YXT.com Debuts Intelligent Productivity Portfolio and White Paper, Raising the Bar for Enterprise AI

YXT.com Product Launch: A Product Leader's Brief on Intelligent Productivity

YXT.com Group Holding Limited hosted its Intelligent Productivity Product Launch in Beijing on September 17, 2025. For product teams, the signal is clear: enterprise AI is moving from pilots to production with a full-stack approach-technology, domain know-how, and organizational change baked in.

The event introduced a portfolio of AI-driven solutions across HR, role capability, sales enablement, and employee learning. It also featured an industry white paper and an expert dialogue that framed both the opportunity and the execution path for large-scale adoption.

What's New for Enterprise Product Builders

• Four flagship products mapped to core business scenarios: HR transformation, capability development, sales enablement, and continuous learning.
• A complete AI application lifecycle: from data ingestion and model orchestration to deployment, governance, and measurement.
• Security-first posture: emphasis on enterprise-grade data protection and compliance, paired with proof points from large customers.

Strategic Signals You Can Use

Leadership framed "intelligent productivity" as AI that behaves like a virtual employee-grounded in business context, accountable to outcomes, and collaborative with human teams. The goal isn't AI for AI's sake; it's measurable impact across workflows.

Two big bets stood out: building AI-native organizations and expanding via partnerships, investments, and acquisitions in HR Tech and adjacent AI capabilities. Translation for product: expect faster platform consolidation and higher expectations for integration and governance.

Industry Definition and Expert Dialogue

Frost & Sullivan released the Enterprise Intelligent Productivity White Paper, offering a structured definition of the category and market outlook. For product leaders, this provides a reference model for segmentation, go-to-market, and adoption benchmarks.

A panel with experts and executives from institutions including Tsinghua University and Merck Serono discussed practical adoption patterns-data foundations, domain-specific modeling, and operating model changes-validating the need for cross-functional execution at scale.

Explore Frost & Sullivan's research

Build the AI "Virtual Employee" the Right Way

• Start with anchored workflows: onboarding, sales play execution, capability assessments, and knowledge retrieval tied to performance metrics.
• Define the role: what the AI does, where it hands off, how it explains actions, and how it logs decisions.
• Ground in enterprise data: scoped retrieval, PII controls, content provenance, and audit trails.
• Choose the right stack: model options, retrieval augmentation, policy layers, observability, and rollout tooling.
• Human-in-the-loop by design: review queues, feedback capture, and approval thresholds.
• Governance and security: access policies, red-teaming, incident response, and compliance checkpoints.

Metrics That Matter

• Time-to-competency for new hires and role transitions
• Sales cycle time, win rates, and content usage-to-revenue linkage
• L&D completion-to-performance correlation (not just consumption)
• Copilot satisfaction (CSAT/NPS) and deflection rates
• Model quality: accuracy, refusal validity, regression rates, and bias checks
• Security: data access exceptions, policy violations, and audit closure time

30/60/90-Day Action Plan for Product Teams

• 30 days: Select two workflows with clear owners and measurable outcomes. Inventory data sources and compliance constraints. Draft the virtual employee spec.
• 60 days: Ship a constrained pilot with human review. Instrument detailed telemetry. Run risk assessments and guardrail tests.
• 90 days: Expand to a second department. Standardize prompts, patterns, and policies. Publish a governance and model update schedule.

Buy, Build, or Blend

• Buy when speed, compliance, and existing integrations dominate; verify security claims and customer references.
• Build when proprietary workflows and domain logic are your moat; invest in retrieval, policy layers, and evaluation.
• Blend by composing vendor modules with in-house orchestration and governance to keep control where it counts.

Why This Launch Matters

YXT.com's portfolio and strategy reflect where enterprise AI is heading: outcome-first copilots, lifecycle tooling, and tight security. For product leaders, the competitive edge will come from owning the operating model-how teams design, deploy, and improve these systems quarter after quarter.

Level Up Your Team

If your roadmap includes AI copilots for HR, sales, or learning, align product and enablement early. Curated training can shorten the ramp for product, design, data, and ops.

Browse role-specific AI training

Company leaders emphasized collaboration between people and AI, with plans to expand partnerships and global reach. The immediate takeaway: build AI that understands your business, prove value fast, and scale with governance.