As AI capabilities secure an increasingly central role in enterprise communications, early investors may be wondering what comes next. Until recently, AI tools alone provided a significant competitive advantage; however, as more platforms and businesses adopt them as standard, industry leaders are seeking the next value driver.
“Enterprise communications” is a broad function that spans a range of platforms and use cases, from internal collaboration tools to contact center management, and AI has made inroads into virtually all of them. Alone, these AI features run the risk of replicating the challenges they were designed to overcome, such as siloed information, limited insights, and redundant functionality. To unlock the maximum potential of enterprise AI, businesses must look toward a new approach: the AI ecosystem.
Building an AI communication ecosystem
Many enterprises are already investing in AI-enriched contact centers and unified communications platforms, such as:
- Microsoft Teams with Copilot
- Cisco Webex and AI Assistant
- Five9 and Genius AI
Some communications platforms are oriented toward internal collaboration and individual connectivity, while others prioritize enhanced contact center functionality. Enterprises that implement multiple options as point solutions are faced with an added challenge: which AI solution takes precedence?
Those familiar with the AI space already know that AI tools are only as good as their data foundations. Broadening those foundations involves building connections between disparate AI solutions and sharing data across platforms. Interoperable AI systems can incorporate a larger range of data, align toward the same business goals, and drive even greater efficiencies with a holistic view of business processes. But interoperability is no accident—establishing a unified AI ecosystem demands intentionality.
Unified AI strategy
While some companies are investing in the entire vertical process of AI development, adoption for most enterprises has been piecemeal. Prebuilt or customizable AI tools, scoped for a single platform, present a convenient opportunity for small and medium-sized businesses to step into AI implementation for the first time. Growing beyond this “starter” AI roadmap, however, will require a significantly more substantial investment in AI strategy and infrastructure.
A truly cross-platform AI communication strategy, one which unifies the contact center with internal collaboration tools, must meet several requirements:
- Intercommunication: Host systems and their AI features must be able to communicate with each other, send intentions and requests, and respond to prompts.
- Shared data: AI tools need access to an integrated data pool to produce comparable analyses.
- Cross-functional analytics: AIs must be able to incorporate data from other systems into their own analyses to gain genuinely expansive insights.
- Efficiency: The purpose of an AI ecosystem is to minimize redundancies and streamline operations. Duplicate agents or features create inconsistencies and inefficiencies.
- Scalability: Your strategy should allow you to incorporate additional AI elements as your AI investment grows.
Supporting unified AI with unified data
AI implementations are heavily reliant on a foundation of unified, high-quality business data to produce their best results. Building a unified data resource to support AI innovation is a strategic goal in its own right, requiring coordination across multiple technology functions. Data storage must be structured and housed in appropriate infrastructure, often in the cloud. Engineers integrate data streams and configure processes to transmit, transform, and load data. And technicians continually monitor the flow and usage of data, and structure governance policies to ensure its ongoing quality.
AI-driven efficiencies, in the contact center and beyond
AI tools already enhance productivity and the employee experience within their individual communications platforms. Across both contact center and internal collaboration tools, AI agents and systems summarize meetings, take notes, suggest next steps, transcribe conversations, and enhance call quality. In an interconnected ecosystem, these efficiencies compound.
For example, AI-enhanced call quality enables contact center AI agents to produce more precise real-time transcription, empowering human agents to communicate with customers more clearly, and eventually may even facilitate real-time translation. Sentiment analysis on voice calls paired with company best practices can produce a list of suggested actions for service representatives, which integrates directly into project management processes to populate department task lists and calendars.
When AI tools can transcend the boundaries of their native platforms and interconnect, their flexibility and power multiply. However, to build an ecosystem that is greater than the sum of its parts requires expert strategy surrounding both data and AI, something that most enterprises must look to external sources to find.
Optimize your AI communications ecosystem for growth with CBTS
CBTS consolidates knowledge and experience across unified communications, contact center platforms, data strategy, and AI into a single expert resource. A thriving AI ecosystem demands interoperability and flexibility, which is why CBTS takes a vendor-agnostic approach that prioritizes superior business outcomes. With a long history of tailored enterprise communications solutions and recognition from multiple leading industry brands, CBTS is the ideal partner to develop your future-ready communications stack.
CBTS collaborates with you to develop an AI roadmap tailored to your specific needs, budget, and strategic objectives. Engineers collaborate closely with your team to implement your AI solutions, and CBTS remains involved in support and maintenance at the level that is right for your organization—from service desk support to fully managed solutions. To begin envisioning a cohesive AI strategy, contact CBTS today.
