Cloud insights

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How can tech leaders manage emerging generative AI risks today while keeping the future in mind?

In the third installment of Deloitte’s Engineering in the age of Generative AI series, we explore four gen AI risk categories and how leaders can help manage them

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How should banks respond to the current disruption in software engineering?

As banks race into an AI-driven future, they should embrace a new set of approaches to software engineering, including refreshing their talent strategies and third-party relationships

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Four data and model quality challenges tied to generative AI

As gen AI programs scale, they’re spotlighting data integrity and model accuracy challenges that may require new strategic solutions to maintain overall software quality and trust

AI data integrity and model accuracy challenges may require new solutions to maintain quality and trust in AI software development.

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Cloud gets lean: ‘FinOps’ makes every dollar work harder

Enterprise cloud spend is growing, and using FinOps strategies can make each dollar work harder. Companies can save money, boost value, and build cross-functional cohesion.

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Wireless telecom consolidation speeds up … where regulators allow

In many markets, smaller wireless telecoms see slow growth, low profits, and have debt to repay. M&A, specifically combining assets or even entire consumer-facing companies, may help where it gets approved by regulators.

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The State of Generative AI in the Enterprise

2024 year-end Generative AI report

Explore the Deloitte AI Institute’s quarterly Generative AI report tracking Generative AI investments, adoption, impacts on business, and challenges across 2024.

Perspectives

Platform-as-a-product

Shifting to a product mindset for platform technology

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EngineeringBeat: Fast-tracking mainframe modernization

Key health care modernization insights

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EngineeringBeat: Navigating mainframe modernization complexity

Overcoming digital transformation challenges in banking and capital markets

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EngineeringBeat: Accelerating mainframe modernization

Insights for the transportation and
hospitality sectors

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EngineeringBeat: Cloud modernization for life sciences

Building a future-ready IT ecosystem with cloud migration and AI

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Optimizing digital ecosystems to create more value

Digital ecosystems have the potential for value creation beyond customers. How can strategy leaders take a broader perspective and capture more value from their investments?

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Tech companies lead the way on generative AI: Does code deserve the credit?

Are gen AI coding tools the thin edge of the wedge that can lead to wider use of gen AI across all industries?

Perspectives

Placing your bets: Developer experience strategy

How to invest in the experience of your developer teams

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The power of a mainframe modernization and cloud migration strategy

Mainframe modernization—migrating core applications to a more technologically advanced environment—isn’t optional; it’s essential. As technology evolves, digital transformation is imperative to boost agility, leverage modern tools, and enhance security. A sound modernization and cloud migration strategy can help modernize legacy systems and drive transformation to increase innovation and growth.

Perspectives

Software engineering for your digital business future

Four models of digital product engineering organizations

Traditional, Orchestrator, Innovator, or Leader? Explore four models for software engineering and learn how to be a Leader.

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Gen AI investment opportunities center on data, cybersecurity, and cloud, Deloitte survey finds

Deloitte’s State of GenAI quarterly survey explores where industry leaders are increasing generative AI funding as they work to implement strategies

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Unlocking industry advantage through tech investment

Tech’s role in reshaping the future of industry is huge. Learn how it’s helping create a competitive edge for many businesses across sectors.