SoundHound AI’s agentic revolution: contact centers cash in, but real AI value still eludes most

SoundHound AI's recognition as the overall leader in the 2026 ISG Buyers Guide for Conversational AI is firmly anchored in the exceptional ROI and employee satisfaction delivered by its agentic AI deployments in contact centers. By early 2026, 96% of organizations reported meeting or exceeding their ROI goals, with 72% noting improved employee satisfaction, underscoring the technology's dual impact on financial performance and workforce morale.

Agentic AI is revolutionizing contact center operations by enabling autonomous resolution of complex customer issues, with 28% of deployments capable of end-to-end handling without human intervention. This capability is transforming customer engagement strategies, as 90% of respondents anticipate that at least a quarter of interactions will be fully AI-resolved within five years, signaling a strategic shift toward AI-driven service models.

The adoption of agentic AI is also reshaping customer behavior, reversing longstanding trends of self-service avoidance. Half of the surveyed organizations observed increased active engagement with AI-powered platforms, while the technology's ability to execute multi-step workflows—such as processing complaints, returns, refunds, and coordinating AI-human collaboration—has elevated contact centers from mere deflection points to comprehensive resolution engines.

Deployment experiences for agentic AI have improved markedly, with 82% of organizations finding implementations either as expected or easier, reducing previous barriers related to integration friction and cost overruns. This smoother rollout process is facilitating broader enterprise adoption and enabling strategic transformation across contact center operations.

By early 2026, SoundHound AI's drive-thru voice AI deployments in quick-service restaurants have demonstrated tangible early ROI, with a major QSR customer reporting higher revenues at locations using the technology compared to those without it. This initial success underscores the potential for the vertical to become a significant contributor to SoundHound’s broader enterprise AI growth strategy. However, the company faces the critical challenge of scaling these deployments across multiple restaurant locations to fully capitalize on the opportunity.

Beyond automating order-taking, SoundHound’s Voice Insight tool is gaining momentum by equipping quick-service restaurant operators with detailed analyses of customer interactions and staff responses, fostering deeper customer relationships and enabling increased cross-selling activity. This analytical layer not only enhances operational benefits but also encourages broader adoption of adjacent AI tools, which could be pivotal in driving sustained growth and operational improvements within the QSR vertical.

Despite the widespread enthusiasm for AI-driven rapid product development, a significant disconnect remains between the hype and the reality of delivering sustained business value, especially within legacy products serving established customers. As highlighted in a 2026 analysis, optimizing mature products with paying users requires a fundamentally different approach than launching new offerings, cautioning against prioritizing speed and novelty over thoughtful product management focused on user workflows and meaningful outcomes.

Effective AI adoption hinges on deep organizational readiness that transcends mere technology access, demanding a culture of curiosity and courage where AI experimentation is a high-status activity supported by leadership and broad employee engagement. Companies like Meta illustrate this by providing open AI tool access to all employees, fostering a mindset that embraces iterative learning and adaptation, which is crucial given the rapid evolution of AI platforms and the need to integrate AI strategically into workflows that align with business priorities.

User-centric evaluation remains paramount as organizations navigate the balance between AI automation and human involvement, with nearly half of consumers preferring a hybrid model where AI handles routine tasks but humans address complex or sensitive issues. This nuanced consumer sentiment, underscored by research showing 35% frustration with unready AI support and significant brand loyalty risks among younger demographics, reinforces Sachin Jaiswal’s assertion that consumers reject poor service rather than AI itself, emphasizing the necessity of integrating AI thoughtfully to enhance rather than degrade customer experience.

The stark reality that only 12% of companies generate real business value from AI reveals a critical gap between investment and effective adoption, largely due to middle management bottlenecks and the absence of comprehensive AI governance programs. As Sanjeev Vohra of Genpact notes, the transition from AI as a personal productivity enhancer to AI embedded in workflows that drive measurable business outcomes is essential, with organizational willingness to embed AI into production and rigorously measure impact serving as the decisive factor distinguishing AI leaders from laggards.