🔎 The missing link for (Gen)AI value realization

Organizations across industries are accelerating (Gen)AI investments, with 85% of executives planning to increase budgets. Use case excitement is high – especially in central functions like HR, Finance or Procurement. Yet the value captured remains limited.

📊 Only 12% of organizations have implemented holistic (Gen)AI workflows.

📉 62% of employees don’t use (Gen)AI in their day-to-day work.

💡 The conclusion: use cases are not the issue – the operating model is.

🚧 The real reason (Gen)AI fails to scale

Despite the hype, many companies face recurring challenges when moving from pilots to enterprise-wide (Gen)AI impact:

• 81% of CEOs cite a lack of sufficient data foundation
• 58% see data & technology safety concerns
• 98% report missing specialists and know-how
• 41% say that culture and change are the main barriers

Most operating models are simply not designed to enable AI at scale – lacking the structural, procedural, and human foundations required.

💡 Central functions hold the key – and HR leads the way

Central functions offer particularly strong value potential:

• Bottom-line (cost and efficiency): up to 40% in HR
• Top-line (growth and innovation): up to 5% by enabling skill transformation and performance

HR, in particular, is uniquely positioned as both a use case and an enabler of broader (Gen)AI success. Through automation, data, and personalisation, HR can:

• reduce manual admin
• elevate decision quality
• foster new role profiles and mindsets
• support culture, compliance, and skills across the organisation

🏗️ The three pillars of a (Gen)AI-enabled operating model

To build this foundation, organizations must evolve three interconnected elements:

1. Processes 

(Gen)AI enables streamlined, personalised processes across the entire HR lifecycle – from recruitment to development to exit. Bottom-line impact ranges from 5–40% depending on the area. Examples: 

• Automated onboarding and offboarding 
• AI-supported candidate screening and interviews 
• Personalised learning paths 
• Real-time performance reviews 
• Dynamic reward systems 

This evolution in processes is foundational for driving efficiency and effectiveness across HR operations, setting the stage for enhanced business outcomes. 

2. Organisational structure - an AI-enabled structure means:

• Fewer layers, broader spans of control
• Cross-functional teams enabled by (Gen)AI agents
• Flexible resource pools replacing siloed CoEs and HRBPs
• A central AI tech layer automating administrative services

This transformation frees up capacity and enhances collaboration between HR, tech, and business.

3. People and roles - (Gen)AI shifts HR from administration to strategy – and demands new role profiles:

• Lifecycle leads become business evolution partners
• HR business partners evolve into business managers
• CoEs transform into people experts
• HR service teams become digital platforms

This role evolution must be supported by structured upskilling – moving from generalists to AI-augmented specialists.

🔓 Five key prerequisites to overcome barriers standing in the way of scaling (Gen)AI

🧭 The way forward: From readiness to scale

To succeed, organizations must treat the operating model as a strategic transformation lever. Key steps include:

1. Assessing (Gen)AI readiness across data, structure, processes, and culture
2. Establishing short-term governance and pilots through dedicated task forces
3. Scaling transformation by aligning top-down ambition with bottom-up enablement

When executed well, the (Gen)AI-enabled operating model becomes more than an enabler of efficiency – it becomes a driver of growth, agility, and competitive advantage.

 📖 Full article by Dieter Kern , Pascal Fehst , Niklas Frings , Sina Schieffer , Celina Redder #GenAI #OperatingModel #HRTransformation #AIReadiness #DigitalLeadership #Strategyand