Companies need more AI competency at board level, Norway’s wealth fund says

According to a senior official at Norway’s $1.7 trillion sovereign wealth fund, one of the world’s largest investors, companies must do more to address the use of AI at the board level to ensure it is governed effectively and to minimize associated risks.

Norges Bank Investment Fund, which holds stakes in nearly 9,000 companies worldwide, representing 1.5% of all publicly traded stocks, has led in promoting environmental, social, and corporate governance (ESG) practices.

In August 2022, the fund issued guidelines urging the companies it invests in to leverage AI for profit generation, but to do so responsibly. A year later, the fund’s Chief Governance and Compliance Officer, Carine Smith Ihenacho, emphasized that many companies still have a long way to go.

“There’s a significant need for competence building at the board level,” Ihenacho said in a recent interview.

She clarified that this doesn’t necessarily mean appointing a single AI expert to the board, but rather ensuring that the board collectively understands how AI is being utilized within the company. Boards need to establish AI policies and assess whether the technology is being employed responsibly.

“They should be able to answer key questions: ‘What’s our AI policy? Are we operating in a high-risk or low-risk environment? How does AI interact with our customers? Are we being transparent about it?'” Ihenacho added.

Although she did not mention specific companies, the fund has communicated its views on AI to the boards of 60 of its largest portfolio companies, according to a 2023 report on responsible investments.

Last year, the fund highlighted its focus on AI use in the healthcare sector, recognizing the significant impact the technology could have on consumers. Additionally, the fund is closely monitoring Big Tech companies, given their role in developing AI-driven products.

In discussions with these firms, Ihenacho noted that the fund is pushing for the implementation of robust frameworks to understand and manage the risks associated with AI technologies.

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