Artificial Intelligence Adoption, Usage & Investment Trends in the Telecoms Industry
July 2018
41
About the Report
About the Report
Artificial Intelligence Adoption, Usage & Investment Trends in the Telecoms Industry
Summary
GlobalData's 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 USUSD1 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.
Scope
- 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.
Products
Companies
Telefonica
Megafon (Russian Telecom Operator)
NEC Corp
Huawei
Baidu
Mavenir
Argyle Data
TIM (Telecom Italia)
Microsoft
Table of Contents
Table of Contents
Table of Contents
Section 1: Introduction 5
Definitions and abbreviations 6
Methodology and sample size 8
Respondent profile 9
Section 2: Adoption, significance, and investment: AI in Telecom 11
Advancement in adoption of AI within the global telecom industry 12
AI technology types expected to gain momentum over the next two years 16
Key benefits influencing the deployment of AI in telecom industry 19
Projected investment in AI over next two years 22
Section 3: Practical use case, industrial application of AI, and monetization opportunities 23
Use cases with highest growth potential to drive implementation of AI in global telecom market 24
Success metrics for AI applications: in their words 27
AI applications to gain significance within the telecom industry 29
Monetization opportunities in other external AI applications or use cases 31
Section 4: Market opportunities, implementation challenges and advice 32
Market opportunities expected to influence the investment in AI over next two year 33
Major implementation barriers / challenges faced by telecom companies in adopting AI 35
Recommended activities for setting out the implementation of AI: In their words 37
Appendix 39
List of Figure
List of Figures
Exhibit 1: Projected adoption of AI in telecom industry-Overall and Region 13
Exhibit 2: Projected adoption of AI in telecom industry-Company types 14
Exhibit 3: Planning stage for implementation of AI-Overall and Region 15
Exhibit 4: Planning stage for implementation of AI-Company types 16
Exhibit 5: AI technology to gain prominence within the industry in 2018 and 2020-Overall 17
Exhibit 6: AI technology to gain prominence within the industry in 2018 and 2020-Region 18
Exhibit 7: AI technology to gain prominence within the industry in 2018 and 2020 -Company types 19
Exhibit 8: Key AI benefits/ offerings to gain momentum in telecom market in 2018 and next two years-Overall 20
Exhibit 9: Top five AI benefits/ offerings to gain momentum in telecom market-Region 21
Exhibit 10: Top five AI benefits/ offerings to gain momentum in telecom market-Company types 22
Exhibit 11: Projected value of investment in AI over next two years-Overall 23
Exhibit 12: Use cases with high growth potential to drive AI in telecom market over the next two years-Overall 25
Exhibit 13: Use cases with high growth potential to drive AI in telecom market-Region 26
Exhibit 14: Use cases with high growth potential to drive AI in telecom market-Company types 27
Exhibit 15: Success metrics for previous AI application in telecom market: In their own words 28
Exhibit 16: AI application types to gain significance within the industry over next two years-Overall 29
Exhibit 17: Top four AI application types to gain significance within the industry over next two years-Region 30
Exhibit 18: Top four AI application types to gain significance over next two years-Company types 31
Exhibit 19: Monetization opportunity for other external potential AI applications or use cases-In their own words 32
Exhibit 20: Market opportunities influencing telecom companies to invest in AI over the next two years-Overall 34
Exhibit 21: Market opportunities influencing telecom companies to invest in AI- Region and company types 35
Exhibit 22: Major barriers / challenges faced by organizations to adopt AI-Overall 36
Exhibit 23: Major barriers / challenges faced by organizations to adopt AI-Region and company types 37
Exhibit 24: Advice regarding the implementation of AI: In their own words 38
Exhibit 25: Advice regarding the implementation of AI: In their own words 39
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