Source: Gartner
AI Regulations
With AI projected to contribute $15.7 trillion to global GDP by 2030 (exceeding all of UK’s GDP in five years), discussions around regulations were front and center. Currently, there are about 35 AI-related regulations globally, with much more anticipated in the near future. The leading regulation currently is the EU AI Act with Article 5 starting to be nigeria rcs data enforced as soon as February 2025, likely setting a precedent similar to GDPR. In the United States, AI governance regulation is progressing through executive orders, state-level initiatives (e.g., California, Colorado, Maryland, and Illinois), and local measures like NYC 144. Industry-specific regulations are also anticipated, underscoring the need for organizations to stay ahead of compliance requirements.
Source: IAPP
AI Tools
With even more regulatory compliance for AI (and data) on the horizon, it’s also important to note the many tools and technologies available today for different capabilities of AI and AI governance. Sunil Soares categorized these into various vendor groups (in no particular order):
As is helpful with data governance, there are existing frameworks that enable organizations to implement AI governance leveraging the expertise of industry practitioners, large organizations, and public entities. Sunil Soares provides a 13-component framework for AI governance in his free, downloadable book: AI Governance Comprehensive: Tools, Vendors, Controls, and Regulations. Nicole Janeway Bills and John O’Donovan also provided a comparison of seven prominent AI governance frameworks for enterprise use including those from Singapore, Microsoft, the Council of Europe, OECD, NIST, Google, and AWS. This can be found on their Data Strategy Professionals website.