Between 2009 and 2023, Inspira founders Benny and Izzy Traub hired 1,927 workers, many of whom were part-time and working remotely.
Like all humans, the majority of their workers were prone to inconsistent performance. This included a wide range of issues that were disruptive to other team members (such as showing up late for meetings). But even more disturbing was when workers completed work that could have been performed in far less time. With hundreds of thousands of man-hours, opportunities for improvement began emerging in the form of AI software.
CEO, Izzy Traub, returned to school in 2021 to obtain a certificate in data science from the University of Texas. Prior to this, he founded VFX Los Angeles, a post-production company in the film industry, serving clients such as Netflix, HBO and Hulu, working directly with A-list leaders such as Ben Affleck and Jennifer Lopez. He has done pioneering work in the area of deep fakes and automating components fo the VFX pipeline using AI. He remains the CEO of VFX Los Angeles, although most day-to-day duties are handled by his team.
COO, Benny Traub augmented his education with a certificate in AI Strategy from MIT in 2021. Prior to this, he had taken two companies public during the dot com boom. He had successfully handed management of these companies off to industry leaders, only to witness both companies implode during the dot com bomb. He retired for seven years before coming back to work in 2009 to found Marketing Education.org, Wealth Management Association and Student Marketing Agency. He continues to be involved in those organizations, although on a minimal basis, directing most of his energy into Inspira.
Our approach is; When your people fail, your systems cannot. AI systems must be capable of identifying problems before they become noticeable to a human. AI systems must attempt to solve those problems without human intervention. Only after attempts at an automated solution are those issues escalated to a human.
The transformative journey into AI began with the development of simple RPAs, automated systems that are capable of identifying problems and alerting management. The system has since grown into a rapidly evolving AI framework for performance optimization, tailored for the knowledge worker.
Competitive advantage can quickly be lost. Once lost, it is difficult or even impossible to gain back. A company (or nation) that does not rapidly augment every worker with AI, may suffer irreversible economic consequences.
It will take time to automate the myriad of tasks that humans routinely perform. The transition will not be easy. But before, during and after the transition, humans will still be at the center of the productivity cycle.
As AI advances, human leadership will rapidly become more important than ever before. The leverage-ability of AI cannot be optimized without human leadership. And by leadership, we are not referring to ‘management’, rather, the humans that must govern and lead the AI. In this sense, every worker is a leader who must organize, prioritize and delegate work to AI systems.
Just as the productivity of human teams depends on good management, in the same way, AI systems depend on humans to provide similar leadership. And yet the impact is multiplied since the productivity of AI systems is so much higher. If AI can perform the work 100 times faster, each AI system is comparable to having 100 employees that are under the supervision of a human. Get the leadership wrong, and the leverage of AI will be vastly diminished! Poor human leadership could be responsible for reducing the effectiveness of an AI system to only 2x that of a human. If the competitors are pushing 100x, a catastrophic outcome cannot be avoided.
The economic future of every company and nation depends on the rapid AI augmentation of every worker. If we do not augment every worker, others will leap ahead by such a margin that we cannot catch up. On the other hand, rapid augmentation, with every tool at our disposal, will put us in that leadership position and others will struggle along in our dust.