Our "Artificial Intelligence Adoption, Usage & Investment Trends in the Telecoms Industry", report examines the advancement in adoption of AI within the global telecom industry along with the key benefits influencing the deployment and projected investments in AI over the next two years. The report highlights the use cases and applications that have highest growth potential in driving the implementation of AI in the global telecom industry. Additionally, the report covers the information about the market opportunities expected to influence the investment in AI and challenges/ barriers encountered by telecoms businesses.
The majority of telecom industry executives consider that their organization is in the development phase of implementing artificial intelligence (AI). Due to significant value and potential that AI has to offer to telecom enterprises companies are moving towards AI solutions and use cases. Improved operational efficiency is expected to be the most beneficial factor of AI for telecom companies over next two years. In total, 40% of surveyed industry executives revealed that their company has plans to invest more than US$1 million in AI during 2018-2020. Moreover, the rising popularity of AI applications within the telecom industry is supported by the increasing complexity in networking caused by growing volume of IoT devices, cloud migrations, the increasing number of OTTs and the arrival of 5G. However, lack of skill-sets and making changes to traditional organizational structures are major challenges faced by the telecom companies to adopt AI.
What else does this report offer?
- Adoption and implementation of AI: identifies how advance are the companies in adoption of AI
- Preferred AI technologies/areas and offerings: highlights key AI technologies/areas and benefits that are influencing the deployment of AI in telecom industry over the next two years
- Projected investments: examines the value of the investment enterprises are planning to make in AI in the next 2 years
- Practical use cases and AI applications overview: highlight important use cases with the highest growth potential in driving AI and applications that are expected to gain significance in telecom industry during 2018-2020
- Monetization and marketing opportunities: identifies monetization opportunities in other external AI applications with the market opportunities expected to highly influence telecom companies to invest in AI
- Enterprises expected revenue from investment in BDA: recognizes revenue generated from investment in BDA during 2016-2018
- Challenges encountered and recommendations for implementation of AI: provides information about the pressing challenges faced by organizations while adopting AI along with the executives’ advice for successful AI implementation.
- Machine learning is the most expected AI area to gain momentum in the telecoms industry this year, followed by natural language processing
- Regardless of the region of operation majority of respondents agree that their organization is planning to implement AI in the next 12 months
- Overall, improved operational efficiency is expected to be the most beneficial factor of AI for telecom companies over next two years
- Self-diagnostics and self-optimization for mobile networks is expected to show a high growth potential over the next two years
- 80% of respondents who operate in Asia-Pacific anticipate data mining/analytics and optimization of network operations to gain significance over the next two years
- 68% of respondents operating in large companies identified customer experience enhancement as a key driver of telecom companies’ AI investments.
Reasons To Buy
- Assists telecom companies to take faster, better decision making by understanding the benefits of adopting AI solutions
- Telecom companies can gain a competitive advantage by examining the prominence of various AI use cases and applications which in turn help to improve operational efficiency
- Leads to informed decisions by helping to recognize the market opportunities offered by AI during 2018-2020
- Helps organizations to understand the major implementation barriers / challenges in adopting AI
- Provide useful information on use cases with highest growth potential to drive implementation of AI and success metrics for AI applications.