Taking a computer-aided engineering (CAE) approach to business transformation can help businesses manage program risks, maximize value, decrease costs and accelerate innovation.
About Nabil Abu el Ata
Nabil Abu el Ata has invested over 20 years maturing the science of risk management and the practical application of predictive analytics technologies. In the late 1970s Dr. Abu el Ata's mathematical discoveries provided accurate coordinates for space exploration. By solving a problem that was previously defined as unsolvable, Dr. Abu el Ata set the foundation for a new era of risk management, which today enables companies worldwide to more accurately predict future system behaviors and take strategic actions to improve business outcomes.
Entries by Nabil Abu el Ata
X-Act libraries are a critical asset that shortens the time to value of an X-Act deployment from months to weeks and allow businesses to benchmark their systems against best in class implementations, gain a forward-looking view of the health of interconnected systems and know when a system transformation or disruption is needed. Any decisions can be justified with accurate knowledge of the benefits, costs and constraints of any proposed change.
To thrive in world that is constantly morphing due to the acceleration of innovation and the velocity of disruption, we must move the AI cursor to generate a wider domain of intelligence.
The pursuit of AI assumes that human intelligence is worth replicating and will create a benefit for end users. But do we really want to replicate the flaws of human intelligence like prejudices, greed, and procrastination? Or the shortcomings of our processing capabilities? Merely replicating human intelligence using known patterns and outcomes might unburden us from menial tasks, but it won’t solve the most pressing problems of the future.
Generative intelligence pairs human perception and decision making capabilities of artificial intelligence (AI) with the scientific disciplines of dynamic complexity and perturbation theory, supported by causal deconstruction, to create a systemic and iterative collection of rational and unbiased knowledge that exceeds human intelligence.
The systemic enterprise is an integrated “systems-based” operations management approach that uses mathematical emulation, generative intelligence and automation to model, analyze, and measure operational risk so that system owners can optimally manage the health of business processes and underlying information technology.
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