Genesys, the global industry leader in experience orchestration powered by artificial intelligence, is launching a revolutionary advancement in the customer experience technology space – the Genesys Cloud ‘Agentic Virtual Agent,’ enabled by large action models. The new feature is enabling the next step in virtual agent technology, far beyond current chatbots, allowing for the performance of autonomous actions.
Unlike other most popular artificial intelligence chat-based application tools that are fed with LLMs and can efficiently handle dialogues as a part of the conversation, however, fail to execute the tasks in a sequence to satisfy customer needs, the agentic virtual agent technology offered by Genesys, as discussed above, not only attempts to understand customer needs better but also execute tasks to achieve customer resolution. Hence, it is a strategic technology shift from reactive self-service to autonomous engagement, which attempts to achieve customer experience by lowering customer effort, resolution volume, and operational efficiency.
The solution embeds governance, explainability, and policy alignment directly into AI workflows, giving CX leaders the controls necessary for enterprise-grade deployments. Early explorations of this capability are already underway with major organizations such as M&T Bank, Banco Pichincha, a global Fortune 500 healthcare company, and a Fortune 50 North American retailer ahead of the virtual agent’s general availability in early Q1 of Genesys’ fiscal 2027.
Also Read: Yellow.ai Launches Nexus – A Game-Changer for B2B Marketing and Advertising
What Makes Agentic Virtual Agents Different?
Traditional virtual agents built on LLMs are effective at generating conversational responses, but they struggle to fulfill tasks that require multi-system orchestration – such as updating orders, initiating service requests, or navigating internal customer service platforms without agent supervision. Genesys addresses this gap through:
- Large Action Models (LAMs): Specialized AI models emphasizing planning and execution of actions to take next, not limited to responding in natural language itself.
- Enterprise Grade Orchestration: Integration with various enterprise systems such as CRM, billing, and service operations to take the workflows through to completion.
- Governance and Compliance: Audit trails, explainability, and policy enforcement enable responsible and transparent automation at scale.
It is this combination which allows what Genesys terms “true autonomous CX”-where AI systems can not only converse with customers but can act upon them “without any human intervention whatsoever.”
Implications for B2B Marketing and Advertising
While Genesys’ announcement centers on customer experience, its effects ripple outward — particularly in the B2B marketing and advertising industry. Here’s how:
From Static Self-Service to Active Engagement
In B2B contexts, complex buying cycles often involve multiple touchpoints, including inquiries about pricing, product features, contract statuses, and support tickets. Traditional automated systems tend to generate information but rarely resolve issues autonomously.
With agentic virtual agents, B2B marketers can bridge the gap between engagement and execution. For example:
- A prospect interacting via a campaign landing page could receive automated responses, plus scheduling actions (like booking a demo) without manual staff involvement.
- B2B buyers can complete tasks such as requesting customized quotes or order tracking through AI that not only understands intent but completes multi-step operational tasks.
This transition toward action-oriented automation aligns marketing with revenue-generating activities and decreases friction in long, enterprise sales cycles.
Enhancing Customer Data Integration and Personalization
Agentic AI powered by LAMs doesn’t simply interpret language; it aggregates customer context and operational data in real time — weaving together CRM histories, service records, purchase data, and prior interactions.
For B2B marketers, this means:
- Deeper customer understanding: Cross-channel and historical data can inform personalized engagement strategies.
- Smarter segmentation: AI-driven behaviors can be used to refine audience segments based on actual operational intent rather than inferred intent alone.
- Higher conversion rates: Personalization that extends beyond messaging into automation of customer actions can boost campaign effectiveness.
Scaling Operational Efficiency Across Touchpoints
B2B organizations often struggle with operational bottlenecks when demand increases or when complex client requests occur simultaneously.
Genesys’ agentic virtual agent provides a scalable solution, enabling enterprises to automate routine and complex tasks at scale, such as:
- Customer onboarding workflows
- Support ticket resolution
- Service escalations
- Contract renewals or adjustments
This not only reduces customer support workloads but also improves marketing ROI — as prospects receive quicker, more consistent interactions that are aligned with brand experience.
Aligning Cross-Functional Teams Around Shared Metrics
Agentic AI naturally fosters collaboration between departments that traditionally operate in silos — including marketing, sales, customer support, and IT – because it requires shared data structures, unified goals, and coordinated execution.
For example, marketing campaigns can now tie directly into automated operational workflows:
- A lead generated through a digital campaign triggers an agentic workflow for qualification and scheduling.
- A customer segment targeted with renewal messaging triggers automated follow-up actions across CRM and billing systems.
By aligning cross-functional processes around agentic automation, enterprises can measure performance with business outcomes rather than isolated marketing metrics.
Wider Business Impact
Beyond marketing and advertising, agentic virtual agents have implications for broader business operations:
- Cost Efficiency: Automation of simple tasks can play a vital role in cost efficiency.
- Customer Satisfaction: Faster and more reliable self-service will increase customer satisfaction and reduce customer defection — an imperative in B2B relationships with high customer retention rates.
- Innovation Enablement: As enterprise autonomous systems will include governance and control, this will enable businesses to innovate with confidence, knowing that undertaking such efforts with AI-based systems will not compromise control and compliance.
Conclusion
The introduction of Genesys’s agentic virtual agent based on large action models is an important milestone, not merely for customer experience, as is commonly understood, but also for the broader scope of how different businesses, including B2B marketers and advertisers, manage their operations and workflows. On one hand, the shift from conversational agents to autonomous agents promises much in the realm of personalization and operational workflow not merely as pertains to marketing or advertising.
In an age where experience is a differentiator, automation is a requirement, and agents of AI represent the future of digital engagement with the promise of making customer interactions yield business results with the speed, precision, and governance the digital enterprise requires.
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