HCLTech’s HPE Acquisition Led to a Reinvention It Says Telecom Needs

TLDR

• HCLTech is reinventing its telecom business. Its HPE acquisition adds software and intellectual property to a business traditionally centered on technology services, according to telecom chief Srinivas Lakkaraju.
• Carriers face a similar business-model challenge. AI is advancing inside telecom networks, but operators still need to turn those capabilities into new sources of revenue.
• The biggest obstacles go beyond technology. HCLTech’s survey points to unclear business models, skills gaps, legacy systems and organizational resistance as barriers to broader AI transformation.

Global technology services giant HCLTech’s telecom business spent decades primarily selling technology services. Now it is trying to become something broader: a provider that combines services with its own software, intellectual property and reusable technology components.

Its acquisition of Hewlett Packard Enterprise’s Telco Solutions business, completed in August, is a central piece of that transition. The deal added nearly 1,400 engineering and telecom specialists in 39 countries, as well as software for telecom operational support systems, 5G subscriber data management and other network functions.

The acquisition also follows HCLTech’s 2024 purchase of certain assets from HPE’s Communications Technology Group. HCLTech said the two transactions will help it offer carriers more complete systems for network modernization and AI-led autonomous operations.

For Srinivas Lakkaraju, the senior vice president and head of HCLTech’s communications service provider unit, the significance of the deal goes beyond adding products to the portfolio. HCLTech’s telecom operation has been changing its business model because AI is altering the economics of the services business itself.

“With AI coming into picture, services will get cannibalized,” Lakkaraju said in an interview with The AI Innovator. “Telecom has to change the business model; we ourselves changed the business model.”

That parallel has become central to HCLTech’s argument about the telecommunications industry. Carriers themselves are confronting the same basic question: What happens when the product that historically defined the business no longer creates enough differentiation?

For HCLTech, the answer has been to move beyond pure services toward what Lakkaraju calls a solutions model, combining engineering work with reusable software and intellectual property. For telecom operators, HCLTech argues, the equivalent shift is from selling connectivity toward providing AI-enabled network intelligence and enterprise services.

The company’s Telecom Pulse Survey suggests carriers largely agree that change is necessary but remain much less certain about how to make it.

Seven out of 10 respondents “agree” or “strongly agree” that connectivity is becoming commoditized and that their organizations need new service models to maintain margins. Six in 10 rated AI and advanced analytics as a “high” or “very high” driver of future revenue. Yet only 25% rated themselves a “4” or “5” on a five-point scale measuring readiness to deliver AI-powered, cloud-native services to enterprise customers.

The implication is not that telecom carriers are failing to deploy AI. Major operators are already using AI to automate network operations, diagnose problems and improve customer service. The harder challenge is transforming those technical capabilities into a different business.

From services provider to solutions provider

HCLTech’s own transformation offers a concrete example of what Lakkaraju means by business-model change.

The company has long been a major provider of engineering and IT services. In telecom, Lakkaraju said, HCLTech concluded several years ago that remaining primarily a services provider would become more difficult as AI automated more of the work traditionally performed by people.

The company did not want to become solely a product vendor either. Instead, its telecom organization decided to build a model combining services with software components, frameworks and intellectual property that could shorten deployments for customers.

“You cannot have 100% services,” Lakkaraju said of the new approach. Customers increasingly expect HCLTech to arrive with building blocks already developed rather than beginning every project from scratch, he said.

That strategy helps explain the HPE transaction.

HPE’s Telco Solutions business brought operational support system software, or OSS – systems carriers use to monitor, configure and manage their networks – as well as Home Subscriber Server and 5G Subscriber Data Management technology, both of which are systems that store and manage subscriber identities, profiles and service access.

HCLTech combined those assets with capabilities it already had in areas including business support systems, network functions, service management and orchestration, data intelligence, digital twins, eSIM and AI applications for radio networks.

The acquired business also has substantial installed infrastructure. When the transaction was announced in December, HCLTech said HPE’s Telco Solutions business supported more than 1 billion devices across over 200 deployments globally.

The deal lets HCLTech offer something different from a conventional consulting engagement. Rather than simply supplying engineers to help a carrier modernize a network, it can bring software already embedded in telecom environments and combine it with engineering and AI services.

Lakkaraju described the differentiation more simply: instead of beginning at step one of a 10-step project, HCLTech wants to arrive with enough reusable technology to “start from step four.”

HCLTech said the two transactions together should deepen its shift toward an IP-led and platform-oriented telecom business. It also illustrates the type of transformation Lakkaraju argues carriers themselves need to undertake.

Carriers face their own version of the problem

The old telecom business model is not disappearing. Consumers and enterprises will continue to pay for mobile, broadband and other connectivity.

Nor is the problem that carriers aren’t using AI. Verizon said its closed-loop automation systems made more than 70 million network configuration changes autonomously in 2025. AT&T has deployed a generative AI system that can simulate and predict network coverage under changing conditions and determine how neighboring towers could compensate for a failed site. Deutsche Telekom said it has AI agents running in its German mobile network that automatically adjusts network parameters during major events.

Rather, the issue is growth and differentiation: turning such technological advances into new sources of revenue.

HCLTech’s survey found that slow product and service innovation was the most commonly cited barrier to capturing revenue from higher-value services, at 49%, followed by skills and operational gaps at 40% and legacy-system costs and limitations at 39%.

The product-development numbers make the problem more concrete. Nearly 80% of respondents said they launched between zero to five new digital products or services in the last year. Only 11% launched more than 11.

That pace highlights the challenge behind what the industry calls the shift from being a ‘telco’ to a ‘techco’ – moving beyond providing traditional connectivity to encompass technology and digital services that can generate new sources of revenue.

Lakkaraju argues the problem is not primarily a shortage of AI experiments. “There are enough experiments done,” he said. “It’s not a question of adoption of AI; it’s a question of adopting at an enterprise scale so that the telecom operators remake themselves as intelligent network providers.”

He identified three broad constraints: organizational change, accumulated technical debt and data.

Telecom carriers often operate decades’ worth of technology at once, spanning wireline and wireless networks and multiple generations of cellular technology and systems from numerous equipment vendors. AI models may be new, but they still have to obtain reliable data from those environments and execute actions through existing operational systems.

“The entire stack needs to be modernized,” Lakkaraju said.

HCLTech’s survey suggests the organizational problem is at least as important. Only 32% of respondents rated their culture as “strong” or “very strong” for digital and AI transformation. Forty-six percent cited resistance to change as a workforce challenge, the same share cited inadequate training and development, and 44% cited a lack of domain experts.

AI efficiency is not the same as a new business

There is an important distinction between using AI to make an existing telecom operation more efficient and using it to create something customers will buy.

Some major carriers are making substantial progress on the first.

AI can help predict network congestion, detect equipment problems and automate some routine corrective actions. More advanced systems are intended to move toward “self-healing” networks in which software can identify and resolve defined problems with less human intervention.

HCLTech’s survey found 40% of respondents were investing in or piloting self-healing networks and automation, while the same percentage were backing data platforms and real-time analytics. Six out of 10 were investing in generative AI and large language models.

But a network that costs less to operate does not by itself solve the revenue problem.

When the survey asked what was preventing carriers from bringing AI-powered and cloud-native services to enterprise customers, the most common answer was not technology. Forty-one percent cited a lack of clarity around monetization and business models. Skills and talent followed at 37%, while roughly one-third cited integration with legacy systems.

That finding goes to the heart of Lakkaraju’s argument.

“Whoever transports more data, they are not going to win the race,” he said. “Whoever makes monetization of the data and the intelligence, they are going to win the race.”

His examples include private wireless networks and AI-enabled services for industries such as mining, manufacturing and retail, where carriers could combine connectivity with computing, data processing and automation rather than simply selling bandwidth.

Partners become part of the strategy

HCLTech’s own response to AI also illustrates another feature of the telecom transformation: companies are unlikely to build everything themselves.

HCLTech acquired products and specialists rather than relying exclusively on internal development. Carriers similarly are building ecosystems around cloud providers, AI vendors, equipment suppliers and systems integrators.

Around half of respondents in HCLTech’s survey consider hyperscalers, AI providers and systems integrators important to future growth.

Lakkaraju said carriers can lead the transition but “can’t do it all,” and will need hyperscalers, specialized technology companies and engineering partners.

That dependence creates its own strategic tension. Carriers want to capture more of the value created on top of their networks, yet many of the technologies required to do that come from companies that also want a larger share of enterprise AI spending.

HCLTech sits on one side of that equation. Its survey identifies the industry’s modernization, skills and business-model problems, while its acquisition strategy gives the company more technology to sell to carriers trying to solve them.

Ultimately, “this shift from telcos to techcos is inevitable. There’s no choice,” Lakkaraju said. Operators that industrialize AI, develop business models around it and assemble the right partner ecosystem fastest “will win.”