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Mamoun Alamouri, Regional VP - MEA at Uniphore, discusses overcoming AI project failures by managing expectation gaps and more.
Mamoun Alamouri, Regional VP-MEA at Uniphore, in conversation with MIT Sloan Management Review Middle East for the Tech Leaders Lab series, shares his insights on the challenges organizations face due to expectation and estimation errors when implementing AI. According to him, one of the primary drivers behind these errors is the rapid escalation of expectations that often outpace what AI can realistically deliver. This misalignment is resulting in significant organizational friction, hindering successful AI integration.
To bridge this gap, Alamouri advises leaders to “start defining parameters to minimize estimation errors. This involves establishing a clear understanding of risk appetite, speed of innovation, and setting realistic goals.” He emphasizes the importance of leadership alignment and education: “You must first acknowledge what you don’t know, then educate yourself on what is possible and what isn’t.”
In this video Alamouri also talks about:
- Skills that business leaders need to learn and unlearn – to work with AI successfully.
- How can brands incorporate automation in customer interactions without compromising on brand voice and human connection?
Read more about the importance of continuous learning and adaptation as AI becomes more integrated into businesses in AI’s Role in Business Transformation: Overcoming Challenges and Driving Growth.
