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AI governance, or the process of defining policies to guide AI development, is a fast-growing market opportunity. A report from StrategyR highlights this, predicting that AI governance software and services could be worth $402 million by 2026, up from $49.3 million in 2020.
“Amid the COVID-19 crisis, the global market for AI governance [has grown significantly],” StrategyR wrote in a press release. “The report presents fresh perspectives on opportunities and challenges in a significantly transformed post-COVID-19 marketplace.”
AI governance adoption
The pandemic forced companies to rethink models used to manage AI risk, but many face continued challenges. According to a Deloitte analysis, as of March, 38% of organizations either lacked or had an insufficient governance structure for handling data and AI models. And a survey by Pegasystems predicts that if the current trend holds, a lack of accountability within the private sector will lead to governments taking over responsibility for AI regulation over the next five years.
Last year, the University of California, Berkeley Center for Long-Term Cybersecurity published a report positing that AI governance has gone through three stages since 2016. The first stage was marked by the release of ethics principles by tech companies and governments, followed by consensus around themes like privacy, human control, explainability, and fairness. The third stage, which began in 2019, is converting principles into practice.
Responsible AI practices including governance can bring major business value to bear. A study by Capgemini found customers and employees will reward organizations that practice ethical AI with greater loyalty, more business, and even a willingness to advocate for them.
This being the case, not all organizations have gotten onboard. In a recent KPMG report, 94% of IT decision makers said that they feel that firms need to focus more on corporate responsibility and ethics when developing their AI solutions. Analysts like StrategyR are betting that emerging laws such as the European Union’s algorithm framework and “AI registries” in Amsterdam, Helsinki, and other cities will spur companies into action, accelerating the demand for AI governance solutions that ease the adoption of best governance practices.
“In jurisdictions worldwide, new policy initiatives and regulations concerning the governance of data and AI signal the end of self-regulation and the rise of new oversight,” researchers at KPMG wrote in the aforementioned report. “As the regulatory environment continues to evolve at traditional pace, leading organizations are addressing AI ethics and governance proactively rather than waiting for requirements to be enforced upon them.”
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