A.I. presents significant risks to organizations regardless of whether they use the technology. There are potentially enormous reputational risks to an organization when technology like generative A.I. reaches a point where it is impossible to distinguish between actual evidence of corporate bad acts and deep fakes intended to harm the organization. This creates a novel set of risks for the organization, regulators, and the general public alike.

A.I. is also an accelerant to other risks. Generative AI could eliminate the awkward language in phishing email attempts that often make them easier to detect. That would allow foreign bad actors to level up their efforts in any language without many of the current telltale red flags. Generative A.I. has already passed the tests given to Google applicants, meaning that any bad actor now has an entry-level Google coder at their disposal to create all kinds of new malware. While there are guidelines designed to limit this type of result, bad actors will likely find workarounds.

The “simplicity risk” factor becomes far more concerning when A.I. is daisy-chained together. Just as the hurdle of linking large non-standardized distributed data sets used to be a natural brake to A.I. prep work, having one A.I. technology work on removing barriers for another A.I. technology could mean developing new models generated by A.I. with no explainability. With  A.I. having such low barriers, if that becomes the front door to creating other, more sophisticated technology, the path is set to have A.I. build A.I., which is an incredibly risky situation.

Organizations need A.I. GRC to ensure the responsible, practical, and appropriate use of A.I. technologies. A.I. GRC enables the organization to:

  • Ensure A.I. systems comply with evolving laws and regulations helps prevent legal issues, financial penalties, and damage to reputation.
  • Manage uncertainty and risk when A.I. can have unintended consequences, including biased decisions or privacy breaches. Effective risk management helps identify and mitigate these risks.
  • Meet ethical standards, ensuring A.I. is used fairly and doesn’t perpetuate harmful biases.
  • Deliver trust and transparency where A.I. GRC practices help organizations demonstrate that their A.I. systems are trustworthy and transparent, essential for customer and stakeholder confidence.
  • Provide strategic business alignment where Strong A.I. GRC ensures that A.I. usage aligns with an organization’s broader strategic goals and doesn’t deviate into potentially harmful or unproductive areas. 
  • Enable agility as the A.I. landscape rapidly changes; A.I. GRC practices help organizations prepare for future regulatory changes. 

A.I. GRC is necessary to ensure legal adherence and uphold ethical standards, manage risks, build trust, align with strategic goals, and prepare for the future. Organizations need A.I. GRC to ensure responsible and ethical use of A.I. technologies. 

Without a structure to govern A.I., risk exposure will grow, resulting in bad decisions from improper use, increased regulatory pressure, and legal liability and exposure. Organizations should not see A.I. GRC as simply a regulatory obligation; A.I. governance enables strategic decision-making and performance management. Short-term A.I. risk management projects may pass regulator scrutiny but fail in the long run to effectively manage risk and performance effectively.

To effectively govern A.I., organizations need a structured approach to:

  • A.I. GRC Oversight. A well-defined A.I. governance framework to manage A.I. use that brings together the right roles, policies, and inventory.
  • A.I. GRC Lifecycle. An end-to-end A.I. management lifecycle to manage and govern A.I. use from development/acquisition, throughout their use in the environment, including A.I. maintenance and retirement.
  • A.I. GRC Architecture. Effective management of A.I. in today’s complex and dynamic business environment requires an information and technology architecture that enables A.I. GRC.

The blog above is taken from GRC 20/20’s paper on: A.I. GRC: The Governance, Risk Management & Compliance of A.I.

I will be speaking on A.I. GRC at the upcoming events:

My keynotes at the upcoming #RISK in Amsterdam and in London is on A.I. GRC

September 27 – September 28

ber 18 – October 19

Upcoming webinars where I am speaking on A.I. GRC

October 10 @ 10:00 am – 11:00 am AEDT 

October 11 @ 12:00 pm – 1:00 pm EDT 

November 7 @ 12:00 pm – 1:00 pm CST 

Other conferences where I am presenting on A.I. topics

October 2 – October 5

Third-Party Risk Workshops where part of the focus will be on A.I. in the Extended Enterprise

September 25 @ 10:00 am – 5:00 pm BST 

October 13 @ 10:00 am – 4:00 pm CDT 

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