u/BatterUp99

As organizations continue adopting LLMs and generative AI, governance is becoming increasingly important.

If you could wave a magic wand and solve just one AI governance problem tomorrow, what would it be?

I'm researching how organizations are approaching cybersecurity and governance challenges associated with LLMs and generative AI as adoption continues to accelerate.

For those working in cybersecurity, AI governance, risk, compliance, architecture, or engineering, I'd be interested in hearing your perspective.

A few questions I'm particularly curious about:

• What AI-related risks are receiving the most attention in organizations today?
• Which concerns are overhyped, and which are underestimated?
• What challenges have proven harder to solve in practice than expected?
• What is consuming the most time and attention from security or governance teams?
• How are organizations currently mitigating these risks?
• Where do existing tools, controls, or processes fall short?
• If you could solve one AI security or governance problem today, what would it be?

I am only looking for industry perspective and lessons learned

Looking forward to hearing different viewpoints from across the field.

I'm researching how organizations are approaching cybersecurity and governance challenges associated with LLMs and generative AI as adoption continues to accelerate.

For those working in cybersecurity, AI governance, risk, compliance, architecture, or engineering, I'd be interested in hearing your perspective.

A few questions I'm particularly curious about:

• What AI-related risks are receiving the most attention in organizations today?
• Which concerns are overhyped, and which are underestimated?
• What challenges have proven harder to solve in practice than expected?
• What is consuming the most time and attention from security or governance teams?
• How are organizations currently mitigating these risks?
• Where do existing tools, controls, or processes fall short?
• If you could solve one AI security or governance problem today, what would it be?

I am only looking for industry perspective and lessons learned

Looking forward to hearing different viewpoints from across the field.

I'm researching how organizations are approaching cybersecurity and governance challenges associated with LLMs and generative AI as adoption continues to accelerate.

For those working in cybersecurity, AI governance, risk, compliance, architecture, or engineering, I'd be interested in hearing your perspective.

A few questions I'm particularly curious about:

• What AI-related risks are receiving the most attention in organizations today?
• Which concerns are overhyped, and which are underestimated?
• What challenges have proven harder to solve in practice than expected?
• What is consuming the most time and attention from security or governance teams?
• How are organizations currently mitigating these risks?
• Where do existing tools, controls, or processes fall short?
• If you could solve one AI security or governance problem today, what would it be?

I am only looking for industry perspective and lessons learned

Looking forward to hearing different viewpoints from across the field.