Industry Spotlight: Accenture’s Dan Rice Talks AI and More

Today we sit down with Dan Rice, Accenture’s Communications & Media Industry Lead for the USA, to look at trends in AI and communications infrastructure.  We last spoke with Dan about a year and a half ago, which is about a generation in the AI infrastructure world. Lots has happened since then in this industry, let alone the rest of the world.  How are things shaping up?

TR: AI is obviously driving much of the news these days, but let’s drill down below the hype. What would you say the most impactful actual use of AI will be in the communications industry in the next few quarters? 

DR: lot of the discussion right now is about autonomous networks, dark NOCs and AI-native BSS transformation. Those things are coming. But the biggest impact over the next few quarters will be much more practical. It’ll be about helping care teams, network engineers and field technicians make better decisions, solve problems faster and spend less time hunting for information.

In care, AI is far past the simple inquiries, as we all know. It can explain a bill, troubleshoot issues and manage appointments, helping operators resolve more issues first time and reduce handling times when escalation is needed.  T-Mobile’s Live Translation is a clear example. The service uses real-time AI built directly into the network to translate phone calls in more than 80 languages, on any phone on the T-Mobile network, without apps, upgrades or special hardware.

The same applies in network operations. AI has turned hours of dashboard reviews into quick work, allowing engineers to focus on problem solving, rather than searching for information.   We’ve seen dramatic reductions here.

TR: There has been much talk of AI agents helping improve customer engagement, but the specifics are rather harder to pin down. How might they actually help in the near term? 

DR: AI is moving from answering questions to taking action.  We’re seeing Agents onboarding new customers, troubleshooting day-one issues and spotting churn signals before a customer calls.  AT&T’s AI Digital Receptionist is a good example. AT&T describes it as a network-based agentic AI helper that can answer calls on a customer’s behalf, ask who is calling and reason, determine whether the call should be let through, take a message, or handle certain interactions like accepting a delivery window. It also uses advanced voice-to-voice and agentic AI to screen calls.

That is where the industry is today – the agent proposes, the human in the lead.  The system executes the actions across customer systems. Fully autonomous customer engagement is still evolving, but the assisted model is delivering value today.

TR: In what ways should telcos be re-imagining their operations to take advantage of Agentic AI? 

DR: Many operators are still looking at where AI can fit into existing processes. The bigger opportunity is redesigning those processes around what AI agents can do.

Order-to-activate illustrates the challenge. Today it spans sales, provisioning, engineering, customer care, field operations and billing, with multiple handoffs along the way. If an agent can coordinate across those systems and manage the handoffs, the process starts to look very different.

The same applies in network operations. Instead of manually reviewing alarms, performance and historical tickets, agents summarize network health, find root cause and prepare remediation.

Verizon’s network automation work is a strong example. Verizon says it is targeting Level 4 cognitive automation to build an intelligent core network that can reason and self-heal. It also says its closed-loop automation platforms executed more than 70 million network configuration changes autonomously in 2025.

That changes roles as much as processes. Supervisors and senior engineers spend less time routing information and more time overseeing agent-led work, handling exceptions and improving the system.  Agentic AI is as much an operating model question as a technology question. Again, we’re seeing people in the lead.

TR: How are companies like Accenture looking to use AI to better serve their customers? 

DR: The question now is where AI can improve performance and how they scale it safely. Clients face three challenges. The first is modernizing complex legacy tech. The second is turning successful AI pilots into something much broader across the enterprise. And the third is understanding how AI changes the way work gets done.

We’ve developed a set of offerings designed to help address each of those areas.

GenWizard is our AI platform for technology delivery. Many operators are still dealing with decades of legacy technology and the complexity that brings with it. GenWizard helps accelerate knowledge capture, application modernization, software development and operations, allowing teams to move faster and improve engineering productivity.

Accenture AI Refinery addresses a different challenge: scale. Many organizations have AI pilots, but no consistent way to manage them across the business. AI Refinery brings together agents, enterprise knowledge, models and governance, helping clients move from isolated experiments to enterprise-wide adoption. We have also announced telecommunications-specific AI agent solutions built on the platform.

The workforce side is just as important. Talent Navigator helps organizations understand how AI changes work itself. It breaks roles down into tasks and helps identify what should stay human, what can be augmented, what can be automated, and what new skills are needed. For operators, that matters across customer care, sales, network operations and field teams.

We’re also seeing a lot more interest in digital twins. One of the biggest challenges with transformation is understanding the knock-on effects before you make a change. Digital twins let operators model changes across customer care, field operations, billing and network assurance before rolling them out in the real world.

For us, AI isn’t a single product or initiative. It’s a set of capabilities designed to help clients modernize technology, scale AI, redesign work and make better transformation decisions.

TR: How quickly is the communications industry’s workforce adapting to an AI-powered reality? Is there a sufficient pool of people skilled enough to do this right yet? How should people prepare for it? 

DR: Some people are using AI every day and have completely changed how they work. Others have access to the tools but are still using them (mainly) for basic productivity tasks.

The shortage isn’t AI engineers. It’s people who understand both AI and industry. A network engineer who understands AI knows when to trust a recommendation and when to challenge it. A care leader who understands customer journeys can help design agents that improve resolution rather than simply deflect calls.

The people progressing fastest are not necessarily the most technical. They are the ones using these tools every day, learning where they help, where they do not, and applying them to real business problems.  Design has always been important, but it’s at the next level now.

TR: Is there any oxygen left for other next-generation technologies right now? What else is driving change in the industry right now? 

DR: Physical AI is the big one. Generative AI can often run in a distant data center. Physical AI can’t always do that. Robotics, autonomous systems, drones, industrial automation, AR/VR for field work and real-time computer vision need low latency, local processing, reliable connectivity, and local data residency.

That makes private 5G, edge computing, cloud-native networks, network APIs, non-terrestrial networks, and quantum-safe security very important. These technologies are increasingly part of the same conversation because they provide the infrastructure AI-enabled services need.

The risk is that operators stay too low in the stack, provide the infrastructure and watch most of the value increase somewhere else. The opportunity is in how AI, cloud, edge, private networks and programmable connectivity come together in a way that gives operators a stronger role in the next wave of digital infrastructure.

TR: Thank you for talking with Telecom Ramblings!

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