The enterprise landscape is abuzz with AI. However, unlike the initial adoption stage, enterprises are now moving to the implementation and consolidation period.
Indeed, a new industry Revelate Survey from AI company Domino Data Lab shows that while enterprises are advancing from AI experimentation to full-scale production, measurable returns on investment (ROI) remain limited for most organizations.
The survey states 88 percent of enterprises have improved their ability to deploy AI at scale, but nearly 60 percent expect less than 50 percent ROI from machine learning and generative AI initiatives.
Yet at the same time, communication solutions provider Vida released an SMB AI Voice Agent Adoption & Impact Survey revealing that 97 percent of adopters of AI agents are reporting increased revenue.
"The future of AI agents will be about more than efficiency, but a new opportunity to transform customer engagement and maintain a competitive edge,"
Akshay Srivastava, EVP and GM at RingCentral, told UC Today.
Thus, in this new business landscape that is now looking to receive ROI from AI, should businesses look to Voice AI as the obvious answer?
AI's Use in Calls
AI is rapidly transforming the calling capabilities of businesses.
Generative AI tools now automate post-call processing by summarizing conversations and updating CRM records, saving valuable time for human agents and standardizing documentation for future reference.
Equally, AI-driven quality assurance solutions analyze interactions to help drive back-office decisions on things like staffing numbers during peak hours or script changes.
However, recently, companies have been focusing less on AI assistance and more on agent-centric AI solutions that can take over some workload for agents.
The AI Voice Ecosphere
In February, RingCentral became one of the first major UCaaS providers to launch its AI Receptionist (AIR) solution.
Built directly into the RingCentral business phone system, AIR can absorb customer questions, answer them with the correct business-related information, and even transfer callers to the right place, much like traditional full-time receptionists do.
Targeted at SMBs and currently seeing an initial controlled release in the US, RingCentral has announced the solution has already achieved 1,000 customers.
"As businesses grapple with inflation, rising taxes, and reduced consumer spending, many are reassessing their strategies to ensure long-term viability," Srivastava said.
Despite the industry debating whether voice has a future, a recent survey from Transaction Network Services showed 64 percent of consumers still prefer to talk via voice call when engaging with certain industries.
Where AI voice is seemingly providing a clearer return compared to AI assistants is through the creation of a new 'agent' rather than the augmentation of the workflow of one.
"A security company that trialed RingCentral AI Receptionist now automates 50 percent of its calls, freeing staff for revenue-generating tasks," Srivastava explained.
"This reflects a growing trend where AI-powered solutions take over routine tasks."
AI Voice Solutions Catching On
Hot off the heels of RingCentral's AIR announcement, UCaaS GoTo released its own AI voice solution the GoTo Connect AI Receptionist.
A solution that can handle customer calls with voice responses, GoTo solidified the direction of travel the industry was taking when it comes to AI voice applications.
AI tools that assist receptionists or call agents typically enhance productivity and service quality but do not directly replace headcount, making their financial impact less immediately visible and often dependent on incremental improvements in efficiency or customer experience.
In contrast, an AI receptionist can directly replace the traditional front-desk role, leading to substantial cost savings and operational efficiencies.
By automating routine call handling, appointment scheduling, and basic inquiries, an AI receptionist can reduce or eliminate the need for a full-time human receptionist, whose annual salary often far exceeds the monthly cost of an AI solution.
