The future is intent: agentic AI and the reinvention of BSS

The telecommunications industry stands at a decisive inflection point. Over the past decade, operators have invested heavily in digital transformation—modernizing interfaces, migrating to the cloud, and introducing automation. Yet, beneath these layers of modernization, many business support systems (BSS) still operate on rigid foundations. They depend on manual approvals, static configurations, and fragmented data models that limit agility and customer centricity.

While the industry has made progress, true transformation demands more than digitization—it requires intelligence. The next wave of innovation will not come from faster workflows, but from systems that can understand intent, act autonomously, and evolve continuously.

Beyond transformation: the bottleneck of rigidity

For decades, BSS has served as the operational backbone of digital service providers (DSPs), supporting product configuration, Charging, billing, and customer management. However, these systems were designed for predictability, not for a world defined by real-time personalization and dynamic digital ecosystems.

Consider a familiar scenario: a customer wants to configure a flexible family plan combining weekend data boosts, streaming bundles, and temporary roaming offers. Even in “digitally transformed” environments, this request often triggers a cascade of internal processes—approval chains, catalog updates, and provisioning delays. By the time the offer is ready, the customer’s intent has changed, and the opportunity is lost.

This friction is not isolated. Industry surveys continue to show that a large portion of customer interactions stem from billing or configuration issues—areas still bound by legacy logic. In parallel, one in seven mobile users globally switch providers each year, citing poor personalization and inflexible plans among their top reasons. These statistics underscore a reality: today’s BSS modernizations have improved efficiency, but not responsiveness.

To meet the demands of the intent economy, BSS must evolve from process-driven systems to purpose-driven intelligence—able to interpret, decide, and act in real time.

Agentic AI: the catalyst for intent-driven operations

This is where agentic AI comes into play. TM Forum’s AI & Data Mission identifies agentic AI as a core pillar of the AI-native blueprint—enabling systems that can perceive context, interpret intent, and execute autonomously across digital ecosystems.

In an intent-driven BSS, Agentic AI agents perform three essential roles:

• Interpret intent: translate customer or business objectives—expressed in natural language or policy terms—into operational logic.
• Align with context: map intent to catalogs, rules, and governance constraints, referencing data standards and interoperability principles from TM Forum’s AI-Native Data Architecture (IG1356, IG1424).
• Execute autonomously: orchestrate actions across microservices and APIs aligned with the Open Digital Architecture (ODA), ensuring seamless enablement and assurance.

Unlike traditional automation, which executes pre-defined workflows, agentic AI continuously learns from outcomes, refining decisions to improve efficiency and personalization. It represents a step-change from reactive process automation to proactive, cognitive orchestration—the foundation for real-time intent fulfilment.

Reimagining BSS with AI-native principles

TM Forum’s AI & Data frameworks—including GB1003 AI & DA Maturity Model and GB1077 AI for ODA Components—outline how AI can become intrinsic to enterprise architecture. Applying these principles to BSS reveals a powerful evolution path:

• From rules to reasoning: replace static decision trees with AI models capable of reasoning about business outcomes and intent-based policies.
• From configuration to collaboration: enable BSS components to act as intelligent agents collaborating across domains—sales, billing, assurance, and care—through shared ontologies and intent models (IG1421 MAS Ontology Model).
• From automation to autonomy: move beyond workflow automation toward closed-loop, self-learning BSS ecosystems built on AI Closed Loop Automation principles (GB1064, IG1414).

By embedding AI and data governance practices defined in TM Forum’s GB1023 Data Governance Guidebook and IG1336 Data Governance Checklist, DSPs can ensure that intent-driven operations remain ethical, transparent, and compliant.

A new operating paradigm: BSS as a living system

An intent-driven, AI-native BSS will no longer act as a static system of record—it will function as a system of reasoning and response. Through continuous learning, it can adapt product portfolios, detect customer behaviour, and optimize offers in real time.

Key benefits include:

• Adaptive personalization: real-time intent understanding drives hyper-relevant experiences and reduces churn.
• Operational agility: intent-to-execution cycles shrink from weeks to minutes, accelerating innovation.
• Sustainable IT investment: AI-native architectures reduce maintenance overhead, freeing up capacity for continuous value creation.

Ultimately, BSS modernization is not just a technology upgrade—it’s an architectural and cultural shift toward autonomous business enablement.

The future is intent

The reinvention of BSS through Agentic AI marks the beginning of a new era for DSPs. Guided by TM Forum’s AI-Native Blueprint and ODA, the industry can move beyond incremental automation to systems that understand, decide, and act autonomously.

As intent becomes the universal interface between business ambition and system execution, BSS will evolve into the digital nervous system of the enterprise—responsive, intelligent, and always aligned with customer and business intent.

The future is not merely digital. The future is intent – and it has already begun.