Why Enterprises Struggle to Turn AI Investments Into Business Value
As enterprises increase investments in artificial intelligence, translating AI experimentation into measurable business outcomes remains a significant challenge. While organisations continue to deploy AI tools and run pilots, many struggle to integrate the technology into core business processes, modernise legacy infrastructure and establish clear accountability. The shift towards AI-native operations also raises questions about engineering productivity, workforce readiness and governance, particularly as enterprises explore autonomous AI agents.
In this interaction, Pankaj Vyas, MD & CEO, Siemens Technology and Services, discusses why AI initiatives struggle to move beyond experimentation, how organisations can redesign workflows around AI, and what it takes to build a workforce that combines human expertise with AI capabilities.
Beyond AI Experimentation
McKinsey finds that AI adoption is rising faster than enterprise-level financial returns. What is the most common organisational failure preventing pilots from scaling?
The most common reason AI pilots fail to scale is that organisations treat AI...
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