We often hear about how important it is to prioritize sustainability in our efforts to develop and grow AI in business and society, since it overwhelmingly drains precious resources like land, water and power. A new report out from McKinsey & Company offers a different perspective: how public and private funding is flowing toward the UN Sustainable Development Group Goals (SDGs) where AI is perceived to have the greatest potential.
In 2015, all United Nations Member States adopted a 2030 Agenda for Sustainable Development, centered on 17 broad SDGs designed to create a future of peace and prosperity for people and the planet. McKinsey & Company‘s report, out last week, analyzes tens of thousands of data points gleaned from surveys and interviews, and public and private capital investment databases related to global AI from 2018-2023, with some fascinating takeaways. Let’s start with the Exhibit below, which summarizes cumulative funding to the 17 SDGs during the period:
Now, a few takeaways from the exhibit and the report:
Private capital is overwhelmingly driving AI-focused investment in SDGs
Total private capital invested from 2018-2023 totaled $349.4 billion during the 5-year period vs. grants of around $930 million
McKinsey noted that about 40% of private capital investments into the 20,000 AI companies analyzed in the study contributed directly or indirectly toward at least one of the SDGs
McKinsey found that 55% of foundation grants to support AI R&D across SDGs were $250K or less
Public and private funding are directed to different SDGs
The two sources shared just 2 top-five ranked SDGs by funding:
- SDG3: Good health and well-being ranked #1 by both public and private funding
- SDG 12: Responsible consumption and production ranked #3 by public funding and #5 by private investment.
As the charts below illustrate, private investment tends to skew more toward long-term sustainability in business practices, while public funding is focused more on pressing social needs.
Both public and private sources are woefully underinvesting in AI R&D to drive SDG4: Quality education, particularly in low-income countries
While Quality education is the #2 ranked SDG by AI potential overall and among public funding sources (#6 by private investment), investment in this area is still tiny where the need is greatest
The authors point out that one in 20 school-age children from low-income countries has internet access at home today vs. nearly nine in 10 from high income countries
More public-private partnerships are needed to accelerate the deployment of AI for social good
Citing challenges to further scaling AI-focused SDG investing like high costs, intensive training requirements and organizational resistance to adopting AI, the authors propose public and private organizations collaborate to mitigate challenges and accelerate AI deployment
By partnering for reach, data and resources, McKinsey concludes: “Both public and private sector organizations can build innovation ecosystems that bring together stakeholders, generate ideas for AI solutions that target existing issues, and reduce barriers to impact.”
Many thanks to the QuantumBlack, AI by McKinsey and McKinsey & Company Digital Team collaborators on this report, including: Medha Bankhwal Ankit Bisht Michael Chui Roger Roberts Ashley van Heteren
More information about the UN 17 SDGs can be found here: THE 17 GOALS
