Every day, my inbox brims with enticing promotions and eye-catching events all centered around the buzzword “agentic AI.” It seems like everyone is talking about how AI agents in telecommunications are on the verge of transforming our workspaces or offering step-by-step instructions for seamlessly integrating these tools into our daily routines. But amidst all the hype, what’s the real story behind agentic AI?
In this article, we’re going to dive into the claims about the impact of agentic AI, uncovering why it has become a go-to resource for unified communication providers. I’ll also highlight some of the standout benefits of embracing agentic workflows and introduce you to some of the leading providers on the market.
Key takeaways
- When comparing agentic AI vs generative AI, it’s essential to consider their use cases. Generative AI is used for content creation and answering questions, while agentic AI focuses on automating workflows and managing interactions.
- Agentic AI offers big benefits, including time and resource savings, while also enhancing user experience. By providing customers with 24/7 access to information, you can decrease wait times and free up team members to handle high-priority tasks.
- When implementing agentic AI, it’s crucial to establish strong governance frameworks, including real-time monitoring, role-based access control, audit logs, and human oversight, to manage agent behaviors and ensure ethical and compliant operations.
- Organizations should carefully choose UCaaS providers that support agentic AI based on their specific needs, considering factors like interoperability and support structures, while continuously tracking performance using KPIs like CSAT and AHT.
What is agentic AI, and why does UCaaS need it now?
But first things first, what is agentic AI and why is it such a buzzword amongst unified communication as a service (UCaaS) platforms? Simply put, agentic AI refers to artificial intelligence systems capable of making decisions and taking action independently, without direct human input.
While you may be familiar with LLMs like ChatGPT or Google Gemini, which often operate by having a user provide information to generate content, agentic AI focuses on initiating workflows capable of independent decision-making. This makes them especially relevant for UCaaS providers.
Specifically, UCaaS platforms bring together voice, video, messaging, and support channels into a single, integrated experience. But as organizations scale, managing these channels becomes more complex. To address this, many providers are now integrating agentic AI to automate routine tasks, assist with customer interactions, and ensure workflows stay efficient and responsive without relying on constant human direction.This integration enhances user experience and streamlines communication processes by providing context-aware assistance to contact center agents, customers, and team members. To see how agentic AI can improve processes within different unified platforms, I included a table below showing how your workspace would change after adopting AI agents across five focus areas.
| Focus areas | Legacy unified communication (UC) platforms | Agentic UCaaS platforms |
| User experience | Customers face limitations in support access, confined to business hours for human interaction and reliant on FAQs or knowledge bases outside of those times. | Serves as after-hours customer support for simple inquiries; Reduces wait times during peak hours by managing interactions that human agents are unable to handle. |
| Collaboration | Fragmented communication channels often require oversight from multiple teams or platforms to complete projects or assignments. | Agentic AI ensures seamless cross-channel communication by providing real-time updates on messages and tasks to team members. |
| Meetings & scheduling | Manual scheduling of meetings and event coordination is the responsibility of individual team members. | Has the ability to analyze schedules and set up meetings or appointments automatically, eliminating the need for direct input. |
| Information discovery | Searching for information in your workspace or online consumes valuable time for team members. | Responds to queries, offers context, and retrieves information swiftly and effectively. |
| Delegation & scalability | As the workload increases, human team members may become overloaded when assigned tasks. | Agentic AI anticipates the needs of human staff and steps in to lighten the load even as tasks increase. |
How agentic AI works
Now that you know what they are, let’s talk about how they work. In a unified communications platform, agentic AI orchestrates workflows from the initial trigger through to the execution of specific tasks. To understand how a UC AI agent processes inputs and generates outputs, consider the following steps:
- Event trigger: An agentic workflow begins with a trigger, or some activity that sets automation in motion. For example, when an agent finishes a customer call, it can trigger an AI agent to generate post-call notes.
- Ingestion and pre-processing: If the input is audio, automatic speech recognition (ASR) converts it into text. This is also the step when natural language processing (NLP) detection, speaker diarization, and PII redaction clean and normalize the data.
- Classification: Once the input is ready, the agentic AI analyzes the event to determine the appropriate next steps. This may involve sentiment analysis of the call or reviewing the transcript to classify the type of assistance required.
- Action selection: After classifying the input, the AI selects an appropriate action. In a contact center, this might mean providing the human agent with a call summary, highlighting action items, or offering real-time coaching and feedback.
- Output generation: Finally, the AI delivers a tailored output, whether it’s a summary, suggested actions, or coaching feedback, based on the trigger, classification, and selected action.
- Learning loop: Agentic AI gathers feedback from users, supervisor edits, and performance results to enhance future workflows by learning the context of your workspace. Over time, this leads to improved outputs and a more personalized experience for customers and employees.
Key benefits of agentic AI
If you have heard a lot about agentic AI, it’s easy to get caught up in the hype of adopting a new technology without a clear outline of return on investment. Therefore, the following list includes some of the benefits of adopting agentic AI for different business use cases and how these tools can improve service management and increase operational efficiency.
- Time-saving at scale: As a business grows, managing all the tasks can become even more challenging. With agentic AI, you can save time by letting the agent handle specific functions in your workspace, such as collecting customer feedback or scheduling meetings.
- Workflow automation: While many platforms have some form of automation built in, they often require team members to complete complex configurations. However, with an agentic workflow, automation is managed by the agent instead of requiring extensive setup.
- Fewer manual handoffs: Overall, the main benefit of AI is that it reduces the time spent on repetitive daily tasks, and agentic AI is particularly effective at handling manual tasks in the workplace, like responding to emails, searching for information, or creating a list of action items.
- Improved user experience: Whether you’re interacting with a business or on the other end of the phone, many users feel frustrated when they don’t get help when needed. However, with agentic AI, there’s always a response available for employees’ questions or customers’ concerns.
- Reduced IT admin workload: One of the main advantages of agentic AI is its ability to predict problems before they occur. For IT teams, implementing agentic workflows can help address common issues, like password resets, or notify you about potential risks, such as system failures or data breaches.
Choosing the right UCaaS partner for agentic AI
When selecting a UCaaS provider for agentic AI, several platforms include pre-built or customizable agents and workflow automation to perform specific roles in the workspace. Therefore, it’s important to understand your needs for agentic AI and ensure the interoperability of your various business tools when choosing a provider.
To help you choose the right agentic AI for your organization, I have included a comparison table of the top unified communication providers supporting AI agents as well as their key features and use cases.
UCaaS Providers for Agentic AI
Best for
Monthly starting price
Key features
Advanced call routing
$30
- AI receptionist
- CRM integrations
- Agent assist tools
Contact center tools
$23
- Intelligent virtual assistants (IVAs)
- Skills-based routing
- Knowledge base integration
Team collaboration
$16.99
- Workflow automation
- AI companion
- Self-service support
Agent customization
$4.80
- Microsoft Copilot Studio
- Pre-built agent templates
- Automation across 365 apps
Customer experience management
$37
- Post-call customer satisfaction scores
- AI scorecards
- Appointment management
Risks and rewards: Establishing governance for agentic AI
While there are many benefits to adopting agentic AI and a growing number of UCaaS providers offering these tools, there are also pitfalls to be aware of during their implementation. Specifically, the autonomy of agentic AI means that there is often a lack of transparency in their decision-making, which can make it more difficult to assign accountability and audit these systems. Therefore, it is important to incorporate ethical and compliance controls when allowing these agents to operate autonomously.
Establishing clear governance frameworks and protocols is vital for creating safeguards around agentic AI, such as implementing software or dashboards for continuous workflow monitoring with real-time alerts. Adding security measures like role-based access control (RBAC), audit logs, and fallback to human oversight can also help regulate agent behaviors and prevent unauthorized access or changes to data or systems, as well as ensure oversight of the accuracy of agent output.
Did you know: According to a 2025 study conducted by YouGov for Pegasystems, 42% of workers prioritize improved accuracy and reliability of agentic tools, while 33% want to see increased transparency in AI decision-making.
Best practices for user experience and adoption
For those who are new to agentic AI, this is a good time to consider how you can incorporate these tools into your workspace, such as whether or not your current provider offers agentic AI and how you plan to introduce these tools to your team. While some people are open to new technologies, others may have a negative view of artificial intelligence as a role replacement or surveillance system.
If you want a successful implementation, consider offering feedback sessions before adopting agentic AI to ensure you understand your team’s concerns and their expectations for the technology. You should also do training sessions that introduce how agentic AI can act as a helpful collaboration tool rather than a competitor or a constant critic.
Tip: If you are incorporating agentic AI into a contact center, consider adopting quality assurance software or monitoring tools that make it easier to integrate data privacy standards and uphold compliance requirements that come with handling sensitive data.
For those who have already started to integrate AI agents into their workspace, an essential next step is to track their performance. Pay close attention to your call analytics and reporting dashboards because they hold the key to identifying areas where you can enhance the implementation of AI agents and spotlight instances where these agents are making a significant impact.
For example, tracking key adoption metrics such as usage rates, task completion times, and customer satisfaction (CSAT) scores can create more transparency around the value added from agentic AI. This approach not only optimizes your resources but also empowers you to harness the full potential of AI in your operations.
Embracing the future of agentic AI
Based on the conversations buzzing online and the many benefits that organizations are reaping from adopting AI agents, agentic AI is here to stay. It’s already delivering real-world value, and its role in UCaaS platforms will only grow. So, if you want to stay ahead of the curve, now is the time to start thinking about what’s next.
In particular, I expect agentic AI to become more anticipatory as they learn not just how we work, but what we need before we ask for it. With advances in predictive analytics and forecasting, these systems will begin offering proactive insights that truly improve communication, beyond simple workflow automation.
That said, I’m also paying close attention to the ethical questions surrounding increasingly autonomous agents. As a data curation expert, the AI era demands more transparency, explainability, and user trust in these tools, especially in regulated environments. With that said, I’ve already seen agentic AI make an impact here by supporting compliance through real-time monitoring and data evaluation, and I know there is more to come in this area of the industry.
So, whether you’re looking to automate repetitive tasks like quality assurance or provide smarter, more contextual support to both employees and customers, agentic AI is reshaping how we communicate, collaborate, and lead. But, moving forward, it will be less about what these tools can do for us and more about how to use agentic AI in ways that matter and make sense, with clear safeguards and a focus on supporting team members.
Frequently asked questions (FAQs)
