Uploaded February 2026 | Updated September 2026, 16 hours ago
Enterprise AI doesn’t stall because the models are bad. It stalls because security, governance, cost control, and compliance are hard.
You can hear more details in my co-worker Purnima Padmanabhan's talk at AI in Finance Summit NYC in April: ny-ai-finance.re-work.co
In large organizations, the real work isn’t prompts or model selection - it’s:
• Who can access what
• Where workloads run
• How costs are tracked and controlled
• How data is secured
• How you stay compliant
• How you standardize without slowing everything down
This is the same lesson from DevOps, SRE, and platform engineering: the value comes from the “trimmings” - the controls, guardrails, and systems around the application.
If you want AI to actually deliver business value, you need a platform and operating model that makes it safe to use at scale.
Featured in this tiny video:
1. Arvind Narayanan & Sayash Kapoor, “AI as Normal Technology”: knightcolumbia.org/content/ai-as-normal-technology
2. Camille Crowell-Lee & Chris Sterling: blogs.vmware.com/tanzu/the-security-gap-in-ai-applications-rethinking-api-protection-for-a-new-era
3. Oren Penso on The New Stack: thenewstack.io/shadow-ai-isnt-a-threat-its-a-wake-up-call
4. Bridget Kromhout’s classic: queue.acm.org/detail.cfm?id=3185224
5. Camille Crowell-Lee & John Dwyer: blogs.vmware.com/tanzu/what-is-ai-middleware-and-why-you-need-it
If you read this far, why not try Tanzu? trytanzu.ai
#AI #EnterpriseAI #Leadership #BusinessStrategy #DigitalTransformation #Governance #RiskManagement #Innovation #Management #Productivity
Enterprise AI doesn’t stall because the models are bad. It stalls because security, governance, cost control, and compliance are hard.
You can hear more details in my co-worker Purnima Padmanabhan's talk at AI in Finance Summit NYC in April: ny-ai-finance.re-work.co
In large organizations, the real work isn’t prompts or model selection - it’s:
• Who can access what
• Where workloads run
• How costs are tracked and controlled
• How data is secured
• How you stay compliant
• How you standardize without slowing everything down
This is the same lesson from DevOps, SRE, and platform engineering: the value comes from the “trimmings” - the controls, guardrails, and systems around the application.
If you want AI to actually deliver business value, you need a platform and operating model that makes it safe to use at scale.
Featured in this tiny video:
1. Arvind Narayanan & Sayash Kapoor, “AI as Normal Technology”: knightcolumbia.org/content/ai-as-normal-technology
2. Camille Crowell-Lee & Chris Sterling: blogs.vmware.com/tanzu/the-security-gap-in-ai-applications-rethinking-api-protection-for-a-new-era
3. Oren Penso on The New Stack: thenewstack.io/shadow-ai-isnt-a-threat-its-a-wake-up-call
4. Bridget Kromhout’s classic: queue.acm.org/detail.cfm?id=3185224
5. Camille Crowell-Lee & John Dwyer: blogs.vmware.com/tanzu/what-is-ai-middleware-and-why-you-need-it
If you read this far, why not try Tanzu? trytanzu.ai
#AI #EnterpriseAI #Leadership #BusinessStrategy #DigitalTransformation #Governance #RiskManagement #Innovation #Management #Productivity
