AI

What The Last Century Of Cybersecurity Can Teach Us About What Comes Next In The Age Of AI

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AI transforms cybersecurity; businesses must adapt rapidly to avoid falling behind. With only 30% ready for AI integration, understanding past security evolutions can guide future strategies. AI can process alerts and aid in threat detection. Analysts must oversee AI actions, ensuring effectiveness and connection to business objectives. Emphasizing AI as a team member, training analysts as supervisors, and tying AI tasks to business impacts will enhance security operations and competitiveness.

https://www.forbes.com/councils/forbestechcouncil/2025/07/18/what-the-last-century-of-cybersecurity-can-teach-us-about-what-comes-next-in-the-age-of-ai/

The EU AI Act: What You Need to Know

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EU AI Act Summary: The EU AI Act, adopted by the European Parliament, regulates AI development and use, balancing adoption with individual rights. It categorizes AI risks as unacceptable, high, and low/minimal. Unacceptable risks, like harmful subliminal influences, are banned. High-risk systems must comply with strict standards, while low-risk systems face fewer regulations. The Act will gradually implement over time, with measures including prohibitions on risky systems, establishment of national AI regulatory sandboxes, and guidance on high-risk categories. Organizations must assess and document their AI systems regarding these classifications.

https://kpmg.com/dk/en/ai/the-eu-ai-act-what-you-need-to-know.html

The General-Purpose AI Code of Practice

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EU's General-Purpose AI Code of Practice, published July 10, 2025, aids industry compliance with AI Act on safety, transparency, and copyright. It's voluntary for AI model providers, offering legal certainty and reduced administrative burdens. The code includes chapters on Transparency, Copyright, and Safety, applicable to advanced models with systemic risks. Providers can sign the code to demonstrate compliance.

https://digital-strategy.ec.europa.eu/en/policies/contents-code-gpai

Why CIOs Must Build the Infrastructure That Makes AI Drive Revenue

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CIOs must develop robust infrastructure to leverage AI for driving revenue, transforming their role from IT leaders to strategic growth architects. Despite high confidence in AI, many organizations struggle with disconnected revenue processes and poor data trustworthiness. CIOs are tasked with creating integrated systems that automate workflows, harness data context, and ensure governance, enabling AI to provide reliable insights. The rise of the “Revenue Architect” role reflects this shift, emphasizing unified data management and strategic workflow design to optimize AI's effectiveness in revenue generation.

https://www.intelligentcio.com/north-america/2025/07/11/why-cios-must-build-the-infrastructure-that-makes-ai-drive-revenue/

Europe’s AI Code Urges Companies to Disclose Training Data and Avoid Copyright Violations

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EU's AI code mandates companies disclose training data and respect copyright, facing fines up to 7% of revenue for noncompliance. Guidelines aim to help tech giants like OpenAI and Google follow the AI Act, which includes transparency about model development and safety measures.

https://www.techspot.com/news/108644-europe-ai-code-urges-companies-disclose-training-data.html

European Commission Receives Final Version of General-Purpose AI Code of Practice

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European Commission publishes final General-Purpose AI Code of Practice, aimed at governing AI operations ahead of the EU AI Act's August rules. Code is voluntary, offering compliance benefits like reduced administrative burden. It addresses safety, transparency, and copyright obligations, developed with input from 1,000+ stakeholders. Debate continues on its effectiveness and regulatory burden, with companies expressing concerns over its prescriptiveness and need for implementation time. Official endorsement from member states is next, allowing organizations to voluntarily comply.

https://iapp.org/news/a/european-commission-receives-final-version-of-general-purpose-ai-code-of-practice

CIOs Tackle the AI Change Management Challenge

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CIOs are enhancing change management to boost generative AI adoption and business value. Companies like Principal Financial Group and Liberty Mutual emphasize education, collaboration, and culture shifts. Research indicates that effective change strategies address employee trust and skill gaps, while CIOs are seen as key change agents. Innovations include structured training programs, collaborative workflows, and grassroots influencer approaches, enabling organizations to adapt and experiment with AI, ultimately improving productivity and fostering a culture of innovation.

https://www.cio.com/article/4016354/cios-tackle-the-ai-change-management-challenge.html

It’s Time to Retire the Ticket: An IT Roadmap for Agentic AI

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TLDR: IT tickets are outdated and hinder productivity in modern enterprises. They slow down response times and create inefficiencies. The future demands proactive solutions using agentic AI and automation to resolve issues before they escalate. This involves reimagining service delivery, focusing on automation of repetitive tasks, integrating AI for intelligent decision-making, and allowing human agents to concentrate on higher-level strategic tasks. By transitioning to this model, organizations can enhance productivity, reduce incident resolution times, and align IT outcomes with business goals.

https://www.cio.com/article/4018133/its-time-to-retire-the-ticket-an-it-roadmap-for-agentic-ai.html

How Should Businesses Kick Off Their AI Initiatives? Time for the AI Advice Column

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Businesses should initiate AI projects with caution, focusing on clear goals like efficiency or competitive advantage. They need to consider their current capabilities, data quality, and potential risks involved. Smaller firms may struggle without necessary personnel or adequate infrastructure. It’s essential to evaluate AI opportunities, prioritize tasks, and prepare for organizational changes, ensuring proper training and change management. Ultimately, selecting a well-defined proof of concept can aid in navigating the complexities of AI implementation.

https://diginomica.com/how-should-businesses-kick-their-ai-initiatives-time-ai-advice-column-your-doctors-are

Cybersecurity and AI : Towards a New Human-centered Approach

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AI adoption is reshaping business and increasing risks, requiring a shift in cybersecurity to focus on human factors. Traditional security methods are insufficient as threats exploit human cognitive weaknesses. New scenarios include deepfake impersonation and misinformation. Addressing these risks involves enhancing cognitive awareness, establishing verification protocols, regulating AI use, mapping cognitive risks, and preparing response teams. A cultural shift in organizations is essential for proactive AI risk management, integrating technology with human capabilities for comprehensive cybersecurity.

https://www.rsm.global/france/en/insights/yuksel-aydin-cybersecurity-ai-human-centered-approach

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