AI and cloud computing technology are merging to revolutionize enterprise communications. Generative AI (GenAI) is already bringing new levels of efficiency, functionality, and user-friendly design to digital workplace tools.
Natural language processing (NLP) prompts provide more human-centered controls based on conversational questions and commands for internal users and end customers. Chatbots have reached the next stage of intelligence, capable of understanding an unprecedented number of queries and prompts while responding in a more human way and even monitoring a customer’s mood. Preparing for AI-enabled solutions enables companies to make sense of their data more deeply, providing analytics that predict likely outcomes and assist stakeholders in making better-informed decisions.
However, incorporating AI into communications carries risk. Changing compliance rules, avoiding negative brand associations from consumers, and maintaining security and customer privacy are just a few of the challenges. Organizations must thoughtfully implement, monitor, and train AI models within their communications systems or risk adverse outcomes like inaccurate AI results or regulatory fines.
This post examines how to prepare for and optimize AI in enterprise communications while considering what the future might bring to this space.
Also read: Playbook: Implementing AI solutions to achieve operational excellence
The current state of enterprise communications
Understanding AI’s potential in communication means examining its real-world implementations. AI is increasingly being embedded into Unified-Communications-as-a-Service (UCaaS) platforms like Microsoft Teams and Webex Calling, as well as Contact-Center-as-a-Service (CCaaS) solutions such as Webex Contact Center, Five9 Contact Center, and CXsync Contact Center. This integration is transforming business operations in several ways.
AI-driven chatbots and virtual assistants within CCaaS platforms can take over routine customer inquiries. This automation allows human agents to focus on more complex issues, improving operational productivity while delivering faster, more precise responses that elevate customer satisfaction.
Additionally, a key benefit for remote and hybrid teams is AI-driven speech recognition tools. These enable real-time transcription of conversations, simplifying the process of reviewing and sharing important information.
AI also plays a critical role in predictive analytics by examining customer interactions to identify patterns and forecast future trends. These insights allow businesses to proactively resolve potential issues and optimize communication strategies, ultimately strengthening customer relationships and improving the overall experience.
While many organizations are already leveraging AI for internal communications and customer support, others may still be in the early stages or looking to elevate their AI strategies. So, how can AI novices and perfectionists alike prepare for AI communications? Whether you’re just starting out or aiming to maximize AI’s potential, there are key steps to take that ensure you’re ready for the future of AI-driven communication.
How to prepare your organization for AI communications
To prepare for, implement, or enhance AI within your organization’s communications systems, take the following steps into account:
1. Develop buy-in from the C-Suite. Every organization’s decision-makers should have first-hand experience and understanding of AI communication tools to model and drive adoption organization-wide.
2. Foster an AI-friendly culture. Understandably, many employees are dubious about AI and fear being replaced by it. IT leaders can help ease these fears by emphasizing the hybrid nature of AI tools and creating many opportunities to learn about AI. This will allow employees to voice their opinions and regularly interact with new technology. Forming committees and discovery panels can also be a way to generate interest and ease distrust.
3. Evaluate and prepare your communication infrastructure. AI relies on fast network speeds, low latency, and high availability. Is your infrastructure up to the task? Now is the time to take stock and seek expert opinions.
4. Invest in data management. AI depends on clean and de-siloed data to ensure accuracy and eliminate bias.
Learn more: Modern data management: Infrastructure solutions for AI and data-driven decision-making
5. Assess the risks. Implementing any AI model raises significant security, compliance, and accuracy concerns. Keeping customer data private and company intellectual property secure is also essential.
6. Identify key use cases. Determine where AI can make the most impact in your communications. Find the overlap between high-priority and low-effort cases and start there.
7. Emphasize training for both humans and AI. AI is far from autonomous, at least in its current incarnation. Employees must learn how to prepare for AI integration in their roles. Likewise, AI must be “taught” and corrected to achieve optimal outputs.
8. Find ways to measure ROI. Measuring returns on AI investment is notoriously difficult. Due to its embedded nature, AI is unlike regular capital expenditures. It is hard to draw a direct correlation between investments and outcomes. Regardless, it is essential to find metrics that point to the success or failure of AI implementations.
9. Manage compliance. AI regulations frequently change. Set up governance policies to best meet emerging rules and to ensure accurate and bias-free results.
10. Partner with AI experts. AI implementation, management, and monitoring are burdensome for internal teams alone. An experienced AI partner like CBTS can guide your organization through each phase of AI adoption and help you get the most out of your AI investment.
The future of communications
Perhaps the “final” step of successfully utilizing AI communications is to stay informed on the latest AI advancements. In the future, AI may offer further benefits by enhancing personalization and predictive analytics. Additionally, communications that integrate an NLP AI tool for requests may become “channel-less.” Partially today, but increasingly in the future, AI will create workflows that span applications and platforms to achieve singular results.
Also, AI will help users get more out of their existing tools. For example, Microsoft Excel has over 500 advanced features, but most users only use a handful of tools and formulas. AI could make advanced applications like Excel much more intuitive for everyday users.
Getting the most out of AI
Organizations should adopt a hybrid AI mindset. Preparing for AI means paying attention to how humans and computers work together. When working in an optimized environment, human workers and AI become greater than the sum of the whole. And CBTS can help you achieve that optimized environment.
Learn more about our AI Readiness Assessment and other AI services.
