Generative AI assistants have arrived, but adoption, and value are TBD.
If there was a “term of the year” award for the communications, collaboration, and customer experience space, “generative AI” would win for 2023 in a landslide. This past year saw a slew of gen AI announcements from just about every vendor in the market. But, as we hit the peak of the hype curve, there are very real questions about gen AI heading into 2024, answers to which will determine if the hype translates into actual adoption and customer benefit.
WILL COMPANIES ADOPT IT?
Metrigy’s Customer Experience Optimization: 2023-24 – Consumer Perspective study earlier this year of ~500 people in the United States found widespread awareness of generative AI but significant concerns related to privacy, security, and trust. Adoption plans were limited, with just 19.7% saying they would use generative AI for content creation and meeting/chat summarization if available. 16.1% said they would not use it. Almost 41% of participants said that for them to trust gen AI, the technology would require human oversight of content creation as well as limitations on how the tools collect data. Nearly 32% say they will never trust it.
Specific concerns include accuracy of generative AI responses, security of corporate information that may be available to large language models, and privacy of information captured by generative AI tools such as meeting transcripts and interaction critiques.
WHAT’S THE ROI?
As companies get their hands on generative AI assistants they are beginning to focus on ROI, especially when evaluating vendors who charge for AI assistants. We’ve seen in our research over the years that ROI for investments in collaboration applications and features is often difficult to quantify. Some companies look at metrics such as average time spent on repeatable processes to see if they can identify reductions. Other areas may include overall revenue, reduction in costs or staff time, or metrics specific to customer interactions such as first call resolution and customer satisfaction scores.
As generative AI assistants go beyond meeting and chat summarization and transcription, identifying ROI should get easier. For example, employees can identify improvements in data analysis and speed of content creation. IT staff can measure improvements in mean-time-to-repair (MTTR) and administrative tasks from the use of generative AI tools for application and network management.
Even for those adopting free tools there will be some associated costs in terms of user and IT training, IT support, and administration, and to meet security, governance, and compliance requirements for generated content such as meeting transcripts or chat summaries.
DOES IT WORK?
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