CSPs Struggling to Deploy AI Due to Data Challenges, Finds Nokia-Commissioned Research
Communications service providers (CSPs) are facing obstacles in effectively implementing artificial intelligence (AI) due to data challenges, according to a new research study commissioned by Nokia and conducted by Analysys Mason. The study reveals that CSPs are struggling to access high-quality data sets, which hinders their ability to make accurate decisions and integrate AI into their networks.
The research, based on responses from 84 CSPs globally, highlights that nearly 50 percent of Tier-1 CSPs consider data collection as the most challenging stage of the telco AI development cycle. Legacy systems with proprietary interfaces are preventing CSPs from accessing the necessary high-quality data, ultimately limiting the speed at which they can integrate AI into their networks. This data issue also impacts CSPs’ ability to attract and retain AI talent.
The study further reveals that only six percent of the CSPs surveyed believe they have achieved the most advanced level of automation, known as zero-touch automation, which relies on AI and machine learning algorithms to improve network operations. However, despite the challenges, 87 percent of CSPs have begun implementing AI into their network operations, with 57 percent deploying telco AI use cases to the point of production.
CSP respondents believe that AI will help enhance network service quality, drive top-line growth, improve customer experience, and optimize energy consumption to meet sustainability goals. To overcome the data challenges and other hindrances such as the inability to scale AI use case deployments, the research suggests that CSPs need to evaluate their telco AI implementation strategies and develop a clear roadmap for AI integration.
Adaora Okeleke, Principal Analyst at Analysys Mason, emphasizes the need for CSPs to transition to more autonomous operations in order to manage networks more efficiently and deliver on their main business priorities. Okeleke highlights that accessing high-quality data remains a critical obstacle for deploying telco AI within networks, requiring CSPs to reexamine their AI implementation strategies to work around this data quality issue.
Andrew Burrell, Head of Business Applications Marketing, Cloud and Network Services at Nokia, acknowledges the vital role of AI in driving significant improvements in network performance, including reducing carbon footprints. Burrell suggests that CSPs must address the challenges of integrating AI into their operations while considering steps to positively alter the situation, such as building an ecosystem of vendor partners with the necessary skills to cater to their network needs.
In conclusion, the research study commissioned by Nokia reveals that CSPs are struggling to deploy AI effectively due to data challenges. The study emphasizes the importance of accessing high-quality data and developing clear AI implementation strategies for CSPs to overcome these obstacles and achieve more autonomous operations. With AI’s potential to enhance network performance and contribute to sustainability goals, CSPs must prioritize addressing the data challenges to fully unlock the benefits of AI in their networks.
Source: [Nokia]
