Summary Bullets:

• AI is driving up voice traffic while also making voice more vulnerable, so voice security needs urgent attention.

• The building blocks are in place, but solutions are fragmented. Voice security needs to be integrated on the carrier network level and backed by strong verification at the business.

Voice security is of paramount importance today. Advances in AI are affecting voice in two ways. First, AI is improving the voice experience as it becomes more interactive, which is expected to increase overall voice traffic. Second, AI can be used to bypass security barriers, significantly raising the threat level. The threat landscape varies depending on the call type, recipients, and network routing (such as international borders); this blog focuses on voice security within customer engagement (particularly contact centers), predominantly in the US.

Voice security in customer engagement is a multi-layered issue that must be viewed from the perspective of both incoming and outgoing calls:

• For incoming calls, the objective is to protect business systems from threats like telephony denial of service (TDoS), i.e., when business operations are flooded with fake calls to disrupt service or demand a ransom, or scammers posing as customers to access sensitive data.

• For outgoing calls, the goal is to ensure customers do not ignore crucial alerts, such as notifications of fraudulent bank activity or delivery confirmations.

The initial safety net for incoming calls must start on the carrier level, where threats like TDoS can be identified and mitigated at the network stage. A carrier helps determine a call’s legitimacy using Secure Telephony Identity Revisited / Signature-based Handling of Asserted information using toKENs (STIR/SHAKEN), a mandatory US government framework acting as a digital notary. The originating carrier attaches a digitally signed certification to each call:

• Full Attestation (Grade A): The gold standard; the carrier knows the caller and confirms they legitimately own the number.

• Partial Attestation (Grade B): The carrier knows the caller but cannot verify they own the number.

• Gateway Attestation (Grade C): The carrier simply passes the call along from an unverified, unknown source.

Relying solely on networks is not enough; spoofed calls can still slip through. Businesses require extra layers like call identification and authentication. Conversely, for outgoing calls, brands must ensure their outreach isn’t mistaken for spam. This is achieved by displaying a branding logo, verified number, and the reason for the call. Notably, ecosystem requirements are stringent—calls without the highest certification grade (Grade A) cannot utilize call branding.

A robust partner ecosystem in the US brings these pieces together:

• SecureLogix orchestrates the screening of incoming calls.

• TransUnion (via its Neustar division) operates a massive database of legitimate business numbers to match callers accurately.

• Pindrop addresses audio authenticity and caller verification once calls pass the carrier gateway and reach the business phone system.

• Hiya and First Orion provide branded calling for outgoing traffic, displaying logos and call reasons.

• TNS, a carrier network hub, operates the data highways that route cryptographic signatures for both initial screening and outbound branding.

While these building blocks are in place, the broader architecture needs attention. Point solutions remain fragmented and are generally sold as add-ons, leaving gaps and placing a costly, complex configuration burden on enterprises. Partner integration should ideally happen upstream on the carrier network routing level to seal the gap at the origin.

Furthermore, stronger verification is required at the business phone system layer, as AI voice cloning makes it easier than ever to impersonate customers. Implementing multi-factor authentication can reinforce this safety net. Finally, for outgoing calls, while cross-carrier interoperability has improved, branded calling can still experience fragmentation depending on the recipient’s mobile operating system and carrier ecosystem.

The post Voice Security in Customer Engagement Has Missing Pieces appeared first on IT Connection.

Summary Bullets:

• Agentic orchestration has been dominating vendor narratives as growing complexity in the CX space is driving the need for a sophisticated coordination system.

• CX agentic orchestration remains fragmented as there are still infrastructural gaps, and trust remains a major issue for customers.

Agentic orchestration has been increasingly occupying CX vendor narratives in recent years, so it is time to take a deep dive into what orchestration is and why it is becoming relevant. Simply put, orchestration is bringing people, workflows, and technology together to achieve an outcome. Depending on how far we stretch the concept, orchestration is not new, and even a deterministic call routing can be described as orchestration. The question is, what is new today and why is orchestration increasingly dominating vendor narratives?

There are two factors bringing orchestration to the forefront: connected customer experience and agentic AI. Connected customer experience came into play with the advent of cloud platforms, making it possible to consolidate the CX IT stack and create a unified system. This enabled data to flow seamlessly between applications and systems for contextual insights before, during, and after customer engagement, reducing fragmented customer experiences. The second factor is the rise of agentic AI, which, as the name implies, involves agents that can autonomously perform tasks on behalf of humans. This autonomy stems from the ability to understand, reason, decide, and act. The projection is that agentic AI will proliferate, acting as digital assistants for workers and customers. While interactions today are still between agentic AI and humans, it is predicted that in the future, they will also take place directly between agentic AI.

What we are witnessing is the rise of a complex CX landscape with numerous actors, including AI, people, and applications, making it necessary to have a sophisticated coordination system. This is where orchestration becomes relevant and even critical. What makes orchestration compelling today is its agentic capabilities with a cognitive layer in the backend. It is probabilistic in nature and can understand, reason, decide, and act on its own, unlike the pre-programmed, deterministic models used for reaching a goal. Agentic orchestration is designed to autonomously map the most optimal customer journey depending on customer intent and stage, as well as determine the most suitable resources, insights, and tools to achieve a given goal. The challenge, however, is that the term is broadly used, and the underlying question is: How agentic are the orchestration layers today?

Agentic orchestration as it stands falls under two classifications: routing orchestration and workflow orchestration. Routing orchestration is when AI autonomously routes interactions to the most suitable agent, while workflow orchestration is when AI determines the optimal customer journey to accomplish an outcome. We see some instances where routing orchestration is deployed and some instances where workflow orchestration is deployed, but in most cases, orchestration remains fragmented across bits and pieces of specific, outcome-driven workflows.

In a true agentic era, orchestration will take place end-to-end across all use cases, but there are infrastructural gaps before such a state could be achieved: LLMs are still reasoning and decision tools and cannot really act although tool calling are used for driving actions; data requires more work, including quality improvement, aggregation, and the development of data graphs; and latency/real-time technology needs to be faster. The most critical factor, however, is trust. Today, AI autonomy and trust work in reverse order. It is a journey vendors are taking as they gradually fill the gaps, but there is still some distance to go before we see a pure state of agentic orchestration.

The post Beyond the Hype: The Reality of CX Agentic Orchestration appeared first on IT Connection.

Summary Bullets:

• Conversational AI is driving a major voice resurgence in customer service by improving the IP voice experience.

• Long call queues on account of human agents being thinly stretched across large call volumes have led to customer frustrations and poor CX, but modern versions of conversational AI are set to change that by taking away the frictions associated with voice.

It was believed that voice would diminish in value as digital channels started to emerge as an alternative to the voice channel. While messaging and chatbots offer cost and scale advantages, GlobalData’s research shows that voice continues to remain a vital channel for connecting with customers despite the frictions. Voice provides instant gratification and tends to be more straightforward to use as it does not involve navigating through messaging channels, websites and so and having to type messages. While the elderly demography tends to prefer voice due to greater familiarity, voice is seen to be popular even with the younger generation.

The modern versions of conversational AI are reinforcing the value of voice by taking away the frictions, leading to improved experience, at least for some use cases. Conversational AI is not new, but the older versions were highly programmed, rigid, and could only answer limited, non-interactive queries. Modern conversational AI relies on probabilistic models, making it highly interactive and capable of closely emulating human agents. This technology has given birth to virtual AI receptionists that handle calls, greet customers, carry out authentication, identify intent, and route calls. This eliminates long queues and grants customers 24/7 access. The value multiplies with real-time translation, allowing AI receptionists to speak multiple languages. This is a game-changer for diverse ethnic groups who do not speak English as a first language, especially when accessing critical local government public services where expressing needs in a native language is vital.

Driven by rapid tech advancements, conversational AI is expanding from basic receptionists into autonomous AI agents. These agents handle tasks like answering queries, booking appointments, and taking orders. To do this, they require robust technical foundations, integrating seamlessly with knowledge bases and CRMs (systems of record) to provide targeted responses. Linked to the right workflows, AI agents can check calendars to schedule medical visits or process restaurant orders. Combined with 24/7 availability and translation, this dramatically elevates the voice experience for customers. Furthermore, non-technical teams can easily build these bots in agent builder studios by simply describing the desired persona and goals, removing the need for complex coding. As 8×8 CEO Samuel Wilson noted at the company’s analyst summit this June, “The next billion voice numbers will go to AI agents.”

Despite the promise, architectural challenges remain. Latency is a primary hurdle; the traditional multi-step process (like speech-to-text) can create latency, leading to awkward pauses that disrupt conversational flow. Robust guardrails are also critical to stop AI from hallucinating false information, which carries severe financial and legal risks. Additionally, backend integrations can be clunky due to poorly documented APIs or failing connectors. Finally, the compute costs for generative (GenAI) and agentic AI remain high and can be prohibitive for many businesses. While agentic conversational AI is still in its developing stages, steady breakthroughs are addressing initial operational hurdles to gradually enhance the contact center voice experience. This ongoing progress will drive deeper adoption of the voice channel, counteracting previous assumptions that voice would decrease in value.

The quest for ever-more automation within customer contact solutions continues apace. There will always be scenarios where human-to-human conversations are the preferred and best option. But to enable companies to offer voice interaction at the scale that customers demand, AI will have to carry a significant share of the burden. GenAI- and agentic AI-powered conversational AI is fundamentally shifting the voice experience in contact centers and customer service.

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