Utilities are under pressure from every angle with tighter margins, stricter regulation, and competition, all while customers demand immediate resolution and seamless digital experiences. It’s no surprise that AI has become a strategic priority in almost every boardroom. However, a different reality often emerges: AI stuck in pilots, innovation labs, or isolated chatbots that never integrate into the core of day-to-day operations. Insights are generated, dashboards are built, but billing errors still occur, collections still linger, and field crews still respond to avoidable visits.
The truth is, AI sitting on the sidelines doesn’t generate real impact. It’s time to stop treating AI as a science experiment and start treating it as a core capability.
From Experiments to Real AI
According to the Harvard Business Review, 72% of employees wish their collaboration tools were integrated into their daily processes [1]. For utilities, this means moving toward an AI-driven platform capable of perceiving operational events in real-time, predicting commercial outcomes, and automating key decisions throughout the entire business cycle.
Smartflex has been evolving to become a platform that empowers customer care and billing capabilities with embedded intelligence directly into the flows that run your business every day.
Instead of adding AI as a sidecar or a collection of separate tools, Smartflex integrates AI natively into processes such as:
- Billing and revenue management
- Customer care, employee experience, and digital self-service
- Collections and debt recovery
- Field operations and work management
An AI Agent Engine to Transform Customer Operations
At the heart of this evolution is the contextual and AI agent engine, serving as the intelligence layer that equips the billing and customer care platform with “digital co-workers”: AI agents that have a specific role to play, reducing complaints, proposing better offers, avoiding truck rolls, improving collection effectiveness, and more.
These are not simple chatbots that only answer questions. This AI agent engine can:
- Perceive what is happening in real time: new orders, overdue invoices, unusual consumption, complaints, etc.
- Decide the best next action based on business rules, data, and predictive models.
- Act directly inside Smartflex and connected systems, within clear guardrails and with full traceability.
In other words, they behave like a team supervisor: they monitor, prioritize, decide, and trigger actions, but at machine speed and scale.
Transforming How to Run Key Processes
Smartflex’s AI agent engine follows an agentic approach, capable of configuring and orchestrating a set of specialized agents, each focused on a specific business outcome.
Some examples of what these agents can do when combined into flows:
- Revenue & cross-sell: detect customers who are likely to respond to an upsell, select the best offer, propose it through the right channel, and track the outcome.
- Collections & risk: identify invoices and customers at higher risk of default, trigger proactive reminders or tailored payment plans, and automatically update promises to pay.
- Quality of billing: flag anomalous bills before they reach the customer, trigger validation or correction workflows, and reduce re-billing efforts.
- Field operations efficiency: avoid unnecessary site visits by combining consumption data, network events, and customer interactions to recommend remote resolution where possible.
These flows are not running in a separate AI platform. Under the hood, they are triggered by the same events that already move through the billing, revenue, and customer care processes, like a new service request, an overdue bill, a disputed invoice, a work order, and so on.
Trust, Governance, and Security by Design
AI is exciting, but it also raises legitimate concerns: What happens to the customer data? How to avoid unintended actions? How to stay compliant?
Smartflex’s AI agent engine addresses these questions with a strong trust and governance layer:
- Data protection: personal and sensitive data is masked or hidden when it is not strictly necessary for the task.
- Clear guardrails: you define what AI agents can and cannot do, with rules that govern their actions.
- Full traceability: every decision and action taken by an agent is logged, so your teams can audit and explain what happened.
- Private AI models: you can use private language and AI models within your own corporate environment, so sensitive data never leaves your ecosystem.
Measurable Business Value for Utilities
Because Smartflex’s AI is built into the daily operation, it translates directly into measurable results. Utilities and telecoms can expect impact across several dimensions:
Revenue & cash flow
- Fewer billing errors and reprocessing
- Reduced days sales outstanding
- More effective collections and higher recovery of overdue accounts
Customer experience
- Shorter resolution times
- Proactive and predictive self-service
- Traceable and transparent interactions
Operational efficiency
- Less manual intervention in repetitive tasks
- Faster processing cycles
- Lower error rates across core processes
Control & compliance
- End-to-end audit trails
- Security and privacy built into the architecture
- Alignment with internal and regulatory requirements
Agility & innovation
- Easy integration with different corporate systems
- Agents that learn and improve over time with feedback
- Copilots that make front-line teams more productive, not replace them
The future of utilities isn’t about having AI; it’s about having real AI operations.
Why This Matters Now
AI is no longer a differentiator simply because it exists in your company. Your customers don’t feel a “pilot”; they perceive whether their issues are resolved quickly, their bills are accurate, and your digital channels actually solve their problems.
If you are already experimenting with AI, the next strategic question is not “What else can we pilot?” but “How do we embed Real AI into the heart of our operations?”
That is exactly the question Smartflex is designed to answer.
