#AI-driven governance

[zomb13s]

Honey or Vinegar: Analyzing Influence, AI, and Leadership Dynamics in Modern Governance

Alfons Scholing, CEO of Alfons Design, Founder of the Ik Zie Zombies Platform The complexities of global governance, particularly in the era of rapid technological advancement and artificial intelligence, call for deeper insights into how leadership shapes both societal dynamics and individual lives. My personal journey, profoundly altered after soliciting the position of Vice President of the…

[insightfultrends]

Elon Musk’s Ally Pushes for ‘AI-First’ Strategy in Government Agency

Elon Musk’s Ally Pushes for ‘AI-First’ Strategy in Government Agency In a groundbreaking statement, a close ally of Elon Musk has revealed that embracing an “AI-first” approach is the future for a key government agency. This bold vision outlines how artificial intelligence (AI) will shape the operations and policies of government entities, especially those tied to technology and national…

[iyemarathichiyenagari1971]

महाराष्ट्र कृषि-कृत्रिम बुद्धिमत्ता महाॲग्री-एआय धोरणास मंत्रिमंडळ बैठकीत मंजुरी

महाॲग्री-एआय (MahaAgri-AI) धोरण २०२५-२०२९ मंजूर  मुंबई – राज्याच्या कृषि क्षेत्राला डिजिटल युगात अग्रेसर ठेवणाऱ्या “महाराष्ट्र कृषि-कृत्रिम बुद्धिमत्ता महाॲग्री-एआय (MahaAgri-AI) धोरण २०२५-२०२९” या धोरणास मंगळवारी ( ता. १७ ) मंत्रिमंडळाच्या बैठकीत मंजुरी देण्यात आली.   बैठकीच्या अध्यक्षस्थानी मुख्यमंत्री देवेंद्र फडणवीस होते.             कृत्रिम बुद्धिमत्ता (AI), निर्मितीक्षम कृत्रिम…

[goodoldbandit]

Navigating the AI Act: What Technology Leaders Need to Know.

Sanjay Kumar Mohindroo Sanjay Kumar Mohindroo. skm.stayingalive.in What tech leaders must know about the EU AI Act—strategic risks, practical tools, future outlook, and leadership insight. A New Chapter for Digital Transformation Leadership. We’re standing at a turning point. The AI Act—Europe’s bold attempt to regulate artificial intelligence—is no longer a far-off policy discussion. It’s…

[tagbintech]

AI Streamlining Decision-Making 2025: Transforming Business Efficiency

Introduction

In 2025, artificial intelligence (AI) is revolutionizing decision-making processes across industries, making operations faster, more accurate, and highly data-driven. With AI-powered analytics, predictive insights, and automation, businesses can optimize strategies and improve overall efficiency. This article explores how AI is streamlining decision-making in 2025, its applications, and the future it holds for businesses worldwide.

How AI is Transforming Decision-Making in 2025

1. Real-Time Data Processing for Faster Decisions

AI-powered algorithms can process vast amounts of data in real time, enabling companies to make swift and informed decisions. Businesses no longer have to rely on traditional data analysis, which often lags behind market trends.

2. Predictive Analytics for Strategic Planning

AI-driven predictive analytics help businesses anticipate trends and challenges before they arise. This allows companies to implement proactive strategies rather than reactive measures, ensuring competitive advantages in dynamic markets.

3. AI in Financial Decision-Making

AI is transforming financial forecasting, risk assessment, and investment strategies. By analyzing historical data and market patterns, AI enables businesses to make profitable financial decisions while minimizing risks.

4. Enhancing Customer Decision Journeys

Companies are using AI to personalize customer experiences by analyzing preferences and behaviors. AI-driven recommendation engines enhance decision-making in marketing, sales, and customer service.

5. AI-Driven Automation for Operational Efficiency

From supply chain management to HR processes, AI streamlines decision-making by automating repetitive tasks, reducing human error, and improving efficiency.

The Role of AI in Different Industries

AI in Healthcare Decision-Making

AI assists doctors in diagnosing diseases, recommending treatments, and predicting patient outcomes with high accuracy. AI-driven diagnostics speed up decision-making and improve patient care.

AI in Manufacturing & Supply Chain Management

Manufacturers leverage AI for inventory optimization, quality control, and production planning. AI-powered supply chain analytics reduce delays and optimize logistics.

AI in Marketing and Customer Engagement

AI helps marketers analyze consumer behavior and optimize campaigns, ensuring personalized and data-backed decision-making in advertising strategies.

AI in Corporate Governance

AI enhances corporate decision-making by analyzing legal and compliance risks, ensuring transparency, and mitigating potential business threats.

The Future of AI in Decision-Making

AI is expected to become even more sophisticated, integrating with blockchain, IoT, and quantum computing for enhanced decision intelligence. AI-driven platforms will offer real-time insights, self-learning capabilities, and autonomous decision-making systems.

Conclusion

AI in decision-making is revolutionizing industries, empowering businesses with data-driven insights, automation, and strategic planning. As we step into 2025, AI will continue to be a game-changer, improving efficiency, reducing risks, and driving growth. Companies that embrace AI will lead the future, making smarter and faster decisions in an increasingly competitive world.

[jamesmitchia]

Impact AI: The State of AI-Powered Transformation in Government

A guide for delivering your mission today and a roadmap for tomorrow

AI is revolutionizing government operations, enabling faster and more efficient public services. But how are leading organizations achieving real impact?

A global survey of 1,248 government leaders by ServiceNow and ThoughtLab uncovers three key imperatives for AI-driven transformation:

Harness AI and scalable IT platforms. Government agencies must modernize systems to unlock AI’s full potential.

Build human-centric experiences and trust. Citizen and employee engagement is crucial for sustainable digital transformation.

Prepare for regulatory and risk challenges. AI adoption must align with evolving governance frameworks.

Who Are the AI Pacesetters

The study identifies a group of high-performing government agencies called Pacesetters that are achieving extraordinary results:

Seventy percent faster return on investment than expected

One point five times faster time to value compared to others

Fifty percent higher asset utilization

Forty nine percent better risk and compliance management

Forty one percent faster and more efficient public services

Forty one percent increased employee productivity

As agencies digitize services, the benefits multiply. Pacesetters lead the way, demonstrating that AI-powered workflows drive transformative success.

Unlock the AI Advantage

Discover how top-performing government organizations are accelerating impact with AI. Download the full report now to learn how you can drive faster innovation, build trust, and navigate AI regulations effectively.

Get the Report Here

About Us

IntentTech Insights™: Your Tech World Navigator

Uncharted waters demand a seasoned guide. We excel in providing intent-based technology intelligence to navigate complex technology landscapes, such as IT, cybersecurity, data storage and networks, SaaS, Cloud, Edge, IoT, AI, HR technologies, Contact Center software, Fintech, Martech, and 150+ other domains.

IntentTech Insights™ is your compass through the ever-evolving tech landscape. We are more than just a publication; we are your strategic partner in navigating the complexities of the digital world.

Our mission is to deliver unparalleled insights and actionable intelligence to tech professionals and enthusiasts alike. We delve deep into the latest trends, technologies, and innovations, providing comprehensive coverage that goes beyond surface-level reporting.

[leonbasinwriter]

The system is moving. Not just AI, not just business—intelligence itself is in play.

[jcmarchi]

IBM’s leadership in genAI: Insights from Manav, CTO of IBM Canada

New Post has been published on https://thedigitalinsider.com/ibms-leadership-in-genai-insights-from-manav-cto-of-ibm-canada/

IBM’s leadership in genAI: Insights from Manav, CTO of IBM Canada

At the recent Generative AI Summit in Toronto, I had the opportunity to sit down with Manav Gupta, the CTO from IBM Canada to explore the company’s current work in generative AI and explore their vision for the future. Here are the key insights from our conversation, highlighting IBM’s ecosystem leadership, industry impact, and strategies to navigate challenges in the generative AI landscape.

IBM’s position in the generative AI landscape

Manav began by emphasizing IBM’s commitment to ensuring that enterprises own their AI agenda. He stressed the importance of AI being open and accessible to organizations, individuals, and societies to foster growth. To this end, IBM leads with Watson X, a comprehensive platform that serves as both a model garden and a prompt lab. Watson X allows users to leverage IBM-supplied models, third-party models, or even fine-tune their own models for deployment on their preferred cloud or on-premises infrastructure.

One of the standout features of IBM’s approach is its focus on AI governance. Manav highlighted the critical need for enterprises to ensure that the AI they deploy is free from biases, hate speech, and other ethical concerns. IBM’s governance platform is designed to address these issues, ensuring that generative AI outputs are safe and unbiased.

The transformative impact of generative AI

When asked about the impact of generative AI across industries, Manav was unequivocal in his belief that this technology will touch every sector. He cited estimates that generative AI could add up to 3.5 basis points to global GDP, a staggering figure that underscores its potential. Industries such as banking, healthcare, telecommunications, and the public sector are poised to benefit significantly. 

Banking and Financial Services: Streamlining workflows and enhancing decision-making.

Public Sector and Healthcare: Unlocking data-driven efficiencies and improving service delivery.

Telecommunications: Transforming customer interactions and operational processes.

Manav explained that wherever there is a large corpus of data and existing workflows, generative AI can unlock human potential by automating mundane tasks and allowing employees to focus on higher-value activities.

Challenges in deploying generative AI

Despite the immense potential, Manav acknowledged that deploying generative AI solutions is not without its challenges. One of the primary hurdles is client maturity. Many organizations are still in the experimental phase, trying to understand both the opportunities and the risks associated with this technology. Additionally, integrating generative AI with existing data systems is a significant challenge. Enterprises often have high-quality data, but it is locked in silos across departments such as finance, HR, and procurement. Accessing and unifying this data in a timely manner is a complex task.

Another major challenge is the resource intensity of generative AI. The specialized hardware required to run these models is expensive and often in short supply, leading to long lead times for deployment.

Future trends in generative AI

Looking ahead, Manav foresees several key trends in the generative AI market. He predicts that models will continue to improve, with a shift from large language models (LLMs) to more fit-for-purpose smaller models. These smaller models, often referred to as small language models (SLMs), are more efficient and tailored to specific use cases. Manav also highlighted the rise of agentic AI, where AI systems will have greater autonomy to execute tasks on behalf of humans, particularly in high-value areas like software engineering and testing.

Another trend is the increasing importance of multi-modal models, which can process and generate different types of data, such as images and text. Manav gave an example of how enterprises could use multi-modal models to analyze images and make decisions based on that analysis, opening up new possibilities for automation and efficiency.

Key takeaways from Manav’s presentation

Manav concluded our interview by summarizing the key takeaways from his summit presentation.

Be an AI value creator, not just a consumer. Don’t just use AI—figure out how to make it work for you.

Start with models you can trust. Whether it’s IBM’s Granite models or open-source alternatives, experiment with reliable AI solutions.

Don’t treat AI governance as an afterthought. Privacy, security, and responsible AI should be built into the foundation of your AI strategy.

Watch Manav’s presentation at the Generative AI Summit in Toronto.

IBM’s Granite models and InstructLab

During his presentation, Manav also delved into IBM’s Granite models, a series of open-source foundation models designed for enterprise use. These models, which include specialized versions for time series and geospatial data, are trained on vast amounts of data and are optimized for performance and cost-efficiency.

IBM has also developed InstructLab, a novel methodology for adding enterprise data to LLMs without the need for extensive fine-tuning. This approach allows organizations to iteratively train models on their specific data, ensuring that the AI remains relevant and accurate for their unique use cases.

Conclusion

Manav’s insights underscore IBM’s leadership in the generative AI space, particularly in addressing the challenges of scalability, integration, and governance. As enterprises continue to explore the potential of generative AI, IBM’s Watson X platform and Granite models offer a robust foundation for innovation. With a focus on trust, transparency, and ethical AI, IBM is well-positioned to help organizations navigate the complexities of this transformative technology.

The Generative AI Summit series from the AI Accelerator Institute provides a platform for thought leaders like Manav to share their vision for the future of AI.

[rajaniesh]

From Data to Decisions: Empowering Teams with Databricks AI/BI

🚀 Unlock the Power of Data with Databricks AI/BI! 🚀 Imagine a world where your entire team can access data insights in real-time, without needing to be data experts. Databricks AI/BI is making this possible with powerful features like conversational AI

In today’s business world, data is abundant—coming from sources like customer interactions, sales metrics, and supply chain information. Yet many organizations still struggle to transform this data into actionable insights. Teams often face siloed systems, complex analytics processes, and delays that hinder timely, data-driven decisions. Databricks AI/BI was designed with these challenges in…

[nando161mando]

"Race science group say they accessed sensitive UK health data" https://theguardian.com/world/2024/oct/17/race-science-group-say-they-accessed-sensitive-uk-health-data

In 'Resisting AI' I specifically warned about UK Biobank, genome-wide association studies and the emergence of AI-driven eugenics.

[spearsbrandonbooks]

Check out my October 2, 2024 Blog Post:

Artificial Intelligence and Its Impact on Society

In the ever-evolving landscape of technology, one of the most significant advances of our time is artificial intelligence (AI). While AI has undeniably sparked excitement and curiosity, it has also incited fear—much of which is rooted in fantasy and a resistance to change. This fear of AI is not new. Society has always been wary of technological innovations, but these anxieties are often based on misunderstandings and historical precedents that show resistance to change more than the innovation itself.

Consider the reactions to past technologies: the introduction of motorized cars decimated the horse-drawn carriage industry, and the spread of books sparked concerns about information overload. Radio, television, computers, and the internet all faced similar scrutiny. Yet, in each case, society adapted, jobs evolved, and new industries emerged. AI, like its predecessors, will disrupt industries and require adjustments, but it also holds the promise of unlocking new opportunities and societal advancements.

To read the complete blog, please visit my website:

Check out further details in my book, The Evolution of Intelligence: The Interplay Between Human and Artificial Minds, available for FREE on Kindle Friday, October 4, 2024.

[code-of-conflict]

Ethical Dilemmas in AI Warfare: A Case for Regulation

Introduction: The Ethical Quandaries of AI in Warfare

As artificial intelligence (AI) continues to evolve, its application in warfare presents unprecedented ethical dilemmas. The use of AI-driven autonomous weapon systems (AWS) and other military AI technologies blurs the line between human control and machine decision-making. This raises concerns about accountability, the distinction between combatants and civilians, and compliance with international humanitarian laws (IHL). In response, several international efforts are underway to regulate AI in warfare, yet nations like India and China exhibit different approaches to AI governance in military contexts.

International Efforts to Regulate AI in Conflict

Global bodies, such as the United Nations, have initiated discussions around the development and regulation of Lethal Autonomous Weapon Systems (LAWS). The Convention on Certain Conventional Weapons (CCW), which focuses on banning inhumane and indiscriminate weapons, has seen significant debate over LAWS​. However, despite growing concern, no binding agreement has been reached on the use of autonomous weapons. While many nations push for "meaningful human control" over AI systems in warfare, there remains a lack of consensus on how to implement such controls effectively​.

The ethical concerns of deploying AI in warfare revolve around three main principles: the ability of machines to distinguish between combatants and civilians (Principle of Distinction), proportionality in attacks, and accountability for violations of IHL. Without clear regulations, these ethical dilemmas remain unresolved, posing risks to both human rights and global security.

India and China’s Positions on International AI Governance

India’s Approach: Ethical and Inclusive AI

India has advocated for responsible AI development, stressing the need for ethical frameworks that prioritize human rights and international norms. As a founding member of the Global Partnership on Artificial Intelligence (GPAI), India has aligned itself with nations that promote responsible AI grounded in transparency, diversity, and inclusivity​. India's stance in international forums has been cautious, emphasizing the need for human control in military AI applications and adherence to international laws like the Geneva Conventions. India’s approach aims to balance AI development with a focus on protecting individual privacy and upholding ethical standards.

However, India’s military applications of AI are still in the early stages of development, and while India participates in the dialogue on LAWS, it has not committed to a clear regulatory framework for AI in warfare. India's involvement in global governance forums like the GPAI reflects its intent to play an active role in shaping international standards, yet its domestic capabilities and AI readiness in the defense sector need further strengthening​.

China’s Approach: AI for Strategic Dominance

In contrast, China’s AI strategy is driven by its pursuit of global dominance in technology and military power. China's "New Generation Artificial Intelligence Development Plan" (2017) explicitly calls for integrating AI across all sectors, including the military​. This includes the development of autonomous systems that enhance China's military capabilities in surveillance, cyber warfare, and autonomous weapons. China's approach to AI governance emphasizes national security and technological leadership, with significant state investment in AI research, especially in defense.

While China participates in international AI discussions, it has been more reluctant to commit to restrictive regulations on LAWS. China's participation in forums like the ISO/IEC Joint Technical Committee for AI standards reveals its intent to influence international AI governance in ways that align with its strategic interests​. China's reluctance to adopt stringent ethical constraints on military AI reflects its broader ambitions of using AI to achieve technological superiority, even if it means bypassing some of the ethical concerns raised by other nations.

The Need for Global AI Regulations in Warfare

The divergence between India and China’s positions underscores the complexities of establishing a universal framework for AI governance in military contexts. While India pushes for ethical AI, China's approach highlights the tension between technological advancement and ethical oversight. The risk of unregulated AI in warfare lies in the potential for escalation, as autonomous systems can make decisions faster than humans, increasing the risk of unintended conflicts.

International efforts, such as the CCW discussions, must reconcile these differing national interests while prioritizing global security. A comprehensive regulatory framework that ensures meaningful human control over AI systems, transparency in decision-making, and accountability for violations of international laws is essential to mitigate the ethical risks posed by military AI​.

Conclusion

The ethical dilemmas surrounding AI in warfare are vast, ranging from concerns about human accountability to the potential for indiscriminate violence. India’s cautious and ethical approach contrasts sharply with China’s strategic, technology-driven ambitions. The global community must work towards creating binding regulations that reflect both the ethical considerations and the realities of AI-driven military advancements. Only through comprehensive international cooperation can the risks of AI warfare be effectively managed and minimized.

[goodoldbandit]

Multi-Cloud vs. Hybrid Cloud: Strategic Decision-Making for Leaders.

Sanjay Kumar Mohindroo Sanjay Kumar Mohindroo. skm.stayingalive.in Explore the strategic difference between multi-cloud and hybrid cloud with expert insights for CIOs, CTOs, and digital transformation leaders. A Cloud Crossroads for the Modern Leader Imagine this: you’re in the boardroom. The CIO looks up after a vendor pitch and asks, “Should we go multi-cloud or hybrid?” Everyone turns to…

[zomb13s]

The Complex and Unconventional Journey of Alfons Scholing: A Reflective Analysis

Introduction The life of Alfons Scholing, CEO of alfons.design and creator of the artist platform ikziezombies.com, offers an intricate narrative that defies the typical happy success story. His journey, particularly marked by his attempt to secure the position of vice president of the council of state of the royal household of the Netherlands, is one shaped by deep reflections on life,…

[tagbintech]

AI in Corporate Governance 2025: Transforming Decision-Making and Compliance

Introduction

Artificial Intelligence (AI) is revolutionizing corporate governance, enhancing decision-making, risk management, and compliance processes. As we step into 2025, AI's role in governance continues to evolve, driving efficiency and transparency in corporate structures. AI in corporate governance 2025 is not just a trend but a necessity, helping organizations navigate regulatory complexities and optimize operations.

The Role of AI in Corporate Governance

AI is increasingly integrated into governance frameworks to improve compliance, mitigate risks, and enhance decision-making. The key areas where AI is making a significant impact include:

1. Automating Compliance and Risk Management

Regulatory requirements are constantly evolving, making compliance a challenging task for businesses. AI-driven systems can:

Monitor regulatory changes in real time

Automate compliance reporting

Identify potential risks and suggest mitigation strategies

2. Enhanced Decision-Making with AI-Powered Analytics

AI-driven analytics offer insights based on data patterns, enabling executives to make informed decisions. Companies leverage AI to:

Analyze financial reports for anomalies

Predict market trends

Optimize resource allocation

3. AI in Ethical Corporate Practices

Ethical governance is a top priority in 2025. AI helps in:

Detecting fraudulent activities

Monitoring ethical compliance

Ensuring fair decision-making practices

4. Cybersecurity and Data Protection

With increasing cyber threats, AI is crucial for corporate cybersecurity. AI-powered solutions help in:

Identifying potential security breaches

Preventing data leaks

Ensuring compliance with data protection laws

5. AI-Driven Boardroom Decision-Making

Boardrooms now use AI tools to enhance decision-making by:

Providing real-time data insights

Reducing human biases

Automating meeting minutes and key action items

Benefits of AI in Corporate Governance

Improved Compliance Efficiency: AI reduces the burden of regulatory compliance by automating tasks.

Better Risk Management: AI predicts potential risks before they become critical issues.

Faster and Data-Driven Decisions: AI helps executives make well-informed decisions.

Stronger Cybersecurity Measures: AI safeguards corporate data from cyber threats.

Enhanced Transparency: AI improves accountability in governance processes.

Challenges in Implementing AI for Corporate Governance

Despite its advantages, AI adoption in governance faces challenges such as:

Data Privacy Concerns: Organizations must ensure AI compliance with privacy laws.

Bias in AI Algorithms: AI must be trained on diverse datasets to prevent biased decision-making.

Integration Complexity: Implementing AI requires significant investment and expertise.

The Future of AI in Corporate Governance

As AI continues to evolve, the future of corporate governance will see:

Increased use of AI-powered chatbots for compliance queries

AI-driven predictive governance models

Enhanced blockchain integration for transparent governance

Conclusion

AI in corporate governance 2025 is reshaping how businesses operate, ensuring compliance, enhancing risk management, and improving decision-making processes. While challenges exist, the benefits far outweigh the risks, making AI an indispensable tool for modern corporate governance.