Few technologies have become mainstream as quickly as AI, especially in the area of workplace productivity and collaboration. A key reason is that the leading unified communications vendor – Microsoft -- also happens to be a leading AI player, especially for communications technologies.
As such, other UC providers are incorporating AI just to keep pace but not solely because of what Microsoft is doing with Teams. Vendors are racing to add AI features because customers are demanding it. As a result, IT leaders must now consider the AI capabilities offered by every UC vendor and not just those AI features provided by the suppliers they currently use.
This is especially true for UC systems in place for some time, as AI continues to evolve rapidly. If your incumbent isn't keeping up, you may be missing out on some valuable capabilities. To better assess what's going on, here are two best practices around AI communications features to consider -- one for internal needs and one for evaluating vendor offerings.
Identify pain points around workforce needs
AI represents a broad family of technologies, and it can be applied to an infinite range of scenarios. Focus on specific use cases that could benefit from AI-based capabilities rather than view AI as a general-purpose technology that end users apply as they see fit. AI does not provide business value simply because it's AI. Instead, AI delivers value because it enables new outcomes for workers or drives better outcomes for existing applications.
Yet, many workers still do not understand AI well enough to articulate how it can help. So, rather than asking employees how they think AI can be of value, IT leaders should focus instead on pain points in workflows or identify factors that detract from having a good employee experience.
UC touches on both in a major way. To that end, associated applications make for prime AI use cases. Start by considering AI's inherent strengths, such as being able to automate routine and repetitive tasks or processes. Another is AI's ability to process large volumes of data in real time with a high level of accuracy.
At face value, these are high-level characteristics, but when applied to specific tasks or outputs, they translate into business value. For everyday workflows, a good example would be Copilot-style virtual assistants that can manage tasks like organizing meetings with team members, prioritizing which emails to respond to and determining which files to read or tasks to perform.
For data processing capabilities, there is an ever-expanding range of applications, especially around communications. Most prominent is speech to text, where real-time translation and transcription make for better meeting experiences, offering automated summaries and specific action items for each participant.
With the advent of generative AI, automation can be further extended to writing email responses, as well as creating longer-form outputs, like blog posts. The possibilities are endless, but by focusing on specific applications that improve productivity and employee experience, AI can add a lot of new value for UC.
These are all vectors where UC has value, and this is how you should assess vendors' AI capabilities.
Evaluate UC vendors for their AI communications features
Identifying AI-driven use cases for UC is an ongoing process, and this is also a factor when evaluating UC offerings. Every UC vendor has an AI story now, but not all vendors have native AI capabilities. All of them are building out AI partner ecosystems, and many are making strategic acquisitions to strengthen their homegrown capabilities. These factors make it difficult for IT leaders to properly compare and assess vendor offerings, especially with AI advancing so quickly.
Comparing vendors' AI capabilities is futile; suppliers are adding new AI features every day. A better approach is to consider how each vendor frames UC applications through the lens of AI.
The more specifically each application is defined in terms of collaboration or employee experience, the more impactful the AI add-ons will be. Examine each offering on the basis of the problems it focuses on. As with AI, UC is a versatile concept. The value comes from how well specific applications align with your needs.
For example, a UC vendor may tout real-time translation support for 36 languages, but if you only need two or three, that's not a value driver. AI comes in many different flavors, but start with the basics first. For collaboration, a prime example of how AI might deliver value is by making meetings more effective or helping a distributed, hybrid workforce collaborate more effectively.
For employee experience, consider how AI might help keep workers engaged as they face always-on workloads. Other benefits might include helping employees manage and use ever-growing volumes of information. AI can also help support wellness and offers ways to keep workers feel connected. Don't forget business needs. How can AI help your organization compete successfully with other companies in your vertical or sector?
These are all vectors where UC has value, and this is how you should assess vendors' AI capabilities. The first step is to determine how well a vendor's value proposition for AI communications features aligns with the pain points and challenges you're trying to address with UC. Consider AI on the basis of what the vendor claims will be specific outcomes, rather than the fine points of its product's features. For longer-term thinking, determine how well the vendor's AI vision and roadmap align with how you think about them.
The second step is to identify proof points. AI doesn't have much of a track record yet, but examine the results vendors are getting with customers in similar situations or verticals as yours. All vendors publish case studies and success stories, but there may be others -- not public -- that reflect an even closer fit for your situation.
Jon Arnold is principal of J Arnold & Associates, an independent analyst providing thought leadership and go-to-market counsel with a focus on the business-level effect of communications technology on digital transformation.
