• Reducing risk and governing AI & data to manage and monetize AI opportunities at scale.

• AI-driven operations are predicted to save the telecoms industry $27 billion in the coming decade, reduce time to market by leveraging AI to automate manual tasks, reduce customer churn and improve life-time value through effective use of AI and help operators invest wisely to get the right results with AI

• Covering:

  • AI readiness
  • AI governance
  • AI and data management

AI Governance

To meet the need to provide higher quality and richer services in a cost-efficient manner, Communications Service Providers (CSPs) must adopt complex new technologies while simultaneously reducing costs. To do this, the industry relies on AI to effectively augment and automate decision-making that would overwhelm human operators. It is estimated that by 2025 there will be 30+ billion connections worldwide. Manual means of assurance cannot scale to satisfy such digital demands.

Given that CSP Business and Operations Support Services (BSS and OSS) architectures typically contain hundreds or thousands of significant components, it is probable that an equal number of AI modules will eventually be deployed within a CSP organization. Managing AI at this scale leads to accountability, audit and maintenance problems. For example, if it is discovered that a data set used to train AI is corrupted, it is natural to withdraw and redevelop all the models affected - but which ones are they, and where are they located? Can the CSP demonstrate to regulators that every model involved has been removed? Can these tasks be performed rapidly and with little cost?

Data Governance

Communications Service Providers (CSPs) can use data to increase personalization, improve customer retention and spot the potential for new services. Data can also be used for predictive analytics, such as fault detection, and help us respond to global pandemics, natural disasters and climate change.

New 5G ecosystems and services, from autonomous vehicles to sensor data, as well as smart cities and industries, all rely on data analysis. Codified information also powers autonomous operations and artificial intelligence (AI), which are critical as manual assurance cannot scale to meet digital demand.