BofA Explains How Telecom Companies Can Evolve to Become AI Winners
Artificial intelligence is creating a new challenge for telecom companies: the same AI agents that can help operators improve customer retention could also make it much easier for consumers to compare plans and switch providers.
Bank of America analysts say European telecom operators can respond by using AI more aggressively across sales, customer management and pricing. The argument is important because traditional telecom businesses have generally struggled to capture the economic value created by rapidly rising data consumption.
The opportunity, according to BofA, is to make AI part of the commercial engine rather than treating it simply as another technology project.
At the same time, the competitive pressure is real. AI agents could independently search telecom packages, compare prices and even contact providers to negotiate better deals for customers. That could make an already competitive European telecom market even more price-sensitive.
AI Could Change How Customers Choose Telecom Plans
For years, telecom customers have relied on comparison websites, retailers and direct operator channels to choose mobile and broadband plans.
AI agents could take that process much further.
An agent acting on behalf of a consumer could compare available plans, identify cheaper alternatives and potentially negotiate with providers. This reduces the time and effort required to switch and could increase pressure on operators with relatively expensive legacy tariffs.
BofA notes that European telecom markets have already experienced significant price arbitrage for roughly 15 years, driven by challengers such as Iliad and the expansion of mobile virtual network operators. Consumers are therefore already relatively familiar with comparing telecom prices.
The expansion of eSIM technology adds another layer. Because eSIMs can make switching between mobile providers easier, AI-powered comparison and switching could potentially reduce customer friction even further.
For telecom companies, that makes customer retention increasingly important.
BofA's AI Opportunity: Sell Smarter, Not Just Cheaper
BofA's analysis suggests that operators can use AI to counter this pressure by improving how they sell and manage customer relationships.
One potential application is personalised offers.
Instead of presenting every customer with the same upgrade options, AI systems can analyse usage patterns and identify whether a subscriber is more likely to respond to an upsell, a cheaper plan or a different service bundle.
That could help operators improve customer retention, commonly measured through churn. Churn refers to the rate at which customers leave a service during a given period.
AI could also help operators identify customers at risk of switching before they actually leave.
This matters because acquiring a new subscriber can be more expensive than retaining an existing one. If AI allows operators to identify the right intervention at the right time, the technology could have a direct effect on telecom economics.
Pricing Pressure Is Already Uneven Across Europe
The threat from AI agents will not be identical across European telecom markets.
BofA's analysis found that entry-level incumbent mobile tariffs in Switzerland, France and Norway were priced 20%, 14% and 11% below second-quarter average revenue per user, respectively. These gaps can indicate greater potential for customers to move toward cheaper alternatives.
The brokerage also highlighted particularly large challenger discounts in the Netherlands, Switzerland and the UK, where challenger offers were discounted by 71%, 66% and 53% against incumbent back-book pricing.
In Finland and Italy, the corresponding discounts were much smaller at 7%.
This distinction is important for investors because AI does not create the same competitive risk for every telecom operator.
Where pricing differences are already substantial, automated comparison tools could make those differences easier for customers to discover.
Which European Telecom Operators Face More Exposure?
BofA's analysis identified several companies with greater exposure to pricing pressure.
In mobile, KPN, Swisscom and Virgin Media O2 were identified as having the greatest overall exposure based on challenger pricing, potential customer "spin-down" risk and domestic service revenue.
BofA considered Deutsche Telekom, Orange France and Vodafone Germany to have more contained exposure under its analysis.
The brokerage also examined fixed broadband.
The Netherlands and UK had the highest potential spin-down risk, with basic incumbent tariffs priced 52% and 51% below second-quarter average revenue per user, respectively.
For broadband, BofA identified KPN, Virgin Media O2 and Orange France as having the highest overall exposure, while Deutsche Telekom, Telia and Telenor had more contained exposure under the pricing analysis.
These are exposure assessments rather than predictions of future stock performance. Actual outcomes will depend on how individual companies respond to changing consumer behaviour and competitive pricing.
Telecom Companies Have Another AI Opportunity: The Network
The AI story for telecom operators is not limited to sales and customer retention.
AI itself could change the type of networks that operators need to build and monetize.
Ericsson says AI-native applications are creating different traffic patterns, including greater demand for real-time connectivity, higher uplink requirements and more predictable latency. AI-enabled wearables, autonomous systems and other connected devices can continuously send video, audio and sensor data to cloud systems for processing.
That could eventually create opportunities for telecom companies to sell differentiated connectivity rather than treating bandwidth as a largely undifferentiated commodity.
For example, enterprises could pay for connectivity with specific reliability, latency or performance requirements.
Ericsson has also described potential future telecom monetisation models involving AI services, AI compute, premium connectivity and network-based platforms.
This represents a potentially larger strategic shift: telecom operators could move from simply transporting data to providing infrastructure and services that sit closer to the AI value chain.
AI Could Increase Network Demand Too
There is another potential benefit for operators.
If AI applications generate substantially more data traffic, telecom companies could see increased demand for network capacity.
Ericsson's June 2026 network measurements found that 43 of 55 service providers experienced higher uplink growth than downlink growth. Its scenario modelling suggested that additional AI traffic could result in uplink traffic being three times higher or more in 2031 compared with 2025.
That does not automatically translate into higher profits.
Operators still need to invest in spectrum, fibre, radio equipment, data centres and network software. The key investment question is whether additional traffic can be monetised sufficiently to generate attractive returns on that infrastructure spending.
The Risk: AI Could Increase Competition Faster Than Revenue
This is where the telecom AI story becomes more complicated.
AI can reduce costs and improve customer targeting, but it can also make competition more transparent.
If an AI agent can instantly compare dozens of plans, identify the cheapest suitable package and switch providers, operators may find it harder to maintain pricing premiums.
That could put pressure on average revenue per user, or ARPU, particularly where customers have multiple similar alternatives.
There is also the risk that operators spend heavily on AI without generating enough incremental revenue. BofA's broader research on AI infrastructure has highlighted the increasing importance of turning large technology investments into measurable economic returns.
For telecom companies, successful AI adoption therefore needs to show up in metrics such as lower churn, better conversion rates, higher ARPU, lower operating costs or new enterprise revenue.
What Investors Should Watch
The next phase of the telecom-AI story will be less about announcements and more about measurable results.
Investors should monitor:
Churn rates: Are operators retaining customers more effectively?
ARPU: Is personalised selling increasing revenue per subscriber?
Pricing discipline: Are AI-driven comparisons accelerating price competition?
AI-related capex: How much are operators spending on network and computing infrastructure?
Enterprise revenue: Are companies generating new revenue from AI-ready connectivity?
Network traffic: Is rising AI traffic translating into higher-value services?
Operating costs: Are AI tools delivering genuine productivity improvements?
These indicators can help distinguish between telecom companies that are merely adopting AI and those that are successfully converting it into financial value.
Bottom Line
Bank of America sees AI as both a threat and an opportunity for European telecom companies. AI agents could make it easier for consumers to compare prices and switch providers, increasing competitive pressure. But the same technology can help operators personalise offers, improve customer retention and make sales more efficient.
The longer-term opportunity could extend beyond customer management. AI-driven traffic, enterprise applications and demand for reliable, low-latency connectivity may give telecom operators new ways to monetise their networks.
For investors, the key question is not simply whether a telecom company uses AI. It is whether AI produces measurable improvements in customer retention, pricing, operating efficiency and new revenue streams. Those financial outcomes will ultimately determine how much of the AI boom telecom operators can capture.
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This article is for informational and educational purposes only and should not be considered investment advice.