Seeing all these posts about #SAP hashtag#TechEd makes me think …. remember when mobile access was a “nice-to-have” for select employees? Road Warriors, C-Suite, Field Techs …
Those days are over.
As we enter the era of agentic AI, every employee is becoming an orchestrator … managing teams of AI agents, approving tasks, and overseeing processes that never sleep. The definition of productivity now means directing AI operations, not just GSD. These processes don’t wait for you to return to your desk.
Enterprise mobility isn’t about convenience anymore—it’s about keeping pace with AI-speed business.
The question isn’t whether to invest in this trend. It’s whether you can afford not to.
What’s your organization doing to prepare for this shift?
hashtag#EnterpriseMobility hashtag#AI hashtag#FutureOfWork hashtag#DigitalTransformation hashtag#Productivity
A Definition of AGIThe lack of a concrete definition for Artificial General Intelligence (AGI) obscures the gap between today’s specialized AI and human-level cognition. This paper introduces a quantifiable framework to address this, defining AGI as matching the cognitive versatility and proficiency of a well-educated adult. To operationalize this, we ground our methodology in Cattell-Horn-Carroll theory, the most empirically validated model of human cognition. The framework dissects general intelligence into ten core cognitive domains-including reasoning, memory, and perception-and adapts established human psychometric batteries to evaluate AI systems. Application of this framework reveals a highly “jagged” cognitive profile in contemporary models. While proficient in knowledge-intensive domains, current AI systems have critical deficits in foundational cognitive machinery, particularly long-term memory storage. The resulting AGI scores (e.g., GPT-4 at 27%, GPT-5 at 57%) concretely quantify both rapid progress and the substantial gap remaining before AGI.
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