Telecom AI Deployment: From Pilots to Performance
By Rishi Modha and Mark Mulcahey – Vice Presidents, Strategy & Analytics
Telecom executives are excited about AI’s potential, yet most organizations remain trapped in endless pilot cycles. This disconnect reveals a difficult truth that successful organizations will need to confront, and soon: scaling AI isn’t a technology problem, it’s an organizational transformation challenge.
This post will provide insights to help you understand what’s needed to navigate the transition to AI-driven operations with conviction.
The AI Value Gap
AI is driving significant transformation across the telecom industry, impacting everything from workforce development to operational efficiency. Telecom leaders are now embracing AI-powered solutions to streamline operations and improve customer experiences.
Industry executives believe in the importance of AI on strategy[1]:
- 80% believe AI is crucial for their company’s future success
- 49% are actively adopting or assessing generative AI
This enthusiasm is warranted – AI applications are already delivering measurable impact across many functional areas including network, field, customer, sales, and marketing.
Yet, despite buy-in and early wins, a significant gap persists between AI’s demonstrated potential and widespread organizational adoption.
Studies show that most companies struggle to scale AI beyond pilots[2]:
- Just 16% of surveyed CEOs report AI initiatives being scaled enterprise-wide
- Only 25% of AI initiatives have reportedly delivered expected ROI over the last few years
So, while there are plenty of use cases and success has already been seen, most operators struggle to scale these victories into enterprise-wide transformation. Now leaders must recognize that the barrier to do so is not about having the right tools or technology capability, it’s about building the organizational muscle and flexibility needed to tackle change head-on.
The Implementation Challenge
The scaling challenge becomes clear when examining the barriers. 43% of telecom professionals cite the need for AI experts as the key obstacle to scaling, a sharp increase from 24% the year prior[3]. This talent crunch reflects a deeper organizational readiness gap.
Many operators have successfully deployed AI for specific use cases: predictive analytics for network management, AI chatbots for customer service, and automated field operations, among others. These wins demonstrate technical feasibility but remain isolated events, rather than becoming integrated across the organization.
The real challenge isn’t just finding the right AI tool; it’s developing the organizational capacity, skills, capabilities, and resource plan to systematically implement, manage, and scale AI initiatives across complex environments.
The four biggest organizational barriers that prevent AI initiatives from reaching their full potential are:
Data Fragmentation: Data exists in functional silos today across customer, field, network and other teams, which creates silos that limit AI’s contextual intelligence and cross-functional insights.
Talent and Expertise Gap: With 43% citing lack of AI experts as the primary scaling obstacle (up from 24%), organizations lack the internal capabilities to design, implement, and maintain AI systems at enterprise scale.
Organizational Alignment: Without clear accountability for AI deployment across functional organizations, initiatives stall as teams struggle to coordinate priorities and resources.
Change Readiness: When employees don’t understand how AI enhances their work or fear displacement, deployment slows, and adoption suffers regardless of technical performance.
Building Organizational Strength
Successful operators recognize that scaling AI requires building organizational muscle, not just deploying technology.
They treat AI transformation as a comprehensive capability-building exercise across six dimensions:
Strategic Vision & Workflows: They develop a clear view of what the business needs generally, rooted in current operational pain points, existing and developing customer needs, and future business benefits, and where AI should be integrated. Successful operators consider greenfield approaches that may unlock greater potential by redesigning workflows entirely versus looking to optimize existing processes.
Clear Ownership & Governance: They clarify decision rights and organizational boundaries, rearchitecting structures to simplify accountability. They eliminate unnecessary committees while maintaining appropriate governance checks and balances to mitigate risk without slowing progress. They understand the reputation implications, brand, and customer impacts of their actions.
Data & Technology: Successful organizations bridge data silos and misalignment by clarifying data ownership and establishing appropriate feedback loops to power AI applications. They build platforms that enable information flow across previously disconnected or misaligned systems.
People & Talent: They are explicit about intentions and staffing strategy, especially around whether AI will augment roles, require reskilling, or involve restructuring. Designing a thoughtful approach to address industry-wide talent shortages is key, as is designing and communicating this thoughtfully to cut through resistance and build employee confidence in, commitment to and support for the transformation.
Transparent Communication: Leading organizations maintain clear, ongoing communication about the plan, progress, and learnings. They create a simple message that keeps the organization aligned on both successes and setbacks to sustain momentum and trust.
Continuous Improvement: The top organizations recognize that the initial vision will likely not be the final outcome. Build measurement, checks, balances, and accountability into the design from the start, not as an afterthought, to ensure progress towards sustainable value creation.
Moving Forward
The telecommunications industry stands at an inflection point. Operators that build organizational flexibility to scale AI systematically, rather than hoping individual pilots will somehow connect, will capture the full value of this transformation.
The question for telecom leaders is straightforward: Will your organization develop the muscle to scale AI capabilities enterprise-wide, or remain in the pilot-to-pilot cycle while competitors build systematic advantages?
Success requires organizational transformation. The technology is ready, but is your organization?
With 35+ years of experience helping TMT organizations stay ahead of major industry shifts, Cartesian can help you through the noise. From building practical roadmaps to designing new performance evaluation tools, we help you move forward with clarity—so you’re not left behind. Contact us today.
