Open CTI end of life announced for February 28, 2028.
Salesforce’s move from Open CTI to Salesforce Voice reflects a broader shift from screen-driven contact centers to signal-driven architectures built for real-time AI and automation. Open CTI played a critical role in helping organizations modernize voice and scale Service Cloud, but it was designed for human workflows rather than live AI execution. Salesforce Voice natively embeds voice signals, transcription, and routing into Salesforce, creating a foundation for orchestration where humans, systems, and AI operate from the same real-time view. With the right orchestration layer, organizations can transition incrementally, keep existing voice platforms, and introduce AI without disruption, building an architecture that adapts as the contact center continues to evolve.
What can you do to prepare? See More Info →
From Open CTI to Salesforce Voice: Designing the Agentic Enterprise
Some technology transitions deserve more than a brief End-of-Life announcement. The move away from Salesforce Open CTI is one of them. Not because Open CTI failed, but because it worked exactly as intended for a very long time.
Why Open CTI Worked for Its Time
Open CTI was built for a world where people were the center of the contact center. Agents worked from screens. Actions were triggered by clicks. Integrations focused on getting the right information in front of a human at the right time. For that world, Open CTI was the right Salesforce Service Cloud integration model. It helped Salesforce scale Service Cloud. It helped enterprises modernize voice without replacing their existing systems. It solved a clear problem, and it solved it well.
That world has changed.
Why AI Breaks the Open CTI Model
Open CTI came from a pre-AI era. Voice events were mostly there to support human workflows. If information arrived a little late, it was usually fine. If timing was slightly off, a person could adapt. Speed and simplicity mattered more than precision.
AI changes that balance.
AI does not look at screens or wait for buttons to be pressed. It works from real-time signals. It needs to know what is happening on a call as it happens. It needs events to arrive in the right order and at the right moment. If a call connects after AI has already tried to act, the opportunity is lost. If transcription is out of sync with call state, the results are unreliable.
In an AI-driven contact center, timing and order are no longer details. They are requirements.
The Limits of Point-to-Point Integrations in an AI Contact Center
This is where older point integration architectures start to struggle.
Point integrations are good at connecting two systems quickly. They are less effective when many systems need to coordinate in real time. As AI becomes embedded in the contact center, logic often ends up duplicated across integrations. Each system makes its own assumptions about timing and state. Small changes can have unexpected effects elsewhere. Events triggered by user interfaces often arrive too late for AI to do anything useful with them.
This does not mean those systems were poorly designed. It means they were designed for a different kind of problem.
To support AI at scale, a different approach is needed.
Contact Center Orchestration as the Foundation
That approach is contact center orchestration.
Orchestration is about coordinating signals in one place, instead of letting every system guess what is happening. Events are collected, ordered, and shared in a consistent way. Humans, automation, analytics, and AI all work from the same version of what is happening, in real time.
Why Salesforce Moved from Open CTI to Salesforce Voice
This shift helps explain why Salesforce moved from Open CTI to Salesforce Voice.
Salesforce Voice is not just a new integration model. It is the primary entry point for real-time voice signals into Salesforce. It is built to receive live call events in a reliable order, so AI and automation can respond while the interaction is still happening, not after it ends.
Salesforce and the Move to a Signal-Driven Architecture
At the same time, Salesforce itself is changing.
The platform is moving toward a signal-driven architecture. Voice is one signal, but it is not the only one. Business events like a new case being created, a change in customer spend, an account becoming at risk, or an AI insight being generated are increasingly treated as signals too. Instead of being stored and reviewed later, these events can trigger action as they occur.
What matters most is that these signals come together.
Voice events, customer data changes, and AI insights are being brought into a shared execution layer inside Salesforce. From there, they can drive action at scale. That action might be helping an agent during a call, changing priorities, adjusting routing, or allowing autonomous agents to act within clear boundaries.
This is why Salesforce Voice matters beyond voice alone. Voice is one of the most time-sensitive signals in the enterprise. Designing the platform to handle it well raises the bar for everything else.
Modernizing Voice Without Replacing Everything
Just as important is how this transition away from Open CTI can happen without disruption.
Most enterprises already have stable enterprise voice platforms in place. These systems are reliable and deeply integrated. Replacing them all at once is rarely practical or necessary.
A layered approach works better.
Existing voice systems continue to handle call control and media. Salesforce focuses on engagement, productivity, analytics, and AI. An orchestration layer coordinates real-time events, manages transcription, and shares clean signals across systems.
In this model, transcription becomes a shared resource rather than a locked feature. Organizations can choose speech-to-text providers based on their own requirements. The same transcription can support AI assistance, analytics, quality, and compliance without being rebuilt multiple times.
Designing for the Agentic Enterprise
Most importantly, this agentic enterprise architecture does not force a single end state.
Organizations can adopt AI gradually, once the foundation is set. AI features can be added where they make sense. Autonomous agents can be tested in limited, well-defined scenarios. Human-only and human-plus-AI workflows can coexist.
This is what future-proofing really looks like. Not guessing which technology will win, but building a foundation that can adapt as things change.
Open CTI deserves credit for what it enabled. It supported a major phase of contact center evolution. Its retirement marks progress, not failure. Salesforce has made its direction clear. The opportunity now is to move forward thoughtfully, keeping what works and building what the next era of AI-powered contact centers requires.
With the right orchestration in place, organizations do not need to rush. They can move forward with confidence, knowing their architecture is ready for a future where signals, not screens, drive action.
Secure Your Open CTI Buyout Before Time Runs Out
No commitment required.
FAQ: Open CTI, Salesforce Voice, and the AI Contact Center
Salesforce is retiring Open CTI as part of its long-term platform roadmap. Open CTI is no longer receiving new features or enhancements, and Salesforce is guiding customers toward Salesforce Voice as its native, future-ready voice experience.
Yes. Open CTI continues to function today, but it is in a retirement phase and is no longer evolving. Organizations using Open CTI should plan their transition to Salesforce Voice based on their own timelines and priorities.
Open CTI connects voice to the agent desktop. Salesforce Voice is natively embedded in Salesforce and brings real-time call signals, transcription, and routing into the platform so AI and automation can act during the interaction.
Salesforce recommends modernizing voice by moving to Salesforce Voice, which provides native integration with Omni-Channel and Omni Supervisor and supports real-time voice innovation.
No. Most organizations can keep their existing voice platforms and modernize by adding an orchestration layer that connects voice, Salesforce, transcription, and AI.
This approach allows teams to modernize without a full rip-and-replace. Examples of this model in practice can be found here: A Home Improvement Retailer’s Smooth Transition to a Unified Contact Center
The most common challenges are integration complexity, change management, and data governance. Orchestration introduces more real-time signals, which makes upfront architectural planning and cross-team coordination essential.
Many teams address this by defining the architecture early through a structured blueprint process.
Teams reduce disruption by using a design-first, phased approach that allows Open CTI and Salesforce Voice to coexist while new capabilities are introduced incrementally.
By establishing a shared orchestration foundation and piloting changes with a subset of agents, organizations can modernize voice and AI without forcing abrupt workflow changes.
Learn more about this approach here: Migrating from Salesforce Open CTI to Salesforce Voice: A Natural AI Journey
Learn more about this approach here: Migrating from Salesforce Open CTI to Salesforce Voice: A Natural AI Journey
