by iqentity | Nov 6, 2024 | AI Misuse
The liability exposure from AI misuse is poorly understood by most organizations. When an employee uses AI to fabricate a deliverable, misrepresent data, or create misleading communications, the organization may bear legal responsibility regardless of whether it...
by iqentity | Nov 4, 2024 | Development, Tessera
I have been using Tessera in daily operations for two months now, and the most significant effect is not what I expected. The Expected Effect I expected faster decisions. I got them. I expected better precedent recall. I got it. I expected less time re-deriving...
by iqentity | Nov 2, 2024 | Development, Tessera
I keep correcting people who describe Tessera as a productivity tool. She is not. Productivity implies doing the same things more quickly. Tessera does something different. The Distinction Tessera does not make me faster at typing answers. She makes me faster at being...
by iqentity | Nov 1, 2024 | Business Strategy
Most organizations overestimate their AI readiness. They have data, but not the right data. They have technical talent, but not enough of it. They have executive sponsorship, but not sustained executive attention. The gap between readiness assessment and readiness...
by iqentity | Oct 30, 2024 | Development, Tessera
I want to walk through a specific example of how Tessera handles an email chain, because the abstract description does not capture what the experience actually feels like. The Scenario A complex vendor dispute arrives as an email chain with 14 messages spanning three...
by iqentity | Oct 28, 2024 | AI Ethics
Every AI deployment makes implicit ethical choices. The training data encodes values. The objective function prioritizes outcomes. The deployment context determines who is affected. Pretending these choices are purely technical is itself an ethical position, and not a...
by iqentity | Oct 25, 2024 | Business Strategy
Vendor promises and operational reality diverge most sharply at the integration point. The AI model works. The integration with existing systems, workflows, and data pipelines does not. Integration is where 60 percent of the budget goes and 80 percent of the delays...
by iqentity | Oct 23, 2024 | AI Ethics
The gap between ethical intention and ethical outcome is bridged by process, not aspiration. Organizations that have ethical AI principles but no ethical AI processes have principles in name only. The fundamental challenge of AI ethics is not knowing what is right. It...
by iqentity | Oct 21, 2024 | Shadow AI
The risk is not hypothetical. Documented incidents of data exposure through public AI tools are increasing. Legal and regulatory frameworks are beginning to assign liability for data processed through unauthorized AI systems. The window between ‘acceptable...
by iqentity | Oct 18, 2024 | Business Strategy
Most organizations overestimate their AI readiness. They have data, but not the right data. They have technical talent, but not enough of it. They have executive sponsorship, but not sustained executive attention. The gap between readiness assessment and readiness...
