2 weeks ago

Why Indian Enterprises Struggle to Scale AI Beyond Pilots

Many companies try small AI experiments but struggle to use AI across their whole business.

Rishi Aurora says the main challenge is usually not the AI model itself.

Companies also need to redesign how their workers and systems operate.

Banks are using AI in areas such as fraud detection, cybersecurity, customer checks and anti-money-laundering work.

New AI agents can do more than make predictions because they can help manage tasks and workflows.

IBM is training consultants to understand both business problems and technology.

IBM says its own use of AI has produced more than $4.5 billion in productivity benefits.

Indian companies are also looking for AI systems that give them more control over data, governance and model choices.

Key facts

Interviewee: Rishi Aurora, Managing Partner, IBM Consulting India & South Asia
Main scaling obstacle: Weak operating models and foundations around AI, rather than inadequate AI models
Key banking use cases: Fraud detection, cybersecurity, KYC and AML
IBM productivity benefit: More than $4.5 billion through its Client Zero journey, according to Aurora
Consultant training focus: Industry expertise, business acumen and technology fluency
Sovereignty priorities: Data location, AI governance, model choice and reduced vendor lock-in
Preferred architecture: Open and flexible AI architectures that preserve choice and support changing regulations

financialexpress.com · 2 weeks ago