of AI is already impacting the environment through the proliferation of data centers, which consume massive amounts of electricity, very little of which comes from renewable sources. Global data center energy consumption is expected to rise from 500 terawatt hours in 2023 to as much as 1 petawatt hour by 2026 — more energy used than France and Germany combined, as Venture Capital Journal has previously reported.
To assist ESG teams, there are several voluntary frameworks that can be used to manage these risks, such as the EU’s AI governance framework and the framework by the US’s National Institute of Standards and Technology.
Decision-useful
Venture capital is generally considered to have less developed ESG practices compared to asset classes focused on more mature companies or projects. VentureESG’s research suggests that this is still the case.
While ESG reporting has become commonplace, particularly in Europe, comparatively few LPs are using the data collected to inform their future decision making. Almost two-thirds (63 percent) of respondents require fund-level ESG reporting from their GPs, but only 30 percent are using the data collected to influence investment strategies or re-upping decisions.
VentureESG is a non-profit focused on helping VC firms integrate ESG practices into their processes. Its merger with ESG_VC, another organization pursuing similar goals, was announced last month.
