#AI and governance frameworks

[zomb13s]

The Flipped Script: Intelligence, Authority, and the Complex Interplay of Power in Society

Introduction The intersection of artificial intelligence, power structures, and the psychological dynamics of authority forms a rich ground for critical reflection. As CEO of alfons.design, and as someone who has experienced the transformational moment of soliciting for a position within the council of state of the Netherlands’ royal household, the experiences of Alfons Scholing offer a unique…

[tejasviaddagada]

About us | Tejasvi Addagada | Data Management Services

Tejasvi Addagada specializes in delivering comprehensive Data Management Services tailored to help organizations optimize, secure, and govern their data. With expertise in data governance, data quality, and analytics, we provide customized solutions that enable businesses to make informed decisions, reduce risks, and enhance operational efficiency, ensuring data becomes a strategic asset for growth. Connect with us at 123-456-7890.

[aibusinessconsulting]

From Principles to Playbook: Build an AI-Governance Framework in 30 Days | Nate Patel

The gap between aspirational AI principles and operational reality is where risks fester – ethical breaches, regulatory fines, brand damage, and failed deployments. Waiting for perfect legislation or the ultimate governance tool isn't a strategy; it's negligence. The time for actionable governance is now.

This isn't about building an impenetrable fortress overnight. It's about establishing a minimum viable governance (MVG) framework – a functional, adaptable system – within 30 days. This article is your tactical playbook to bridge the principles-to-practice chasm, mitigate immediate risks, and lay the foundation for robust, scalable AI governance.

Why 30 Days? The Urgency Imperative

Accelerating Adoption: AI use is exploding organically across departments. Without guardrails, shadow AI proliferates.

Regulatory Tsunami: From the EU AI Act and US Executive Orders to sector-specific guidance, compliance deadlines loom.

Mounting Risks: Real-world incidents (biased hiring tools, hallucinating chatbots causing legal liability, insecure models leaking data) demonstrate the tangible costs of inaction.

Competitive Advantage: Demonstrating trustworthy AI is becoming a market differentiator for customers, partners, and talent.

Read More: From Principles to Playbook: Build an AI-Governance Framework in 30 Days

[natepatel]

The 30-Day Sprint: Your Week-by-Week Execution Plan

(Assumes a small, dedicated core team - e.g., Governance Lead, Legal/Compliance Rep, Tech Lead, Risk Officer - supported by part-time SMEs)

Week 1: Foundation & Policy (Goal: Draft Policy Signed Off)

Day 1-2: Kickoff & Stakeholder Mapping. Assemble core team. Identify key stakeholders (Legal, Compliance, Security, Privacy, Risk, IT, key business units using AI). Map known AI projects (shadow AI hunt!).

Day 3-4: Gap Analysis & Principles Review. Audit existing relevant policies (IT, Security, Privacy, Ethics, Procurement). Review current AI principles. Identify immediate high-risk AI use cases.

Day 5-6: Draft Risk Classification Schema & Core Requirements. Define simple High/Medium/Low criteria. List 5-7 non-negotiable mandatory requirements based on principles and regulations.

Day 7: Develop Policy Draft. Consolidate schema and requirements into a concise Enterprise AI Policy & Standards draft document.

Deliverable: Draft AI Policy & Standards Document.

Read More: From Principles to Playbook: Build an AI-Governance Framework in 30 Days

- Nate Patel

[jcmarchi]

Building Confidence in AI: Training Programs Help Close Knowledge Gaps

New Post has been published on https://thedigitalinsider.com/building-confidence-in-ai-training-programs-help-close-knowledge-gaps/

Building Confidence in AI: Training Programs Help Close Knowledge Gaps

AI is reshaping the workforce at a breakneck speed, yet training efforts aren’t meeting the moment. Despite a quarter of executives feeling bullish on the technology, only 12% of workers have received AI-related training in the past year. This lack of preparation not only hinders the successful and safe adoption of AI, but also creates uncertainty amongst employees around the technology’s impact on their jobs. As the gap between executive excitement and employee reluctance grows, it’s clear that organizations need training tools to help build AI confidence and usher in this new era of innovation.

AI will enhance, not replace

Perhaps the most important factor of building AI confidence is helping employees understand how the technology will fit into their roles. Despite the amount of misinformation floating around, in most instances, AI is not meant to replace employees. In fact, recent companies that attempted to replace humans with AI are struggling to achieve the ROI they imagined. Instead, the real value of AI comes from using it to augment employee skill sets, productivity, and competitiveness in their fields. By efficiently handling more routine and administrative-heavy tasks, the technology allows employees to focus on higher-value tasks.

However, it’s just as important to note that integrating AI does not make this possible on its own, employees must understand how to use it effectively to unlock its full potential. Without the right training, AI can lead to concerns around data privacy, bias, and inaccuracies – making this foundational knowledge non-negotiable. That’s why both upskilling and cross-skilling are essential to keeping pace with change.

Upskilling vs cross-skilling

Upskilling and cross-skilling training both are used to help employees expand their skill sets and are critical tools when looking to adopt AI. While similar, it’s important to understand the difference between the two.

Upskilling is the process of strengthening existing skills and focuses on helping employees advance in their job and gain higher responsibilities. A great example of upskilling is training IT leaders – who already have a strong foundation in technology – to gain a deeper understanding of AI.

Cross-skilling is just as important, but it’s often overlooked in AI training. Cross-skilling (also known as cross-training) is the process of developing new skills that apply across different functions and focuses on training more than one employee in an organizational task. The adoption of AI and cross-skilling strategies must also be done simultaneously to ensure success. A great example to demonstrate cross-skilling would be a marketing leader with minimal technology background. As AI is increasingly used across departments, cross-skilling ensures that every employee is able to use the technology based on their specific roles and responsibilities.

Benefits of training in the age of AI

With industries, markets, and everyday business practices evolving, employee skills and knowledge remain the bedrock of organizational innovation. Employees want purpose and impact, and aligning corporate goals with employee ambitions is a guaranteed way to boost engagement. In addition, providing employees with the ability to alleviate burdensome tasks through AI helps boost overall satisfaction at work.

In an increasingly competitive landscape, meeting these needs and retaining top talent is crucial to sustaining productivity and growth. And while recent arguments state that those who already possess AI skillsets will take over jobs, 79% of learning and development professionals believe that it’s less expensive to reskill a current employee than to hire a new one.

Upskilling and cross-skilling in action

If upskilling and cross-skilling are not  a current part of  a learning and development program, organizations can leverage resources they already have available. Here are some best practices when getting started:

Assess Current Skillsets: Identifying upskilling and cross-skilling priorities is more difficult without a base-level understanding of the skillsets one’s employee base possesses, and which ones they will need to build confidence in AI. Given teams are already familiar with their roles and the organization as a whole, surveying the current level of AI knowledge and identifying  gaps is a great place to start.

Set Attainable Goals: With this foundational understanding of your workforce, the next step is to set upskilling and cross-skilling goals. It’s important to understand the “why” behind these training programs and identify where employees can and should grow. Goals should be set on an individual contributor level, while also identifying objectives for larger teams and the organization as a whole.

Rethink Learning Formats: Even the most robust training programs won’t move the needle if it’s not delivered in a format that resonates with your workforce. In fact, 86% of companies are unhappy with their existing training programs that they have in place. Employers are increasingly finding that live or in-person training programs no longer suffice. Instead, video-based learning that offers flexibility and better accessibility to various learning styles may be the best route for highly-complex topics like AI.

Prioritize Responsible AI: Implementing data privacy, security and data governance best practices is a crucial step in ensuring that employees use AI responsibly. In addition, implementing a bias and transparency framework to validate AI output and build confidence with AI effectiveness within the organization can be crucial. To help with this, organizations should consider building “AI champions” to teach employees how to effectively use AI so that humans can benefit from the productivity gains and yet have the skills to protect from hallucinations and bias.

Monitor and Promote: For upskilling and cross-skilling to be impactful, employees need to have the opportunity to expand their responsibilities. Organizations should enable a reward structure that motivates employees to look for creative ways to use AI to help improve departmental and organizational efficiency and fast track innovation.

The bottom line

While AI holds exponential promise for the modern workplace, employees are the linchpins who will determine its success. Regardless of their role, department, or expertise, having a foundation of AI knowledge will benefit career trajectories and the business as whole. By focusing not only on upskilling tech-forward employees, but cross-skilling to create a larger AI-centric culture, organizations can reap the benefits of improved engagement, talent retention, and competitive market expertise.

[goodoldbandit]

Governance, Risk, and Compliance (GRC) in the Age of AI: Balancing Innovation with Responsibility.

Sanjay Kumar Mohindroo Sanjay Kumar Mohindroo. skm.stayingalive.in Explore how AI is reshaping governance, risk, and compliance—and what CIOs and tech leaders must do to lead responsibly. A Moment of Reckoning for Digital Leadership As a technology executive navigating the intersection of artificial intelligence (AI) and enterprise strategy, I’ve come to recognize one hard truth: you cannot…

[adeptivai]

Adeptiv.ai: Pioneering AI Governance Frameworks for Ethical and Compliant AI

Explore how Adeptiv.ai offers a comprehensive AI governance framework that simplifies compliance with global regulations like the EU AI Act and NIST AI RMF. Their platform automates up to 70% of compliance workflows, ensuring transparency, accountability, and trust in AI systems.

[neilsblog]

Understanding Governance, Risk, and Compliance Platforms: A Comprehensive Guide

In today’s ever-evolving business environment, the ability to effectively manage Governance, Risk, and Compliance (GRC) has become more critical than ever. As organizations expand, navigate regulatory landscapes, and embrace digital transformation, a well-structured GRC framework is no longer a luxury—it’s a necessity. An integrated GRC solution not only ensures regulatory adherence but also acts…

[rightnewshindi]

AI का जिन्न बोतल से बाहर: उपराष्ट्रपति जगदीप धनखड़ ने विनियमन की जरूरत पर दिया जोर, चेताया- हो सकती है तबाही

Jagdeep Dhankhar: नई दिल्ली में शुक्रवार, 4 अप्रैल 2025 को उपराष्ट्रपति जगदीप धनखड़ ने आर्टिफिशियल इंटेलिजेंस (AI) के विनियमन को लेकर एक अहम और विचारणीय बयान दिया। राज्यसभा सांसद सुजीत कुमार की पुस्तक “AI ऑन ट्रायल” के विमोचन के मौके पर उन्होंने कहा कि AI का सही ढांचा ही यह तय करेगा कि हमारा समाज भवि��्य में किस दिशा में जाएगा। उनके शब्दों ने न सिर्फ तकनीकी विशेषज्ञों, बल्कि आम लोगों का भी ध्यान…

[rsayoub]

Lionbridge Language AI Unleashed: Transforming Localization with Vincent Henderson

In the latest episode of the Localization Fireside Chat, I had the privilege of speaking with Vincent Henderson, Vice President of Language AI Strategy at Lionbridge, one of the leading global companies in localization and AI-driven language solutions. Our conversation focused on how Lionbridge is leveraging AI to revolutionize localization processes, transforming efficiency, quality, and…

[nemkodigital]

Enhance AI transparency, quality and performance with expert advise on governance and AI strategy. Manage your AI models, risks, lifecycle and data for success.

[tejasviaddagada]

Corporate Data Governance in the Digital Era- Tejasvi Addagada

Corporate Data Governance is vital in today’s digital economy. This blog explores how a strong data governance strategy, combined with data management services and frameworks, enhances data quality and security. Learn how businesses can navigate challenges using corporate data governance practices and implement AI-driven solutions like data quality generative AI to ensure compliance, integrity, and informed decision-making.

[procurement-insights]

Procurement didn't start the fire, Gartner did?

Did Gartner create the FUD that led to GenAI initiative failures?

Ryan Backman Senior Account Executive @ Gartner | Problem Solver | Quote EnthusiastSenior Account Executive Book an appointment • 12 hours ago Gartner predicts that by 2027, 60% of organizations will fail to realize the expected value of their AI use cases due to incohesive ethical governance frameworks.Learn how proactive CDAOs are prioritizing AI-ready data governance.Gartner for IT |…

[thisisgraeme]

AI Governance in Education: Insights from Thought Leadership and Comparative Findings in Aotearoa New Zealand

How can AI governance shape the future of education? Explore key insights from PwC and our own findings on ethical oversight, AI in classrooms, and the role of leadership in driving responsible AI use. Read more! #AIinEducation

As AI continues to permeate various sectors, including education, understanding how it should be governed is essential. In PwC New Zealand’s Artificial Intelligence: What Directors Need to Know, a comprehensive framework for AI governance is presented, offering valuable insights that extend beyond corporate boardrooms and into the educational landscape. While the report is primarily…

[jcmarchi]

UK Government prioritizes AI for economic growth and services

New Post has been published on https://thedigitalinsider.com/uk-government-prioritizes-ai-for-economic-growth-and-services/

UK Government prioritizes AI for economic growth and services

The UK government is significantly pushing to harness the power of artificial intelligence (AI) as a central tool for economic growth and improved public services. Newly appointed Science Secretary Peter Kyle has declared AI a top priority, aiming to leverage its potential to drive change nationwide.

On July 26th, Science Secretary Peter Kyle appointed Matt Clifford, a prominent tech entrepreneur and Chair of the Advanced Research and Invention Agency (ARIA), to spearhead the government’s AI initiatives. Clifford’s primary task will be to develop a comprehensive AI Opportunities Action Plan. This plan explores how AI can enhance public services, drive economic growth, and position the UK as a leader in the global AI sector.

“We’re putting AI at the heart of the government’s agenda to boost growth and improve our public services.” — Science Secretary Peter Kyle

Developing a competitive UK AI sector

A key focus of the AI Opportunities Action Plan will be building a robust UK AI sector that can scale and compete internationally. The plan will outline strategies to accelerate AI adoption across various sectors of the economy, ensuring that the necessary infrastructure, talent, and data access are in place to support widespread implementation.

The Action Plan is expected to be a critical driver of productivity and economic growth in the UK. According to estimates from the International Monetary Fund (IMF), the widespread adoption of AI could potentially boost UK productivity by up to 1.5 percent annually. While the timeline for realizing these gains may be gradual, the long-term benefits are substantial.

To support the implementation of the Action Plan, the Department for Science, Innovation and Technology (DSIT) will establish a new AI Opportunities Unit. This unit will bring together expertise from across government and industry to maximize AI’s benefits, ensuring that the UK can fully capitalize on this transformative technology.

Government and industry collaboration

Developing the AI Opportunities Action Plan will involve close collaboration with key figures from industry and civil society. The plan will also consider the UK’s infrastructure needs by 2030, including the availability of computing resources for startups and the development of AI talent in both the public and private sectors.

Science Secretary Peter Kyle emphasized the importance of AI in the government’s agenda, stating, “We’re putting AI at the heart of the government’s agenda to boost growth and improve our public services.” He expressed confidence in Matt Clifford’s ability to drive this initiative forward, highlighting Clifford’s extensive experience and shared vision for the future of AI in the UK.

Chancellor of the Exchequer Rachel Reeves also underscored AI’s economic potential, noting that it could help create good jobs across the country, deliver improved public services, and reduce taxpayer costs.

Matt Clifford’s vision for the future

Matt Clifford expressed enthusiasm for his new role, stating, “AI presents us with so many opportunities to grow the economy and improve people’s lives. The UK is leading the way in many areas, but we can do even better.” He is set to deliver his recommendations to the Science Secretary in September, marking a significant step forward in the UK’s AI journey.

As the UK government places AI at the forefront of its agenda, the newly launched initiatives and the forthcoming AI Opportunities Action Plan are poised to play a pivotal role in shaping the future of the nation’s economy and public services. With strong leadership and collaboration between government, industry, and civil society, the UK is positioned to harness the full potential of AI, driving sustained economic growth and improving the lives of its citizens.

Read about how Singapore is approaching GenAI governance below:

Singapore’s Draft Framework for GenAI Governance

Explore Singapore’s new draft governance framework for GenAI, addressing emerging challenges in AI usage, content provenance, and security.

Like what you see? Then check out tonnes more.

From exclusive content by industry experts and an ever-increasing bank of real world use cases, to 80+ deep-dive summit presentations, our membership plans are packed with awesome AI resources.

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[iso-updates]

AI Governance Frameworks and ISO 42001: Ensuring Responsible AI Development

Artificial intelligence governance alludes to the regulations, planning, standards, and best practices that control the turn of events and utilization of digitalized reasoning frameworks. Artificial Intelligence (AI) Governance expects to limit risks from AI while augmenting the advantages.

A few critical parts of AI Governance Frameworks incorporate transparency, responsibility, bias identification, security, and oversight. Guidelines might require clear documentation of preparing data and measurements, so the rationale behind artificial intelligence frameworks can be examined. 

Inspecting processes can check for uncalled-for inclination and absence of logic. Governance strategies advance AI security through procedures like inspecting during preparatory testing stages. Multipartner bodies administer compliance and review progress.

Many challenges exist in administering quickly propelling innovation like artificial intelligence. Ideas and applications outperform policymaking. Be that as it may, complete governance safeguards people and society while empowering development. Frameworks should adjust these results across medical services, transportation, law enforcement, and more areas. With insightful methodology, AI’s commitment can be acknowledged responsibly.

AI in the Work Environment

The previously mentioned AI governance systems assume a crucial part in giving an organized arrangement of rules and rules that advance the capable turn of events and utilization of artificial intelligence. These rules assist with relieving potential dangers related to AI deployment, for example, bias, protection concerns, and unseen side effects.

Besides, these systems add to regulatory compliance, assisting organizations with exploring the advancing lawful scene encompassing artificial intelligence innovations.

Assuming your association is taking a look at adding AI-driven devices to your tech stack, it pays to know about the ongoing strategy scene. Like that, you also can embrace the tremendous capability of AI while defending your organization's delicate data and safeguarding your workers, clients, and other prime groups.

Significance of an AI Governance Framework 

For AI to be genuinely important and broadly acknowledged, it should adjust data-driven decision production with accepted practices and ethical standards, and a powerful simulated intelligence governance framework fills in as the bedrock for following these targets.

Entrusting Trust and Ethical Contemplations

Dependability and morals are fundamental parts of simulated intelligence administration. Trust in AI systems is based upon the confirmation that they work morally and capably, regarding the privileges and security of people. 

An artificial intelligence governance structure lays out a framework with clear rules and guidelines with guarantee that artificial intelligence technology complies with ethical limits and cultural standards. By fostering a framework around responsibility and comprehensiveness, the system encourages trust preparing for far and wide acknowledgment and reception.

Data Transparency and Compliance

Integral to artificial intelligence governance is the idea of data transparency and compliance. AI frameworks depend intensely on data, and it's basic that this information is taken care of accurately and stays safeguarded. A viable simulated intelligence administration structure guarantees that data assortment, handling, and use stick to regulatory requirements and ethical principles. 

By advancing transparency in data practices, an artificial intelligence governance system improves trust in artificial intelligence advancements while moderating the risk related to data abuse or misuse.

Better Data-Driven Choices

A successful AI governance system plays a significant part in working with better data-driven choices. By laying out clear cycles for data management, and adjusting artificial intelligence drives to ethical limits and cultural standards, the structure guarantees that data-driven decisions are compelling and socially aware. This prompts further developed results across the private and public areas, from medical care and money to transportation and training.

Generally, an AI governance system is fundamental for ensuring that artificial intelligence advancements are data-driven, responsible, ethical, and lined up with accepted practices. By advancing data transparency, compliance, and moral way of behaving, the structure empowers organizations to use simulated intelligence really while building trust and certainty among clients and partners.

Step-By-Step Instructions to Prepare for AI Governance

To plan for arising guidelines for Artificial Intelligence Management Systems, associations can make the accompanying strides:

Remain Informed: Stay up with the latest with the most recent improvements in artificial intelligence guidelines by keeping important news sources, going to industry occasions, and drawing in specialists in the field.

Lead an Artificial Intelligence Audit: Play out an extensive audit of your association's AI systems to recognize likely dangers or moral worries, ensuring the headway and governance of artificial intelligence line up with laid-out AI standards. This incorporates surveying data assortment and use practices, algorithmic dynamic cycles, and effects on partners.

Foster an AI Ethical System: Make a strategy illustrating your organization’s qualities, standards, and planning for responsible artificial intelligence improvement and use. This report ought to incorporate rules for risk management, data protection, inclination alleviation, lucidity, and responsibility.

Train Workers: Guarantee that all employees engaged with creating, delivering, or utilizing AI put-together technologies are prepared concerning ethical contemplations and best practices for AI governance.

Carry out Monitoring and Revealing Components: Lay out observing and detailing instruments to follow the exhibition and effect of your AI frameworks over the long run. This incorporates ordinary appraisals of the framework's exactness, reasonableness, and inclined choices.

The Expectations of ISO 42001

ISO 42001 Certification gives broad direction on the most proficient method to manage and deal with the production of AI frameworks, permitting associations to approve the way that the simulated intelligence frameworks that they are creating, utilizing, or potentially giving are responsible and powerful. It ought to be noted, in any case, that this standard isn't planned to be a 'how to do simulated intelligence' guide. It will likewise not be guaranteed to ensure compliance with obligatory guidelines, for example, the EU Artificial Intelligence Act. 

The standard is additionally not planned to line up with a specific guideline or regulation, thus, while it could be extremely useful in empowering you to accomplish compliance and anticipates that you should keep up with the consciousness of the pertinent guidelines, it won't supplant them.

The Future of AI

As we investigate the fate of AI reasoning, the job of AI governance is progressively crucial, filling in as the preparation for the responsible improvement of artificial intelligence drives and applications, and giving the fundamental design and rules to guarantee ethical, transparent, and responsible artificial intelligence plans.

Conclusion

In this present reality where simulated intelligence's impact is quickly growing, sticking to ISO 42001 Certification ensures compliance with moral guidelines assembles partner certainty, and improves authoritative flexibility. As AI advancements develop, the standards and rules framed in ISO 42001 will be instrumental in directing associations toward mindful and reasonable artificial intelligence practices.