Fortune100 Telecoms Company Adopts AI Service and ITAM Best Practices for IBM Watson

The Challenge

Anglepoint’s partnership with this Fortune 100 telecommunications company has helped to transform its ITAM program since 2023. IBM is one of the client’s top-tier software publishers, with the organization spending approximately $70 million per year on its services.

The client, along with other organizations contracting IBM’s services, was encouraged to explore IBM’s AI offering—Watson—through a SaaS or term-based licensing model. These models afford companies a degree of flexibility—allowing them to test the potential benefits of AI Services before committing to a traditional perpetual license agreement model.

The AI service challenges experienced by this global Fortune 100 client are not unique. By 2026, more than 80% of enterprises will have used generative artificial intelligence (GenAI) application programming interfaces (APIs) or models, and/or deployed GenAI-enabled applications in production environments, up from less than 5% in 2023^*. While the anticipated value of AI is driving aggressive adoption, many organizations are moving forward without the necessary governance structures to manage cost, compliance, and value realization. Gartner also predicts that through 2026, organizations will abandon 60% of AI projects unsupported by AI-ready data. This means that organizations should interrogate ROI of AI initiatives to ensure the high cost delivers the anticipated business value.

Key challenges faced by this client—as well as many other organizations in relation to AI services—include:

1. Time to Realize Return on Investment (ROI)

   Innovation remains a strategic priority, but many business leaders are growing wary of the escalating costs associated with AI. Services can require significant upfront investment—up to $750,000 for a single product in some cases—yet measurable ROI may not be realized for years. Organizations are often sold on the promise of long-term value, but hidden costs and delays in operationalizing proof-of-concepts (POCs) can significantly impact ROI.

2. Complexity of License Models

   AI service licensing structures can be significantly more complex than traditional software—often with multiple, and at times competing, license metrics. For example, this organization’s purchase of IBM Watson is governed by four distinct license metrics: Virtual Private Cloud (VPC), documents, users, and installs. It also includes component-based restrictions, where using incorrect modules can result in non-compliance. Seat-based licensing further complicates matters, tying each license to a specific user and device. This organization had also chosen to deploy within Cloud containers, which added another dimension to its licensing considerations. Without expert oversight—such as that provided by a Managed ITAM Provider—organizations are at high risk of non-compliance without being aware

3. Departmental Siloes

   As a large, global telecommunications company, this client has a complex operating model with hundreds of stakeholders across the world. In this case, the client’s ITAM leadership team was not aware that the team was proactively supporting internal AI initiatives. The business stakeholders using the AI services were also unaware of the multiple license metrics applied. This lack of visibility is common, with stakeholders across departments often making independent decisions—unaware of the broader implications for compliance, governance, and cost control.

4. Impact on Sustainability Targets

   AI services can carry a significant environmental footprint. Training a single, large-scale model can generate hundreds of tons of CO₂ emissions—equivalent to the lifetime emissions of dozens of cars. The underlying infrastructure, including GPUs and servers, consumes substantial energy—often sourced from non-renewables—and requires millions of liters of water annually to manage cooling in data centers. These impacts pose a challenge to organizations striving to meet aggressive sustainability targets, while also endeavoring to push the boundaries of innovation and efficiency.

The Solution

Anglepoint already had a comprehensive ITAM program in place for this multi-billion-dollar global organization. As part of its ongoing service delivery, Anglepoint provides continuous license compliance monitoring, remediation management, quarterly Effective License Position (ELP) assessments and Risk & Opportunity Assessment Reports (ROARs) for in-scope publishers. These assessments ensure that the client remains compliant with IBM’s requirements and avoids both under- and over-licensing. Importantly, this scope extends beyond traditional software assets to include AI services delivered through IBM Watson.

In addition, Anglepoint manages the client’s IBM catalog—an agreement structured around an upfront investment that can be drawn down over the term of the agreement. This catalog model enables the client to maintain a pool of software licenses that can be allocated on demand. Anglepoint oversees all software requests, monitors POC activity and evaluates ROI. This ensures that licenses in use are continuously tracked for effectiveness, while unused assets are flagged. This approach not only delivers cost certainty for AI services but also allows the client to explore and evaluate Watson’s capabilities across diverse business scenarios.

During one of its routine quarterly ELP reviews, Anglepoint identified over-consumption in two of Watson’s four license metrics due to an over-deployment of documents and the number of cores under the VPC model. Anglepoint monitored the POC through to confirmation, then promptly initiated a request to draw down the necessary additional licenses from the existing catalog under the Active User Report agreement. This agreement allows flexible license deployment through the end of the contract term, ensuring the client’s continued compliance and optimized use of its AI investment.

Results

The results for this client represent the best practice outcomes that can be achieved by organizations which apply the ITAM framework to all software, including AI Services. These are as follows:

• Proactive Approach to ITAM: A strategic ITAM approach and regular reporting has been crucial in ensuring the client’s AI investments are cost-effective, compliant, and aligned with strategic business goals.
• Continuous Reporting/Tracking: Ongoing tracking through quarterly ELP & ROARs provide clear visibility into AI service usage, enabling adherence to publisher-specific licensing requirements and minimizing compliance risks.
• Remediation of Licensing Gaps: Through leveraging Anglepoint’s expertise, the client successfully identified and addressed non-compliance issues by drawing down additional licenses as required, ensuring alignment with IBM’s stringent licensing metrics.
• Establishment of Governance and Accountability Framework: By establishing clear accountability structures, updating internal policies, and aligning procedures with both regulatory and organizational standards, the client achieved improved governance over AI investments—across people, processes, and technology.
• Comprehensive AI Infrastructure Lifecycle management: Active monitoring of AI service utilization enabled the client to optimize infrastructure resources, reduce unnecessary provisioning, and reallocate underutilized assets—driving efficiency and sustainability.
• Green IT: With closer oversight of the ITAM impact of AI Services, Anglepoint can support clients in parallel to also measure the environmental impact of its AI projects.

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