For years, the meeting room industry has measured interoperability with one question: how easily can a room join a meeting hosted on another platform? If your organization runs Microsoft Teams Rooms (MTR), joining Teams meetings is easy. Ideally, users should also be able to walk in, tap a button, and join a Zoom, Webex, or Google Meet meeting. In my latest article, I argue we may be asking the wrong question. Rather than "How easily can I join the meeting?" we should be asking, "How easily can I accomplish everything I came to the meeting to do?" As meeting platforms evolve well beyond audio, video, and screen sharing, that distinction matters more and more. Direct Guest Join: Simple, But Limited Microsoft's Direct Guest Join (DGJ) delivers a genuinely simple experience: find the meeting on the room controller, tap Join, and you're connected. For organizations standardized on MTR, joining other platforms without changing equipment or requiring a laptop is genuinely useful. For attendees who mainly need to listen, speak, and view a presentation, DGJ may be all they need. The limitations surface when users need to do more, and they can become critical when you are hosting. Microsoft's current DGJ implementation does not support sharing content through the room's HDMI input, interactive whiteboarding, or controlling the meeting lobby. It also carries restrictions on video resolution, display configurations, and access to certain collaboration features. Enhanced SIP connectivity closes some of the gap, supporting 1080p video, two displays, and HDMI content sharing. However, it is a paid interoperability service that requires a SIP dialing plan plus additional Exchange and tenant configuration. Neither DGJ nor SIP interoperability offers the complete functionality of the meeting platform's native application. An Interesting Alternative From Barco This is why I believe organizations evaluating Teams Rooms should take a serious look at Barco's ClickShare Hub. Barco's approach doesn't require abandoning an investment in Microsoft Teams Rooms. The Hub Core and Hub Pro provide a native, certified MTR experience when deployed with supported peripherals, so Teams meetings work with the familiar room controller and management capabilities. When someone needs to run a Zoom, Webex, or Google Meet meeting, they plug a ClickShare Button into their laptop, connect wirelessly to the room's camera, microphones, speakers, and display, and use their normal conferencing application. The important nuance: Zoom or Webex isn't running natively on the MTR. The meeting runs on the user's laptop, using the room's professional AV equipment. Employees use the platform exactly the way they already know how. The Experience Beyond Joining Consider an employee hosting a customer meeting on Zoom. With DGJ, they can join from the Teams Room, but may still need their laptop for host controls, content sharing, chat, or other features DGJ doesn't expose. Many end up joining the same meeting twice: once from the room for audio and video, and once from the laptop to collaborate and manage the meeting. That works, provided laptop audio is handled correctly, but it adds complexity. With ClickShare, the host uses the familiar Zoom application, with whatever host controls and collaboration capabilities their account and meeting settings permit, while the room handles the AV. There is no juggling two separate conferencing endpoints. The benefit extends beyond the meeting itself. Using a personal, authenticated client keeps recordings, transcripts, summaries, and follow-up activities connected across scheduling, conducting, and following up. DGJ doesn't prevent access to those materials afterward, but the room's guest experience sits apart from the user's own meeting account, which adds friction. The key differentiator isn't that joining is easier. It's that employees use the platform the way they already do on their laptops, while benefiting from the room's professional AV. That consistency has value. Can Direct Guest Join Ever Keep Up? Meeting platforms are evolving rapidly as AI becomes embedded in the experience: meeting assistants, transcription, translation, summaries, intelligent content, and automated actions. Each platform has its own implementation, identity requirements, licensing, and approach to exposing those capabilities to other applications. For DGJ to keep pace, that functionality must be available through the interoperability mechanism and supported by the room system. Because DGJ relies on the host platform's WebRTC experience, some improvements can arrive through the meeting provider's own updates. Still, there are architectural limits; features that work beautifully in a native client may not reach an interoperable room experience. And even native room systems don't support every capability of their desktop counterparts. My view: DGJ will likely always be playing some degree of catch-up. Not because Microsoft isn't investing, but because interoperability and native application functionality are fundamentally different propositions. As conferencing platforms become intelligent collaboration environments, that difference may become increasingly significant. ClickShare Isn't Without Compromises None of this makes ClickShare automatically the better choice. DGJ is excellent for straightforward meetings, especially when users simply want to walk in and join without opening a laptop. ClickShare requires a compatible laptop, adds another device to the workflow, and depends on the wireless connection and room peripherals working correctly. In practice, though, most employees already run meetings from their laptops when they aren't in a meeting room, so it is a familiar workflow rather than a new one. For organizations that primarily use Teams and only occasionally join meetings hosted elsewhere, DGJ may be perfectly adequate. Other options are also worth evaluating, including enhanced SIP interoperability services, wired laptop connectivity, and room systems that support more than one native meeting platform. The point isn't that ClickShare is universally superior; it's that it represents a different, viable approach to the interoperability problem. It's Time to Rethink How We Measure Interoperability Today we tend to judge room interoperability by which platforms a room can join, whether one-touch join is supported, and whether audio, video, and content sharing work. Those measures are important but increasingly insufficient. Organizations should evaluate the complete meeting workflow: scheduling, joining, presenting, collaborating, hosting, and following up. Can employees accomplish what they need without workarounds? Can they use the platform's features? Can they run the meeting with tools they already know? A room that joins every platform but restricts what people can accomplish isn't necessarily better than one that requires an extra step to connect. Successful meeting room interoperability shouldn't be measured by whether users can quickly join a meeting. It should be measured by whether they can accomplish everything they came to the meeting to do. As AI continues to reshape meetings, I suspect that distinction will only grow in importance. Update: Microsoft Cross-Platform Meeting Connect On the day I planned to publish the original article, Microsoft announced Cross-Platform Meeting Connect, which in the future intends to address some of these interoperability issues. Key points for now: it is not yet available; Zoom currently says it will arrive before the second half of 2027; and Microsoft hopes other vendors will announce participation soon. I think it's a great initiative, and I'll provide updates as features become generally available. My analysis focuses on what is available today. And the question I asked about DGJ, whether it can ever keep up, applies equally to Cross-Platform Meeting Connect. This post summarizes my original LinkedIn article. Read the full piece and join the discussion in the comments on LinkedIn.

Zoho is making a significant move in the evolution of business intelligence (BI), repositioning Zoho Analytics as an agentic analytics platform that connects business data, context, AI-driven insights, and actions. The goal is to move beyond reporting and dashboards to help businesses understand what their data means and use those insights to make decisions and trigger workflows. The announcement reflects a broader shift in enterprise AI. As organizations begin deploying AI agents, access to data alone isn't enough. Agents also need to understand how a business operates, how its metrics are defined, and how different pieces of information relate to one another. Without that context, even a technically correct answer can lead to the wrong business conclusion. Zoho is addressing this through what it calls a trusted intelligence layer, built into the Analytics platform rather than requiring a separate data platform or cloud data warehouse. Business context is the foundation Two of the most important elements of the update are the new semantic and ontology layers. The semantic layer provides a business glossary for AI, standardizing terminology, synonyms, instructions, and metric definitions. This matters because organizations often use the same terms differently across departments. Revenue, for example, may have different definitions depending on the business context. Giving AI a consistent understanding of those definitions should help improve the relevance and repeatability of its answers. The ontology layer goes a step further by modeling business entities and their relationships. This gives AI a structured understanding of how the business fits together, rather than treating every data point as an isolated fact. These capabilities are particularly important as businesses move from asking AI to retrieve information toward asking it to analyze problems, recommend next steps, and take action. The quality of those decisions depends on the quality of the underlying data and business context. Zoho says these capabilities are native to Analytics, can be configured without code, and support multiple semantic models for different business contexts. The platform also adds more than 30 data connectors to its existing base of more than 500, including integrations with Zoho applications, SAP, Twilio, Intercom, PayPal, and other enterprise applications and databases. The broader opportunity is to reduce the disconnect between business intelligence and the systems where work actually happens. From asking questions to taking action Zoho is also upgrading Ask Zia, its conversational BI agent, with a multi-agent architecture. A central agent coordinates six specialized agents covering data analysis, data modeling, visualization, data preparation, coding, and actions. The idea is to let users move between tasks without losing the context of the conversation. A user might begin by investigating a business performance issue, prepare additional data for analysis, and then build a workflow based on the findings. Organizations can also build custom agents grounded in their own data, semantic models, and knowledge bases. These agents can connect to external tools through the Model Context Protocol (MCP), web search, and other integrations. Zoho is also introducing agentic actions that allow agents to trigger workflows directly. Another important aspect is that Zoho is extending its analytics capabilities beyond its own interface. Through MCP, a command-line interface, and a Claude plug-in, developers and external agents can access Analytics capabilities. Organizations can also embed agents in their own applications and portals while retaining permissions and governance controls. This openness is strategically important. Businesses are unlikely to standardize all their AI activity on a single vendor's assistant. Making business intelligence available across agents, applications, and workflows gives Zoho a potential role in a broader AI ecosystem, rather than limiting Analytics to customers who work exclusively within Zoho's applications. Governance matters as much as intelligence Zoho is pairing these agent capabilities with controls for managing their use. A unified data catalog provides visibility into data, metrics, models, and analytics assets, including lineage and impact analysis. AI observability lets administrators see which agents ran, who used them, what data they accessed, and how they responded. Usage and cost tracking, sandbox environments, version management, and rollback capabilities provide additional oversight. These aren't secondary features. As agents gain the ability to access business information and initiate workflows, organizations need to understand what those agents are doing and establish boundaries around their actions. Governance will be a significant factor in determining whether enterprises are comfortable moving beyond AI experimentation. Zoho also says pricing for Analytics remains unchanged despite the extensive updates, with Zoho LLM credits now included in each plan. The Basic plan starts at $24 per month, billed annually, for two users, 500,000 rows, and 10,000 Zoho LLM credits. The next step in Zoho's AI strategy The announcement includes more than 50 additional capabilities, spanning visualizations, pixel-perfect reporting, scenario analysis, forecasting, and data science tools. But the more significant development is the direction of the platform. Zoho plans to expand its business context capabilities, introduce decision intelligence based on the outcomes of agent-triggered actions, and build toward a broader unified data platform encompassing data integration, preparation, analytics, data science, and agent building. The challenge will be execution. Semantic models and business ontologies require organizations to invest time in defining their data and processes. AI agents also need to demonstrate that they can deliver reliable outcomes, not just compelling demonstrations. And while unchanged pricing is attractive, businesses will still need to evaluate the cost of AI usage, integration, and ongoing management. Zoho's approach is notable because it treats business context and governance as foundational components of agentic AI, rather than adding agents on top of existing analytics tools. If the company can make that intelligence accessible across applications and workflows while maintaining accuracy and control, Zoho Analytics could become more than a BI platform. It could serve as a common intelligence layer for how businesses use AI to make decisions and get work done.

Zoom is making a bigger play for enterprise AI, with a strategy focused on turning conversations into context, and context into completed work. Its new Unified Context Layer sits at the center of that vision. Zoom’s message at Zoomtopia 2026 was clear: the company wants to be much more than a place where people meet, chat, and make phone calls. It wants to connect conversations across an organization with the context, AI agents, and workflows needed to get work done. The theme was “conversation to completion.” Conversations generate valuable information, but decisions and commitments often get lost across meetings, chats, customer calls, and business applications. Zoom believes it can connect those dots and use AI to help organizations act on what they already know. It’s an ambitious vision, but one that addresses a real problem. Enterprises have invested heavily in collaboration tools and AI assistants. The next challenge isn't simply getting AI to generate a good answer; it's giving AI the right information and the ability to do something useful with it. The Unified Context Layer Is the Big Story Some of the most valuable business information never makes it into a formal document. A customer raises a concern during a sales call, a team makes a decision in a meeting, or a support conversation reveals a recurring product issue. Those details can remain buried in transcripts, chat threads, and employees’ memories. Zoom’s new Unified Context Layer is designed to bring this information together. It combines general knowledge, documented information from files, and connected applications such as Salesforce, ServiceNow, Workday, and Jira, and dynamic context generated through ongoing conversations. Zoom connects these inputs into an evolving picture of people, topics, decisions, and relationships. The goal is to let people and AI agents work from synthesized, current context rather than having to search through raw transcripts and disconnected systems every time they need an answer. This goes beyond simply connecting a language model to a company’s documents. By incorporating information generated through live interactions and linking it to business data, Zoom aims to give AI a more complete understanding of what is happening across an organization. If it works as intended, that context could help agents do more than retrieve information: they could recommend or initiate the next step. But execution will depend on how accurately Zoom captures information, how well it connects systems, and whether the resulting context is reliable enough to support business decisions. Capturing Context Wherever Work Happens One of the most potentially impactful announcements was around My Notes. Zoom is extending My Notes beyond traditional online meetings to capture conversations across phone calls, in-person discussions, and third-party meeting platforms. Planned enhancements include a dedicated app for offline meetings and mobile calls, hardware partnerships for capturing in-person conversations, and Follow the Meeting, which generates a personal transcript and summary even when someone misses part of a meeting. Users will also be able to capture screenshots and associate them with specific moments in a transcript, preserving visual details that text alone might miss. These capabilities address a familiar workplace problem: employees often need to be in the right meeting at the right time to stay informed. Better capture makes it easier to catch up and follow through without relying on someone else to share notes or a recording. Zoom is also making its conversational intelligence available beyond its own interface. New Search and Ask APIs will let AI agents retrieve relevant information or generate answers grounded in Zoom data. Model Context Protocol (MCP) servers provide access to capabilities including meeting intelligence, scheduling, My Notes, and agentic search. Integrations with Claude, ChatGPT, Codex, and Microsoft 365 Copilot are part of the strategy, with Gemini support planned. This is a smart move. Zoom doesn't need every employee to do all their AI work inside Zoom Workplace. Making its intelligence available in tools people already use could extend the value of its platform. The trade-off is that Zoom will need to demonstrate why its context and services remain valuable when employees increasingly interact with AI through other vendors’ interfaces. Customer Experience: Moving Beyond Insights to Action The conversation-to-completion strategy is particularly tangible in Zoom’s CX portfolio. New customer directory and profile capabilities are designed to create an evolving view of customer interactions across virtual agents, live agents, and Zoom Phone. SourceHub connects agents to third-party data, starting with Salesforce Service Cloud, allowing them to view and update contacts, cases, and opportunities without constantly switching between systems. Zoom CX Insights is also moving beyond traditional contact center reporting. It analyzes voice, chat, and email interactions alongside operational data to help businesses understand why customers are contacting them, what drives longer calls, and where agents may need support. New capabilities include recommended actions, scheduled reports, and executive briefs. Customer Workflow Orchestrator takes the idea further by connecting the contact center to CRM, IT service management, HR, and other operational systems. AI-powered reasoning can determine the next step in a workflow and resume it when a customer response or approval arrives, even hours or days later. That distinction matters. Creating a support ticket isn't the same as resolving a customer’s problem. Orchestrating work across systems offers a path toward closing that gap. The potential value is less manual work, faster resolutions, and fewer handoffs. The test will be how consistently these tools deliver results in complex, real-world workflows. Zoom is also extending Virtual Agent to physical kiosks, where customers can ask questions, complete routine tasks, or get help in environments such as retail and healthcare. If necessary, the interaction can be handed off to a live agent through Zoom Phone or Zoom Contact Center. Pricing in the Agentic AI age has become challenging for all vendors trying to figure out the optimal pricing model (consumption and usage, outcome-based, etc.). Zoom announced a new spend-based pricing model, with one unified spend pool across the ZCX portfolio. Zoom notes that the one annual commit covers the entire ZCX portfolio, and the commitment draws down across any ZCX product. This makes it easier for customers to use what they need, when they need it, without worrying about purchasing the right number of licenses for each product. I spoke with Chris Morrissey, General Manager of Zoom CX, about the announcements, the role of CX in Zoom’s broader portfolio, and how the Unified Context Layer can make customer interactions more personalized. I also spoke with Ram Rajagopalan, Head of Product – AI for Zoom CX, about the new kiosk virtual agent, as well as AI Architect, which uses AI agents to help build and test contact center agents. AI Architect is used to generate production-ready voice and digital AI agents from a simple prompt. I was particularly interested in how Zoom helps users create virtual agents. In this video, Ram demonstrated how AI Architect can simplify the process of building virtual agents. For businesses, the potential value is less manual work, faster resolutions, and fewer handoffs between systems and employees. From Productivity Features to Business Execution The same strategy runs through Zoom’s workplace and revenue announcements. My Notes workflows will let users send meeting summaries and action items to applications such as Asana and Slack using templates or natural-language instructions. ZoomMate team agents will coordinate specialized agents working on different parts of a project and combine their work into a single deliverable. For revenue teams, Agentic Workflow Builder will provide templates and custom agents to help recover stalled deals, improve forecast accuracy, and reduce CRM administration. Signal-based orchestration is designed to trigger workflows when buying signals appear, helping sales teams respond faster. Zoom Events is also getting AI capabilities. Content Studio will turn event recordings into clips, posts, and images, while an event setup agent will build configurations from prompts, agendas, or spreadsheets. The common thread is reducing the work between knowing what needs to be done and actually doing it. For enterprises, the bigger opportunity isn't just saving a few minutes on individual tasks; it's improving how work moves across teams and systems. Trust Will Be Critical to Adoption As AI agents gain access to more information and the ability to take action, security and governance become essential. Zoom is expanding capabilities, including deepfake risk detection, identity verification integrations, sensitivity labels, AI guardrails, and centralized AI management. Administrators will have greater visibility into active agents, the information they access, and their activities, with the ability to enforce policies and shut down agents operating outside defined boundaries. Zoom Compliance Manager is also being extended to My Notes and Zoom Canvas to help regulated organizations manage retention, monitoring, and audit requirements. These are more than compliance features. If AI agents can access confidential information, update business records, and trigger workflows, organizations need to know what those agents can see and do. The challenge will be maintaining consistent controls across Zoom products, connected applications, and external AI platforms—and establishing accountability when automated actions go wrong. I spoke with Alex Shockley, President and COO of Journey.ai, about its partnership with Zoom and capabilities for secure transactions, user authentication, and handling regulated data. The Bottom Line Zoomtopia 2026 signals a broader ambition for Zoom: building on its strength in communications to become a platform (or even operating system) that connects conversations, enterprise knowledge, and business execution. The Unified Context Layer is the centerpiece. Better meeting capture, cross-platform notes, customer profiles, AI agents, and automated workflows become more valuable when they share a common understanding of what is happening across the business. Zoom has two advantages. It sits across a wide range of conversation surfaces -meetings, phone, team chat, contact center, events, and revenue intelligence - and it is making its context available to external AI tools through MCP servers and Search and Ask APIs. Zoom is also leaning into open source with Onyx, a platform for interacting with different large language models and searching more than 50 internal data sources while preserving enterprise permissions. There is still plenty to prove. Integration quality, the accuracy of the context layer, measurable ROI, and customer confidence in AI governance will determine how much of this vision translates into business value. Many companies have figured out how to capture conversations. What happens next is what determines whether AI delivers value. Zoom wants to help businesses act on those conversations, carry work across systems, and reach meaningful outcomes. That makes “conversation to completion” more than a product tagline; it's Zoom’s attempt to define its role in the next phase of enterprise AI.

Latest Podcasts BC Strategies Expert analysis, insights, and opinions Podcasts

B usiness C ommunications S trategies Expert analysis, insights, and opinions Search BC Strategies Welcome to Business Communications Strategies (BCS), your go-to source for expert insights and guidance for enterprise success in Communications and Collaboration. Popular Tags Artificial Intelligence (24) 24 posts CCaaS (11) 11 posts ContactCenter (7) 7 posts UCaaS (6) 6 posts AI (5) 5 posts Zoom (4) 4 posts Follow Us Featured Article Quick Picks Latest Events Upcoming Events AI Videos Featured Expert New Expert Latest Research Latest Podcasts Latest Events Upcoming Events AI Videos Featured Expert New Expert Latest Research Latest Podcasts Latest Events Upcoming Events AI Videos Featured Expert New Expert Latest Research Latest Podcasts Latest Events Upcoming Events AI Videos Featured Expert New Expert Latest Research Latest Podcasts Latest Events Upcoming Events AI Videos Featured Expert New Expert Latest Research Latest Podcasts Latest Podcasts Latest Posts Unified Communications & Collaboration Customer Experience Artificial Intelligence Infrastructure The AI Chefs With Kevin Kieller and David Maldow AI Show With Rob Scott and Kevin Kieller

About BC Strategies Expert analysis, insights, and opinions Who We Are We are a collection of experienced, independent analysts, consultants, and thought leaders focused on unified communications, customer experience, artificial intelligence and other technologies associated with effective business communications and collaboration. We provide multi-perspective insights for vendors, enterprises and industry professionals. We offer advisory, research, custom content creation, and strategic services.