Path to Scale – from enthusiasm to ROI in GenAI
Generative AI is entering a new era of maturity. Organizations are shifting their focus from experimentation to enterprise-grade deployments, aiming to unlock measurable business value and sustainable competitive advantage. The key question has become not whether to implement GenAI - but how to do so at scale, securely, and with clear ROI.
Leadership and Strategy
According to Deloitte’s State of GenAI in the Enterprise report, 67% of surveyed organizations are increasing their GenAI investments, citing clear business value from early use cases. But successful scaling requires more than just technology. It starts with strategic leadership decisions, clearly defined accountability structures, and targeted investments tied to measurable outcomes. That’s the only way to turn early wins into lasting competitive advantage.
Technology and Data
As GenAI use cases expand, organizations face increasingly complex technology decisions: from platform selection to integration and data governance. The foundation lies in data readiness: 75% of organizations have already increased investment in data lifecycle management. Without a coherent data architecture, GenAI's potential remains limited. In fact, 55% of organizations had to abandon GenAI use cases due to data quality issues. Investment in this area is no longer optional – it is essential for realizing GenAI’s value.
Trustworthy AI
Building trust in GenAI encompasses both regulatory compliance and responsible use practices. The goal is to ensure transparency and security while preserving operational agility. More than half of organizations are now implementing formal GenAI governance frameworks. Transparent risk management, covering tool approval, usage policies, and escalation path, enables faster adoption and greater user engagement.
Change Management
GenAI is reshaping how organizations operate, impacting internal processes, decision-making models, team roles, and customer and supplier relationships. Consequently, organizations are treating change management as a core pillar of GenAI scaling, embedding it into training programs, internal campaigns, and employee engagement strategies to lay the groundwork for broad adoption.
Operating Model
Effective GenAI implementation requires an operating model that balances two dynamics: the pace of internal adoption and the rapid evolution of the technology itself. Success demands both agility in seizing new opportunities and the ability to adapt and operationalize tools quickly. Continuously integrating the latest GenAI capabilities is challenging, but essential for sustaining a competitive edge.
