Unified communications (UC) has reached a point of maturity. For most enterprises, calling, messaging and meetings now look broadly the same across platforms.
Incremental improvements to meeting experiences still matter, but they are no longer decisive.
Instead, buyers are asking harder questions. How does a platform fit into regulated workflows? Can it support industry-specific risk, compliance and operational demands? And can it deliver measurable business outcomes, not just better meetings?
Across healthcare, financial services, retail and the public sector, verticalisation is becoming central to UC strategy.
The shift reflects a broader change in enterprise buying behaviour. Organisations are no longer purchasing tools in isolation. They are investing in platforms that align with how work actually gets done.
A Core Buying Criterion
The move towards verticalised UC is no longer theoretical. It is already reshaping how vendors position themselves and how enterprises evaluate solutions.
Dom Black, Principal Analyst at Cavell, is clear that horizontal differentiation is losing its power. “It’s no longer good enough being the best SME provider,” he says.
“Businesses are wanting to find suppliers who really understand their use case and how they’re going to communicate with their clients and internally in the future.”
This marks a fundamental change in procurement priorities. Buyers want partners that understand their industry language, workflows and pressures. Feature lists matter less than relevance and credibility.
As Black notes, this shift has implications across the market. “I think this is going to force everyone in the market to really rethink how they go to market, what kind of collateral they’re putting out there, but also how they can build solutions that can really target these specific verticals.”
Operational AI into industry workflows
Verticalisation is accelerating because of how AI is being applied. Analysts increasingly point to operational AI, rather than meeting intelligence, as the next competitive battleground.
Craig Durr, Chief Analyst and Founder of the Collab Collective, argues that attention is shifting behind the scenes. “I believe the next AI battleground isn’t going to be in the meeting experience,” he says.
“It’s operational AI and it’s aimed squarely at the people who are there to keep these environments up and running.”
Durr highlights the scale of the operational challenge facing IT teams.
According to analysis from the Collab Collective, more than 1.5 million video conferencing devices are expected to be deployed in 2026, driven by overlapping hardware replacement cycles. This puts pressure on reliability, support and uptime, especially in complex enterprise environments.
Operational AI, Durr argues, changes the model. “Instead of reacting to outages, systems will run daily room checks. They’ll flag degrading components and they’ll fix common issues automatically.”
In vertical contexts, this proactive approach is critical. High-stakes environments cannot afford reactive support. AI agents that understand both the technology and the context in which it operates are becoming essential infrastructure.
Governance and security move to the foreground
As UC platforms take on more autonomous roles, governance becomes central. The ability to explain, audit and control AI-driven decisions is emerging as a key differentiator, particularly in regulated industries.
Melody Brue, Vice President and Principal Analyst at More Insights and Strategy, describes UC platforms evolving into orchestration layers.
These platforms coordinate specialised AI agents across departments and systems. However, she stresses that technology alone is not enough.
“The competitive separator for enterprises isn’t the AI itself,” Brue says. “It’s governance and explainability.”
She points to the questions now facing enterprise leaders.
“Who decides when the system acts autonomously versus when it surfaces recommendations in human review? How do you audit these decisions for regulatory compliance?”
Irwin Lazar, President and Principal Analyst at Metrigy also echoed these concerns. warning that AI itself is becoming a target.
“Unfortunately I think we’re going to see significant attacks on AI and AI infrastructure.”
Lazar notes that preparedness remains uneven. In research based on more than 300 organisations, just 58 percent have established an AI security strategy.
For verticalised UC, this gap represents both risk and opportunity.
Human expertise remains essential
Despite the rise of automation, none of the experts suggest that verticalisation is about removing people from the equation. Instead, the strongest vision for 2026 blends AI with human judgement and domain expertise.
Satish Upadhyaya, Founder of The North IT Consulting Services, emphasises this balance. “It is not just about having AI. It is about deploying intelligent agents that are trained, guided and maintained by people who understand the real business problems.”
In his view, differentiation comes from how organisations combine automation with oversight. “The organization that can blend AI-driven automation with human oversight will be the ones who truly differentiate themselves.”
Workforce adoption also plays a role.
Zeus Kerravala Founder and Principal Analyst of ZK Research predicts a shift in employee attitudes. “In 2026, workers will say, ‘How did I ever do my job without it?’”
For enterprise leaders, the lesson is clear. Verticalised UC strategies must invest in trust, skills and change management, alongside technology.
Conclusion: Verticalisation becomes unavoidable
By 2026, verticalisation will no longer be optional. As UC platforms converge on core functionality, value will be defined by how well they integrate into industry-specific workflows, governance models and operational realities.
For CIOs, CISOs and executive leaders, the challenge is to look beyond features. The real question is whether a platform understands the business it is meant to serve.
The next phase of enterprise collaboration will not be about making meetings smarter. It will be about making organisations work better, at scale, in the environments that matter most.
