AI accountability is moving from theory to execution, as organizations increasingly recognise the need for robust governance structures and chains of ownership, according to new research from BSI.
In ‘The rise of AI accountability Who’s in the driving seat?’ BSI says that AI governance has shifted from sitting within ICT or strategy functions to being a board-level and executive concern. Despite this, accountability for AI remains fragmented in most organizations, with responsibility for AI strategy, risk, and oversight often spread across roles and functions, creating ambiguity about ownership, liability, and decision-making, particularly when things go wrong.
Identifying a range of accountability models, BSI suggests that no single ‘best approach’ has yet emerged. Currently, some firms have appointed Chief AI Officers, others have expanded CIO/CDO remits, or given responsibility to federated governance councils or business units. Large enterprises and high-risk sectors such as financial services are moving faster toward formalised accountability and governance.
BSI concludes that good governance is less about someone having a designated title and more about that person or team being empowered, having cross-functional reach, and having the resources and ability to effectively operationalise responsible AI.
Good AI governance is fast becoming a leadership and trust issue, with expectations from regulators, employees, and the public that organizations can demonstrate credible, auditable responsibility for AI outcomes. The time is now to build your AI accountability approach, one that can grow with your business to embrace AI responsibly.
Tim McGarr, Global Head of AI Market Development and Partnerships, BSI
