Nexthink: Building the Future of Digital Employee Experience

2026-05-01 · Source: AI Magazine · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Software Development & Engineering, Robotics & Autonomous Systems · Depth: Intermediate, medium

Summary

Nexthink, a leader in digital employee experience (DEX), is undergoing a significant transformation to become an "AI-native" company, as detailed by Moe Haidar, Head of Agentic AI and Engineering. The company's platform monitors employee interaction with technology to proactively resolve issues, serving 25 million users across large enterprises. This AI-native strategy involves building products with AI as a foundational element, rather than an add-on, and integrating AI to enhance internal workflows and efficiency across all teams. Nexthink's approach includes both enhancing existing products with AI and developing new AI-native offerings, such as autonomous agents. This shift from deterministic to probabilistic software models necessitates new disciplines like extensive evaluations, benchmarks, and iterative deployment, alongside upskilling staff to manage probabilistic systems. The company prioritizes responsible AI through a cross-functional committee, continuous monitoring, and robust security measures.

Key takeaway

For Directors of AI/ML leading organizational transformation, prioritize defining what "AI-native" means for your specific product strategy and internal culture. You should establish clear value-driven priorities for AI adoption, implement robust MLOps and responsible AI governance, and invest in upskilling your teams to manage the probabilistic nature of AI systems, ensuring stability and trust in production environments.

Key insights

Becoming "AI-native" requires foundational AI integration in products and pervasive AI-driven efficiency across all internal operations.

Principles

• Reinvent continuously to adopt new technologies.
• Focus AI adoption on clear value addition.
• Treat AI workloads as mission-critical systems.

Method

Integrate AI by enhancing existing products and building new AI-native solutions, supported by extensive evaluation pipelines, MLOps best practices, and gradual rollouts.

In practice

• Establish a cross-functional AI committee for governance.
• Implement AI observability for production monitoring.
• Upskill teams in probabilistic system design.

Topics

• Digital Employee Experience
• AI-native Transformation
• Observability Platform
• Agentic AI
• Responsible AI

Best for: AI Product Manager, Director of AI/ML, AI Architect, MLOps Engineer

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Editorial summary, takeaway, and curation by AIssential. Original article published by AI Magazine.