As communications service providers (CSPs) look to boost network operations with AI investments, the technology faces mounting scrutiny amid growing cybersecurity concerns. SAS, a global leader in data and AI, has announced its commitment to advancing the development of AI governance guardrails through its intent to co-chair the AI Security and Governance Workstream within TM Forum’s AI-Native Blueprint Project. 

A global industry association for service providers and their suppliers in the telecommunications industry, TM Forum is dedicated to empowering CSPs to improve their operational agility through the AI-Native Blueprint Project. 

“Agentic AI is rapidly eclipsing every other technology priority for CSPs as they work to modernise, scale, and ultimately trust AI-driven operations,” said Guy Lupo, TM Forum EVP, AI and Data Innovation. “CSPs must now innovate their engineering foundations and build the confidence to safely shift decision-making from humans, to assistants, and eventually to autonomous agentic systems.."

TM Forum’s AI-Native Blueprint provides the industry’s first structured path to move CSPs out of the lab and into production, enabling the transition from experimentation to minimal viable agentic AI and, ultimately, trustworthy and responsible AI at scale.

The first version focuses on three foundational challenges:

  • Data Products Lifecycle Management: Moving from data projects to discoverable, governed data products that agents can access without human intervention.
  • Security & Governance: Establishing security patterns for agentic interactions and setting the foundation for responsible AI governance.
  • Model as a Service (MODaaS): Defining how CSPs can source, operate, and scale multi-model environments across cloud, on-prem, and edge with consistent metrics, controls, and operational requirements.

SAS helps CSPs implement responsible AI 
As co-chair of the Security & Governance Workstream, SAS contributes a robust background in AI governance, risk management, and security, along with a demonstrated history of real-world success. SAS helps CSPs adopt AI responsibly and align with regulatory frameworks, all while accelerating innovation.  

According to a recent survey from SAS, 57% of organisations plan to moderately increase their investments in responsible AI, aligning with data that shows organisations without strong AI governance underperform. SAS’ AI Governance Map exemplifies this commitment, offering organisations a clear framework for managing risk and transparency in AI deployments.  

“An inability to trust AI’s security foundation can be the downfall of any number of promising AI projects,” said Reggie Townsend, Vice President SAS Data Ethics Practice. “Our collaboration with TM Forum ensures that AI adoption delivers measurable business value without compromising integrity.”

Driving real business outcomes  

SAS has a proven track record of helping its telecom customers achieve tangible results with AI. In telecom, SAS supports CSPs in a variety of business areas such as network, customer intelligence, risk, fraud and revenue assurance. By using automated decision-making, customers can improve their market position, streamline operations, and more.  

Notable customer improvements include: 
  • Optimised telecom network investments   
  • Customers have reduced network rollout time by 40% compared to traditional design methods 
  • Customers have seen payback in as little as seven months with net benefits estimated at up to $5.2 million  
  • Improved call centre productivity with AI agents 
  • Customers have reduced complaint handling time by up to 40% and increased the volume of complaints handled by up to 20%  
Upon conclusion, the AI-Native Blueprint Project will be unveiled at TM Forum’s Digital Transformation World Ignite, taking place June 17–19, 2026, in Copenhagen. This flagship event will showcase how the blueprint enables CSPs to accelerate innovation, engineer for scale, and operate with trust across the telecom industry. Learn more at https://dtw.tmforum.org/.  

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