Privacy inertia: AI is part of the problem and the solution
This report is available to those subscribed to the Digital Consumer module.
The average consumer’s decision to trust a website or app is often based on convenience, typically without a full understanding of the implications of sharing their data. Although consumers appear to be concerned about their privacy online, only a minority are making satisfactory efforts to protect their data. The risks of sharing data – and the lack of action being taken by consumers – are made worse by the deployment of AI and machine-learning technologies, which are being used to automate data collection in an increasingly opaque manner. However, AI could also be used to help manage and protect consumer data, especially if the technology is placed in the hands of regulators and consumers.
Related research
AI opens a new front in the fight against unwanted calls to fixed lines
Although the number of unwanted calls to fixed lines has been decreasing due to efforts from stakeholders (including operators, network and customer-premises equipment vendors and regulators), the emergence of AI, especially generative AI, could reverse this trend while also making consumers more vulnerable to scams. However, AI can also be used to tackle the scourge of unwanted calls. In this report, we examine the approach taken by key stakeholders in various countries, notably the UK and the US, highlighting some of the risks and opportunities in the struggle against unwanted calls.
AI for digital industries: navigating enterprise needs, investments and supplier decisions
Digital transformation of vertical sectors is accelerating, with AI being a top area of investment. GSMA Intelligence surveyed nearly 4,200 enterprises across 21 countries and 10 vertical sectors to gain relevant insights into their digital transformation across a range of technologies. This report analyses the key findings and implications for AI.
Five ways fixed broadband operators are using AI
GSMA Intelligence has identified five AI use cases for fixed broadband operators that aim to enhance customer experience while reducing costs: AI for network optimisation, AI for fibre rollout, AI integrated into CPE, AI for sales and marketing, and AI for customer service.
Authors
How to access this report
Annual subscription: Subscribe to our research modules for comprehensive access to more than 200 reports per year.
Enquire about subscriptionContact our research team
Get in touch with us to find out more about our research topics and analysis.
Contact our research teamMedia
To cite our research, please see our citation policy in our Terms of Use, or contact our Media team for more information.
Learn moreRelated research
AI opens a new front in the fight against unwanted calls to fixed lines
Although the number of unwanted calls to fixed lines has been decreasing due to efforts from stakeholders (including operators, network and customer-premises equipment vendors and regulators), the emergence of AI, especially generative AI, could reverse this trend while also making consumers more vulnerable to scams. However, AI can also be used to tackle the scourge of unwanted calls. In this report, we examine the approach taken by key stakeholders in various countries, notably the UK and the US, highlighting some of the risks and opportunities in the struggle against unwanted calls.
AI for digital industries: navigating enterprise needs, investments and supplier decisions
Digital transformation of vertical sectors is accelerating, with AI being a top area of investment. GSMA Intelligence surveyed nearly 4,200 enterprises across 21 countries and 10 vertical sectors to gain relevant insights into their digital transformation across a range of technologies. This report analyses the key findings and implications for AI.
Five ways fixed broadband operators are using AI
GSMA Intelligence has identified five AI use cases for fixed broadband operators that aim to enhance customer experience while reducing costs: AI for network optimisation, AI for fibre rollout, AI integrated into CPE, AI for sales and marketing, and AI for customer service.
- 200 reports a year
- 50 million data points
- Over 350 metrics