Perspectives

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How telcos can harmonize service desk operations using ServiceNow

With a strong platform foundation and disciplined execution, telecom companies can unify fragmented service desks into an integrated, measurable service operation.

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Beyond copilots: The agentic enterprise

Why most enterprises aren’t ready to let AI agents act on their behalf, and the four-stage roadmap that gets them there.

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How to scale AI: Why business value depends on rewiring the operating model

Many enterprises are investing heavily in AI but seeing little return because they are not focusing on how the business is organized. The technology is important, but the operating model around it is even more so. Organizations that build a product-centric, platform-driven operating model can scale AI and foster measurable business value.

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AI capability maturity model: When scaling needs a game plan

Organizations must assess their current maturity and define their desired state to determine where to invest, before scaling.

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Why AI needs context before it can act

Enterprise context helps AI understand how a business works, enabling it to act within real-world processes, policies, and decisions rather than simply analyze data.

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How AIOps and AI-powered observability transform enterprise IT operations

AI-powered observability and AIOps help manufacturers turn fragmented OT and IT signals into earlier warnings, faster decisions, and more resilient operations.

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How AI can transform telecom billing

What's holding back revenue management in telecom, and how AI and ontology can finally make billing predictable.

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AI token optimization: How to build cost-efficient AI

Token efficiency, or tokenomics, is now a primary design concern in AI deployments. To get ahead, organizations should build a framework of four composable levers, or thinking modes, applied across the agent stack to cut token expenditure without degrading output quality.

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How to build continuous, board-ready risk assurance

Regulatory change is accelerating and breach costs are rising, yet most institutions still rely on periodic, manual risk assurance. Three structural gaps, spanning visibility, third-party oversight, and governance, leave institutions unable to keep pace. Building risk assurance as a continuous, AI-augmented capability closes these gaps. A four-phase roadmap helps institutions get there.

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The missing operating discipline behind enterprise AI

The difference between AI work and AI that works lies in the discipline to scale adoption, governance, and value realization

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CRM's next evolution: From application to infrastructure

As AI agents become part of customer-facing operations, Headless CRM is emerging as the architectural bridge between the SaaS and AI-first eras.

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How enterprises can control AI agent sprawl

Learn how automated integrity checks and human oversight can help enterprises control AI agent sprawl, reduce duplication, and manage risk at scale.

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Trust, context, and control: The foundations of SAP's Autonomous Enterprise

As AI moves from assisting employees to participating in business execution, organizations must build the trust, context, and control needed to enable agent-led execution at scale.

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When the telecom buyer is a bot

The next telecom customer may not be human. AI agents are already consuming network services autonomously, and the operators that build the commercial infrastructure to serve them will define the future of machine-to-machine commerce.

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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