Perspectives

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Bring compute to data: The next phase of multi-cloud strategy

As organizations expand across multiple cloud ecosystems, successful modernization increasingly depends on keeping enterprise data, applications, and cloud services closely connected while preserving the Oracle environments that support critical business operations

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The human side of AI-native telecom companies

Telecom's workforce is AI-ready — yet the organizational strategy, structures, and capabilities to channel that readiness remain underdeveloped. This article examines the gap and sets out what telecom companies must do to close it.

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Why enterprise agentic AI programs stall before they scale

Enterprises are racing to scale agentic AI, but most programs are unable to move past pilots. This article explores the reasons why, and what enterprises need to get right to move from pilot to scale.

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How to generate long-term value from enterprise AI

Sustained AI business value requires moving beyond stacking up use cases to building durable, enterprise-wide capabilities.

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Integrated revenue growth management platforms for CPGs: A buyer's guide

CPGs can shift from fragmented levers to integrated decision-making, enabling faster action, stronger margins, and scalable growth.

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How matrix telcos can maintain autonomy with a unified platform

A unified platform balances business unit autonomy with enterprise-wide integration, governance, and service assurance. deployment.

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From intent to impact: How manufacturers link AI use cases to measurable outcomes

Explore how manufacturers can link AI use cases to measurable outcomes across design, supply chain, production, cybersecurity, warehouse, sales, marketing, and service.

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How AI is changing the telecom playbook

AI costs are exploding and businesses are struggling to manage them. Telecom companies have the billing infrastructure, sovereign networks, enterprise trust, and data assets to become the AI consumption layer companies need. Five monetization lanes define the opportunity. Early movers are already in the market.

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From implementation to sustained control: AI's role in SAP S/4HANA for life sciences

As life sciences organizations expand their use of SAP S/4HANA, the focus is shifting from implementation success to maintaining operational discipline, compliance, and control at scale.

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Trust but verify: Why enterprises need AI observability

AI observability keeps systems reliable, accurate, and aligned with their intended purpose long after deployment.

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The pros and cons of core modernization in insurance

This discussion of insurance core modernization and artificial intelligence comes from a series of questions put to Infosys insurance and technology experts by a technology leader at an insurer. It gives guidance on where AI is changing insurance technology and what that means for modernization strategy.

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The missing link in enterprise AI adoption: How to build the conditions for success

AI adoption is only as strong as the organizational support employees receive.

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Trust over tech: The key to AI adoption

AI adoption will accelerate only when organizations reduce employees' job security fears and build confidence in how AI will reshape their work.

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Why AI adoption looks different depending on your job level

Enterprise AI success depends on narrowing the adoption divide across senior, middle, and junior employees.

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Generative Engine Optimization: Enterprise Strategy Guide 2026

Generative AI platforms now cite only one to three sources per answer, making traditional SEO insufficient to gain and maintain digital visibility. This article explains how generative engine optimization (GEO) works, why it demands an enterprise-wide response, and how organizations can build the cross-functional capabilities needed to stay present, authoritative, and cited in an AI-first world.