Enterprise Sovereignty and CSPs Controlling Their Own Destiny in the AI Era

Enterprise sovereignty refers to a CSP’s ability to retain full authority over its data, processes, models, and business outcomes that are free from unclear dependencies, vendor lock-in, or externally controlled intelligence. In highly regulated, mission-critical environments like telecoms, sovereignty is foundational to trust, resilience, and competitiveness. CSPs cannot do everything in-house, so they need to build a plan that leverages the opportunities of fast-moving AI technology. But they also need to be aware of the danger of vendor lock-in, where they could find themselves at a dead-end, with ever increasing services costs, no way to escape and the intelligence that is increasingly being used to run their business being controlled by a 3rd party.   CSPs need to build a healthy strategy between AI mainstream evolution and their localisation requirements to benefit from the industry-level evolution, but also to keep the ratio of costs to benefits in control.

Who can CSPs best trust to provide AI solutions that will deliver all the operational and cost benefits of AI while ensuring that CSPs have enterprise sovereignty?

As CSPs add more AI agents to their daily operations, we’re seeing a move from AI answering questions to carrying out tasks. Also, as the use of AI expands from customer care to revenue management, sales management and marketing personalisation we’re seeing an increase in the reach and scope of AI in CSPs’ daily operations. A question needs to be asked about who owns, manages and gains from the intelligence that is increasingly being used to run CSPs’ operations and what approach is being used by suppliers of AI solutions.

Qvantel’s AI Strategy – Open, Partnership Approach that Puts CSPs in Control

Qvantel’s model aligns naturally with CSPs that value enterprise sovereignty.

By combining:

• Domain-specific AI agents designed for telecom business processes that are open by design to enable these pre-built agents to evolve to new intents by the CSP and be part of the CSP’s orchestrated agents.

• An open AI framework that provides enhanced features that include security, guard-rails and transparency to enable CSPs to design, deploy, and govern their own agents as part of an enterprise-grade ecosystem, which includes the orchestration of the different agents and sub-agents.

• A product-first architecture that minimises dependency on external services-heavy software customisation.

Qvantel enables CSPs to adopt AI on their own terms. This enables CSPs to gain the operational benefits of AI while maintaining enterprise sovereignty. But not all CSPs are equal, and there will be different AI strategies in play. Some will want an open and powerful platform to build their own agents, and others may want to leverage part or all of ready-made agents. By offering a range of options, Qvantel’s aim is to provide the flexibility and freedom for CSPs to select best fitting AI strategy for them without lock-in.

Qvantel’s approach to AI is not as a black-box solution to be delivered, but as a capability to be governed and evolved by the CSP. This involves providing agents to support initial business use cases and also an open AI framework that allows CSPs to design, deploy, and govern their own agents. This includes flexible and open orchestration for the AI ecosystem, as well as the link to security and transparency with guardrails to ensure an enterprise-grade solution.  This provides CSPs the ability to harness BSS data on customers, events and interactions, services, monetization logic, and more.

The agents that Qvantel provide cover customer self-care, B2B sales management, operations management, and product catalog support. These are useful to get CSPs up and running with agentic AI support for business-focused use cases. In addition to these pre-built agents, we also supply several AI-enabled MCP services to interact with the Qvantel Flex Suite. To ensure enterprise sovereignty, the Qvantel Flex AI Experience Framework provides the toolkit to enable CSPs to build their own agents. It includes open interface support, life-cycle management, and enterprise-grade security. This provides security and trust management, governance and control. The AI Framework also provides no/low code configuration and is LLM agnostic, enabling the CSP to use the LLM that best fits their strategy.

This open, partnership-led approach puts the CSP in control. This empowers them to innovate independently while accelerating time-to-value, and it also delivers enterprise sovereignty to CSPs, ensuring that they are in control of their own destiny.

Key advantages include:

1. Openness and Control by Design
Qvantel’s AI framework is built to run within the CSP’s chosen environment—cloud, on-prem, or hybrid—ensuring data residency, security, and compliance remain fully under CSPs’ control. In addition, CSPs can also use any LLS/SLM.

2. Transparency and Control 
Being open by design, Qvantel’s Flex AI Experience Framework expose models, agents, workflows, and decision logic. This allows CSPs to understand why an AI system behaves the way it does, an essential requirement for regulated industries and mission-critical processes.  

3. AI Evolution Path  
By providing pre-built agents as a starting point and having the option to deploy an AI framework where the CSPs build and manage their own agents in a secure environment, Qvantel is providing CSPs with an AI evolution path. This enables CSPs to manage AI evolution at their own pace and implement a strategy that is driven by their requirements.

4. Scalable Innovation Beyond Internal Automation
Once CSPs use the Qvantel Flex AI Experience Framework to build their own agents, they can scale and evolve them across markets, brands, and use cases.  This includes providing enterprise use cases to support complex B2B customers and complex, multi-party ICT offers. Compared to a service-heavy delivery model, this can drive operational velocity and deliver significant cost savings.

Qvantel’s philosophy has always been about empowering CSP to innovate and have control over their business. We were pioneers in the use of no/low code in BSS and enabling CSPs to make process and rules changes themselves. This philosophy is now continuing with the Qvantel Flex AI Experience approach.

The Sovereignty Challenge with Services-Heavy AI Providers  

Companies with a high percentage of revenue derived from professional services often struggle to align with sovereignty-driven CSPs when it comes to AI. The issue is structural, not technical, and the problem is due to the business models and way of working of service-heavy vendors.

Services-led models typically depend on:

• Proprietary implementations and custom coding

• Human-mediated expertise rather than reusable product capabilities

• Long-running engagements that centralise knowledge outside the CSP and inside the service-heavy vendor, who then capitalises on this knowledge and expertise in other projects.

Using a services-heavy approach in order to implement AI solutions, as this creates several risks for sovereignty-minded CSPs. These risks include:

1. Dependency on External Expertise
AI systems built primarily through services often require ongoing vendor involvement to evolve, tune, or even operate effectively. This shifts knowledge—and control—away from the CSP and into the supplier. 

2. Limited Transparency and Explainability
Services-centric AI solutions tend to bundle logic, models, and workflows into custom implementations that are difficult to inspect, govern, or adapt independently. This undermines a CSP’s ability to audit decisions, ensure compliance, or adapt AI behaviour to changing business needs.

3. Incentives Misaligned with Autonomy
When revenue is driven by billable hours rather than product value, there is little commercial incentive to simplify and standardise. 

4. Slower Innovation and Higher Long-Term Cost
CSPs operating at scale need AI systems that evolve continuously. Services-heavy models slow this down, tying innovation cycles to project timelines rather than product roadmaps and internal teams.

For CSPs that view AI as a strategic asset and not an expensive service, this model is misaligned. In addition to enterprise sovereignty, there are other questions a CSP should ask if they are discussing an AI strategy with a services-heavy company. These include the applicability of a service model in a very fast-evolving technology stream and the flexibility to react quickly to utilise new innovations. Also, with service models, there is the question of costs. Currently, AI costs are not predictable, so the cost-benefit and AI-driven revenue uplift analysis needs tight end-to-end control and correction cycles.
 
Conclusion

CSPs must choose partners that reinforce their enterprise sovereignty. AI will increasingly define how CSPs compete. Sovereignty determines who controls that advantage.

Services-heavy AI providers may deliver short-term results, but they often do so at the cost of long-term autonomy and control. As an open, product-focused company, Qvantel offers a more sustainable path where CSPs remain the architects of their own intelligence, innovation, and future.

To find out more about how Qvantel can deliver AI solutions that put CSPs in control, book a demo.  

Bernhard Kraft
Sr. Director, Product Management

Chrisaman Sood
Product Manager (Agentic AI)