Overcome challenges and embrace change
Alper acknowledges that there are several challenges to achieving AI-native transformation. He points to the complexity of communications networks, which often include a mix of legacy systems and new technologies.
Additionally, data privacy and security issues must be carefully managed, especially as AI enables the processing of vast amounts of network data.
“We have a lot of data, but we are not using it to its full potential,” he warns.
To address these challenges, Alper emphasizes the importance of executive alignment, cross-functional collaboration, and continued stakeholder engagement.
He emphasizes the need to modernize IT systems, retire outdated technology, and invest in advanced monitoring tools to streamline operations.
Beyond technical challenges, Benli emphasizes the importance of change management and restructuring organizational processes.
“Don’t overlook the people side,” he says, noting that successful transformation requires a holistic approach, including restructuring teams, roles and responsibilities to align with new AI capabilities. Let me explain.
