The Impact of AI on Unified Communications

Artificial intelligence is already having an impact on our professional and personal lives. It has use cases in arguably every major industry today, including unified communications. Further influenced by factors such as overall technological evolution, digital transformation, and a pandemic, artificial intelligence is increasingly being integrated into unified communications applications.

AI and UC in Partnership

Pandemic

The reaction to the coronavirus pandemic demanded that we change the way we approach work. The inability to be physically around other people, skyrocketed and expanded work-from-home strategies. With teams distributed, the need for efficient, reliable, and constant communication had never been greater.

Unified communications tools alone were not enough to cater to such a shift. For instance, tasks that require physical human effort could be automated through the use of artificial intelligence tools. Another example is the interaction of customers with conversational AI to complement customer care teams working from home.

Increased cloud dependence

The volume and speed of the creation of new data partly due to the spike in remote work is a challenge. Working from home strategies are increasingly evolving into hybrid work strategies, where employees are provided options to interchange between in-office or remote work per work-week. This presents a challenge of determining the optimal placement of workloads in a hybrid cloud architecture. It also introduces greater complexity of the mobility of data between the cloud, on-premises infrastructure, and the edge. Artificial intelligence contributes to evolving, easing, and optimizing these processes to support the delivery of unified communications applications to enterprises.

Digital transformation

The impact of digital transformation on unified communications is made more feasible when paired with artificial intelligence. Unified communications as a service (UCaaS) platforms are growing considerably, especially in the education industry. The growth of education technology sees more and more integration of digital learning tools into the education environment.

Educational institutions are conducting more activities through UCaaS software. Artificial intelligence improves the quality of UCaaS through personalizing learning for students, analyzing performance, automation of tasks such as online admission processes, and using face and voice recognition mechanisms to prevent identity theft in exams.

Also read: Unified Communications Security Considerations and Solutions

Artificial Intelligence in Unified Communications

Currently, the pairing of artificial intelligence and unified communications provides value in a number of ways.

Improving unified communications efficiency

Consider a context where enterprises need to sift through texts, emails, memos, and other forms of previous communication and conversations to accurately come up with responses to queries and messages. This is tedious work. However, enterprises can leverage artificial intelligence to analyze historical data and suggest, correct context-aware responses to messages based on the data.

Intelligent networks

Artificial intelligence enables networks to be more intelligent, thus improving real-time communications. Networks can prioritize real-time communications traffic without the involvement of network administrators. These intelligent networks have end-to-end visibility of data flow. As a result, they can identify problem areas and areas of congestion, then re-route high priority traffic to maintain a high quality of service.

UC performance insights

AI offers the capability to analyze the performance of unified communication systems. This can be done through monitoring and maintenance of a unified communication system to provide actionable insights. For instance, based on data, artificial intelligence can carry out predictive analysis of the system and suggest troubleshooting options in the event of issues and poor system performance.

Improved meeting productivity

Through the use of data from previous meetings, artificial intelligence can analyze data to understand how much time was spent on specific topics. An algorithm can then use the data to optimize future meetings. It could also use such data to suggest topics based on the individuals set to attend a future meeting.

Also read: The Future of Network Management with AIOps

Challenges of Using AI with UC

• Accuracy. Artificial intelligence is not perfect. Predictive machine learning models give wrong results from time to time. For example, suggesting incorrect topics of discussion for future meetings could cause inefficiency during such meetings. Consequently, their results have to be approved or rejected by a human overseer.
• Bias. Artificial intelligence and machine learning algorithms are susceptible to biases their human creators possess. 
• Exposure to automation. The conversation on the degree of automation of certain types of jobs persists as employees worry that they might be replaced. For instance, constant improvement of conversational AI in unified communications may be viewed as a threat to customer service professionals as more and more tasks become automated.
• Security. The combination of unified communications and artificial intelligence provides a greater surface of attack. Unified communications solutions combine functions like video, text, and voice. Each function has its distinct security needs. Furthermore, artificial intelligence requires vast data to learn from. This adds to the responsibility of securing sensitive data.

The Future of AI and UC

The use of artificial intelligence in unified communications is still in its infancy. Nonetheless, there is great expectation for the evolution of this pairing.

• More intelligent bots. AI-driven bots show lots of promise for the future. For instance, in addition to helping to identify who is speaking at a given time in a virtual meeting, they can provide information on meeting participants from online sources such as social media. They may also deliver supporting information and resources after intelligently identifying the topic of conversation.
• More personalized customer relationships. Organizations are constantly seeking ways to improve how they interact with consumers. A combination of unified communications and artificial intelligence goes beyond internal communications to customer-facing communications. Smarter chatbots may be used to improve and automate customer service. In addition to chatbots, artificial intelligence is capable of improving social listening tools, personalized web visits for customers, and cross-selling capabilities of the unified communication solution.  
• Improved speech-to-text. There is an opportunity for artificial intelligence to supercharge speech-to-text applications. Integration of artificial intelligence and unified communications may serve functions like convert voicemail messages into accurate text, accurate verbal dictation of emails, and automated minute-taking during meetings.
• Innovative applications of predictive capabilities. With improved algorithms, the predictive capabilities of artificial intelligence will be implemented in new and creative ways to boost operational efficiency. For instance, predicting operational delays, issues, downtime, suggesting accurate and feasible solutions, and automatically liaising with users to carry out the best solution.

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