Staying Ahead of The CURVE with AI -Artificial Intelligence Cybersecurity and Business Perspective 2024-2025
Staying Ahead of The CURVE with AI Evolution trajectory- Cybersecurity and Business Perspective. [ A.I For The Future and Beyond- Top 1%]
Today, Artificial Intelligence is undeniably a key disruptor in the new digital age. It cuts through the fibre optics of vertical and horizontal economies, services, and the digital product supply chain. Critical operations in industries such as healthcare (i.e. neurotechnology), geology, energy, commerce, Life Science, manufacturing, government, law enforcement, insurance, agriculture, education, finance, military, technology, tourism, and entertainment are increasingly enhanced by AI-integrated capabilities across workflows. These advancements are expected to influence business efficiency, productivity, and ROI by reducing or eliminating human dependency, thus optimizing and augmenting the workforce. This transformation is driven by AI/ML-powered data, compute, networking, storage and energy infrastructure, capable of generating intelligent Algorithmic token used to enable productivity and creativity while shaping our social choices and power to access smarter decision-making AI Systems Tools thus democratizing AI Capabilities.
In advanced economies, about 60 percent of jobs are exposed to AI, due to prevalence of cognitive-task-oriented jobs. Almost 40 percent of global employment is exposed to AI, with advanced economies at greater risk but also better poised to exploit AI benefits than emerging market and developing economies.(International Monetary Fund on report Gen-AI: Artificial Intelligence and the Future of Work , JAN 2024).
Cognitive-task-oriented jobs
“No job, No function will remain untouched by AI,” - SP Singh, senior vice president and global head, enterprise application integration and services at Infosys, in a report on A playbook for crafting AI strategy by MIT Technology Review Insights (2024).
As many operations, processes, and tasks can be automated, AI technologies and innovative tools advancement, offer an opportunity to transform operations and scale solutions across various sectors at massive length. Despite the transformative potential of AI, uncertainties surrounding Ethical principles, Geopolitical power shifts, and Technology Polarization and weaponization.
Other overlapping concerns are Data Privacy, Quality, Lag issues, Poisoning, security and Scraping, Deepfakes, disinformation, Intellectual Property and copyrights High-tech Plagiarism, Harmful Bias or Homogenization, Confabulation or Hallucination, Cognitive threat, superhuman persuasion and Manipulation- etc. which according to NIST RMF 100-1 publication can cause harm to People (civil rights, jobs, psychological safety), Organization (business operations) and to an Entire Ecosystem(supply chain, global financial system, environmental).
What is AI?
"Ai is simply getting computers to do tasks that require human intelligence and more".....
AI is the over-arching technology
Jean-Michel Basquiat Untitled 1981(Untitled)
AI is the over-arching technology of which Machine Learning is a core approach that is enabled by Deep Neural Networks (DNNs).. - (The Executive guide to Artificial Intelligence- How to identify and implement application for AI in your Organization -Andrew Burgess )
ML-Machine learning is a subset of AI that creates algorithms to learn from data, including supervised(data is labeled), semi-supervised, unsupervised(all data is unlabeled)- (unsupervised problems are grouped into clustering and association problems where k-means clustering), and reinforcement learning. It primarily relies on statistical and computational methods. (detect and extrapolate patterns).
NN-Neural Networks are computational models that mimic the brain to learn from data and make predictions. (artificial networks of neuron). best for handling noisy data.
DL -Deep Learning class of machine learning techniques in which artificial neural networks adapt and learn from vast amounts of data. Deep Learning is simply the tight coupling between hardware and state of the art in machine learning. (3Layers Input, hidden and output Layer)Deep learning helps recognize, classify and categorize patterns in data for a machine.
GenAI -Generative AI is a type of machine learning that focuses on creating new data. it relies on LLMs for user tasks.
LLM- Large Language are AI models that process and generate human-like text, images, video, and audio.
RL - Reinforcement Learning type of machine learning where machines learn to achieve goals through trial, error, and rewards. (applicability in game playing and finance).
DNN- Deep Neural Networks also embodies Convolutional Neural Networks (CNNs) Recurrent Neural Networks (RNNs), Deep Reinforcement Learning (DRL) as DNN encodes raw data into a hierarchy of abstracted feature representations.
Natural Language Processing (NLP): NLP enables software to comprehend and process human language.
Retrieval-augmented generation (RAG)- connects the model to an external knowledge base and retrieves relevant documents at runtime to ground its responses.
Other key component or concept in the AI technology includes ANN, (GAN)Generative Adversarial Networks, Convolutional neural network (CNN), recurrent neural networks (RNNs), extreme learning, Adversarial machine learning (AML), machines (ELMs) and capsule networks (CapsNets), Large Agentic Models (LAM), cache-augmented generation (CAG), Multi-Layer Perceptron (MLP), Responsible AI (RAI), Trustworthy AI, VibeCoding, Physical AI, AI Employee etc.
Two main classes of AI identified by (Nist 100-2e2025)
Predictive AI (PredAI): used in computer vision as well as industrial applications
Generative AI (GenAI)- used in integral part of software applications and internet infrastructure. business and consumer contexts.
Three Types of AI Capabilities
Automating structured and repetitive work processes (Robotic process automation-RPA)
Gaining insight through extensive analysis of structured data(Traditional Ai, GenAI)
Engaging with customers and employees, using natural language processing (intelligent agent- chatbot i.e voice and human-looking avatars)
The Organization for Economic Cooperation and Development (OECD) highlighted The nine indicators of AI Capability which covers a range of human abilities that each describes the development of AI towards full human equivalence: Language; Social interaction; Problem solving; Creativity; Metacognition and critical thinking; Knowledge, learning and memory; Vision; Manipulation; and Robotic intelligence. (Introducing the OECD AI Capability indicators 2025)
other capabilities include Research and Development, Computer vision, capturing information, image recognition, speech recognition, clustering through customer buying-behavior data, semantic computing, Chemical, Biological, Radiological or Nuclear (CBRN) information access capabilities, learning and interaction with other systems, AI-assisted autonomous offensive cyber operations (OCO)...etc.
Creating the AI support structure To ensure your organization adopts AI smoothly, consider how AI will change the way your people and processes work. (Artificial Intelligence Playbook for the UK Government Feb 2025)
AI use Case in Finance: J.P. Morgan successfully used synthetic data for fraud detection model training. AI models were provided with samples of normal and fraudulent transactions to understand the tell-tale signs of suspicious transactions. (Privacy Enhancing Technology (PET) proposed guide on Synthetic Data Generation PDPC Personal Data Protection Commission Singapore,2024)
Labor Shortage + AI Catalyst =Productivity
AI might be Human's biggest Existential threat nevertheless AI does not undermine Aristotle's vitalism theory.
The World Health Organization (WHO) estimates a deficit of 10 million health workers by 2030, particularly in low- and middle-income countries (LMICs). WEF Global Risk Report 2025.
For the first time.– Two demographic shifts are increasingly seen to be transforming global economies and Labour markets: Aging and declining working-age populations. (World Economic Forum WEF 2025 Future of Jobs Report’s - list of top 10 fastest growing skills ).
Globally, the number of people aged 65 and older is expected to increase by 36%, from 857 million in 2025 to 1.2 billion in 2035- WEF Global Risk
Research from the International Labor Office (ILO) suggests that a maximum of 2.3% of global jobs could be fully automated, but this does not account for the new jobs created by this technology (AI for Good Impact Report by International Telecommunication Union and Deloitte 2024)
Future Risks such as Pension crises, consumer gap, insufficient public infrastructure, social protection, private credit, up-skilling and training, retiring population and retirement age, immigration, birthrate as well as extreme weather events(flood, heatwave, wildfires etc), natural resources shortage(i.e. weaponization of food, water etc) are other key factors propelling AI Cognitive and Engineering innovative Labour capabilities into The Era of Intelligent Systems which will drive 4th Industrial Revolution focused on technology-driven automation, smart and intelligent systems, where neural networks and genetic algorithms will provide all the answers with minimal effort.
Globally, one in four workers are in an occupation with some GenAI exposure. 3.3% of global employment falls into the highest exposure category, albeit with significant differences between female (4.7%) and male employment (2.4%). - (Working Paper on Generative AI and Jobs A Refined Global Index of Occupational Exposure by International Labour Organization ILO, 2025)
According to the 2024 Digital Economy and Society Index (DESI), around 45 % of the EU population (between 16 and 74 years old) does not have basic digital skills, let alone AI skills.(EPRS | European Parliamentary Research Service - Lucia Vesnic-Alujevic with Georgios Saitis; Graphics: Samy Chahri Policy Foresight Unit PE 765.806 – June 2025)
Baseline: AI value alignment is essential to ensure that AI systems behave in ways consistent with human values, ethical principles and societal norms. (Executive Summary AI Value Alignment: Guiding Artificial Intelligence Towards Shared Human Goals Global Future Councils WEF 2024 Whitepaper)
62% of AI's value lies in core business functions Evaluating and prioritizing your AI use case opportunities in this way helps accelerate the big wins that create further interest and investment(Identifying and Scaling use cases AI by Open AI 2025)
AI in transportation: Next-Generation Robotaxi Platform Unveiled, Robotaxi on Uber App - as (AI) plays a pivotal role in the development and operation of autonomous vehicles (AVs), enabling them to perceive their surroundings, make decisions, and navigate safely without human intervention. Waymo, Coco, Baidu are autonomous self-driving cars.
Aramco uses AI-driven predictive analytics and automation to optimize supply chain operations and monitor forecast flare emissions, reducing environmental impact and enhancing operational efficiency (Aramco, 2024).
One of the bottlenecks is Becoming Over-Dependent on AI transport systems for mobility which could AI could impact Transportation and Logistics Serverly when disrupted nevertheless, AI applications are becoming more and more ubiquitous, as Autonomous ride-hailing could reduce traffic accidents by 80% by 2030.
The G7 policymakers established 3 AI-related indices to identify three key conduits that link AI-related actions and improved productivity outcomes: technological capabilities; Applications and markets; and Policy and regulation. (Special Report on AI-Driven Productivity Scenarios for G7 the G7 Finance Ministers and Central Bank Governors’ Meeting under the Canadian G7 Presidency, May 2025, Banff, Alberta).
AI Advantage and Value(ROI) in The AI Economy
The exponential growth in AI Software, Hardware and AI Adoption Across will impact GDP growth, governments and revenues, However Human-centric Ethics, mutual Trust and Transparency should be the Core of ROI.
Traditional ROI Formula: ROI = (Net Profit / Cost of Investment) × 100%
Strategic Objectives for rapid innovation or market gain can be short-term or long-term. However, AI ROI takes into account different factors for determining its return on investment. (The ROI of AI Ethics: Profiting with Principles for the Future- ROI Concepts and Models by The Digital Economist Position Paper Marisa Zalabak, Balaji Dhamodharan, et al 2025)
Source: International Data Center Authority (IDCA) Global Airtificial Intelligence Report 2025
IBM Research: Findings indicate that organizations with a strategic approach to AI ethics can achieve an average ROI of approximately 13 percent, compared to 5.9 percent for those without a cohesive strategy (AICadium).
In January 2025, a complaint unsealed in the Eastern District of Virginia revealed that Microsoft’s Digital Crimes Unit observed that an international threat–actor group had developed sophisticated software to exploit exposed customer credentials scraped from public websites (MICROSOFT The 2025 Responsible AI Transparency Report)
The architecture of the New Economy and its new ecosystem is changing AI-powered narrative as AI is becoming a cooperate priority in innovation "Amy Downey, co-head of Global Payments & Liquidity (GPL), described how Wells Fargo is working with AI to modernize and personalize its GPL platform to make the experience more intuitive for clients. (5 key insights from Corporate Priorities in a New Market & Regulatory Environment June 12, 2025, New York, NY).
A single AI data center can cost between $40 billion to about $500 billion
Countries like Taiwan, India, Japan, and Singapore are scaling AI-ready data centers, while the U.S., China, Canada, UAE, Saudi Arabia, and the EU lead in capacity and infrastructure. This concentration exposes widening gaps in global AI readiness
Data residency and sovereignty pivot on geolocation. For example, AWS uses isolated partitions ‘aws’ (global), ‘aws-cn’ (China), requires a Chinese Internet Content Provider (ICP) license or recordal from local authorities before deployment, to ensure data residency and sovereignty by keeping data within legal jurisdictions (Source: AWS Prescriptive)
The Surge in AI adoption is driven by tangible benefits generative AI offers, Including a 7.8% improvement in Productivity and a 6.7% enhancement in Customer engagement and satisfaction.(The Blueprint to scaling AI for Business transformation - Transition from Pilot to Production2025/Harnessing the value of genAI; 2ND Edition; MARK OAST VP GenAI Global Lead)-Capgemini
The global AI market was valued at $279.22 billion in 2024 and is projected to grow at a CAGR of 35.9% from 2025 to 2030. (KMPG 2025 Future Seizing opportunities in an era of disruption)
Cursor AI: $100M ARR in 12months with 20 employees and Lovable: $10 ARR in 2months with 15 employees- (AI First Companies Win the Future Presentation Report by BCG 2025)
Canada pledged $2.4 billion, China launched a $47.5 billion semiconductor fund, France committed €109 billion, India pledged $1.25 billion, and Saudi Arabia’s Project Transcendence represents a $100 billion initiative - (Artificial Intelligence Index Report 2025 HIA Stanford University Human-Centered Artificial Intelligence)
India’s national AI initiative underscores that robust computational infrastructure is foundational to AI innovation, allocating a ₹10,371.92 crore (USD 1.38 billion) budget to expand access and capacity in computing resources ( Global trends in AI governance: Evolving country approaches. World Bank 2025.)
3 core dimensions of return using ISACA's AI ROI Model identifies measurable ROI through direct cost savings and revenue gains, strategic ROI by supporting long-term goals like digital transformation, and capability ROI by enhancing AI maturity through workforce upskilling and cultural readiness Carmichael, M. (2025, March 3). Demonstrating AI ROI: How to Measure and Prove the Value of Your AI Investments.
Medical/Bioinformatics
QVIA and NVIDIA are deploying AI agents trained on multimodal clinical and commercial data to automate complex life sciences workflows, enhancing efficiency in drug development and patient care. These agents use NVIDIA AI Foundry to extract insights from previously inaccessible data, accelerating time-to-market for new treatments.
With AI the Cognitive advantage in healthcare areas that require medical diagnosis protein engineering, and treatment as it learns vast amount of medical and scientific research published. which result-in higher cure rates and best care in remote locations.
AI's applications in biotech ehances, drug discovery reaction prediction, and protein engineering. It also delves into AI's role in diagnosis, treatment, and personalized medicine, this approach holds promise for predicting treatment outcomes, identifying health risks, and enabling proactive interventions.
Medical dataset search techniques are used in AI to find a sequence of steps that will get us from some initial state to some goal state(s). AI Health systems use Federated Learning to avoid sharing sensitive data (e.g. patient medical data) with third parties
A Simple Bayesian Network.
Other methods, such as Monte Carlo simulations, Gaussian processes, gradient descent, and evolutionary algorithms, can also be employed to derive solutions.
The quality, depth, and diversity of these datasets directly impact the performance and fairness of AI models as well as mathematical methods and models (like neural networks, decision trees, etc.) that process and learns from data.
AI models built on healthcare data are only as useful as their alignment with clinical reality. (Medical Datasets for AI Research - Fuel Your Medical AI Projects with the Best Data- Health innovation TOOLBOX - Vol 01, June 2025)
62% of AI's value lies in core business functions Evaluating and prioritizing your AI use case opportunities in this way helps accelerate the big wins that create further interest and investment(Identifying and Scaling use cases AI - OpenAI. (2025, April). Identifying and Scaling AI Use Cases.
AI unlocks powerful opportunities for people with disabilities, but true inclusion demands more than technology alone.
AI GuardRails - Governance, Ethics and Laws
AI Governance is key to organizations with transparency and accountability.
Accountability cannot be transferred to machines- Human decision-making is central to legal accountability for the use of AI-enabled Autonoum Weapon System. .( ‘Proceed with Caution: Artificial Intelligence in Weapon Systems’ The Government Response to the Report by the House of Lords Ai in Weapon Systems Committee Session 2023/24 HL PAPER 16)
AI-enabled NGCV that rapidly learn, adapt, reason and act in complex environments addressing CSA Priorities: (i) Next Gen Combat Vehicles (primary) and (ii) Networks/C3I (secondary).(NATO -Prevailing in a Complex World: ARL’s Essential Research Area on AI & ML)
The rapid deployment of AI shouldn't be about playing catch-up as neglecting the Ethics, Safety and Security across Ai Lifecycle. hence safety, security and trustworthiness must be put into consideration at every stage of AI lifecycle - design, development, use and evaluation of AI products, services, and systems- (NIST 600-1 AI RMF Generative AI Profile)
Emerging technologies, such as artificial intelligence, accelerate crime and provide criminal networks with entirely new capabilities.(The Changing DNA of Serious and Organised Crime 2025 European Union -EUROPOL)
AI systems must comply with existing laws, including federal and state civil rights protections, data protection and privacy laws, as well as consumer protection regulations, as outlined in the Responsible Deployment of AI Systems Act, House Bill 1916, 1st Session of the 60th Oklahoma Legislature (2025) (Alonso-Sandoval).
The Matryoshka Campaign, revealed in VIGINUM’s 2024 report24, illustrates the sophistication of modern disinformation tactics as well as VIGINUM’s operating model. As VIGINUM reports, this Russian-led operation deployed “seeders” to introduce false narratives and “quoters” to amplify them, creating the illusion of organic discourse (SAFEGUARDING ELECTIONS IN THE AGE OF AI AND SYNTHETIC CONTENT: A FRAMEWORK FOR ELECTORAL INTEGRITY INSTITUTIONS FEBRUARY 2025 The Institutional Architecture Lab)
The fusion of AI and biometrics can enhance criminal identification accuracy while protecting the privacy of nonrelevant individuals(AI and policing The benefits and challenges of artificial intelligence for law enforcement Europol 2025).
Hence framework and Methodology formulated and used by both public and private actors should be positioned and comply to aid identifying and addressing risks and impacts to human rights, democracy, and the rule of law throughout the lifecycle of AI systems. (i.e. The HUDERIA)
AI ECOSYSTEM
Inference compute
energy compute
network compute
Data infrastructure
Storage compute
Security infrastructure
AI regulatory, AI policymakers, AI stakeholders, AI Users, AI Developers, AI communities (consulting, academia & research), data providers, incubators etc.
EDGE AI ECOSYSTEM
Source: THE 2025 EDGE AI TECHNOLOGY REPORT, The guide to understanding the current state of the art in hardware & software for Edge AI Edge AI Foundation Los Altos, CA
AI Ecosystem encompasses many entities across verticals (AI industries, AI Tutors etc) and can be redefined by governments, AI developers, AI innovation landscape. etc
Australia’s 2025 AI Ecosystem Report identifies three core components: AI-active public and private companies, research and patent activity, and growing demand for AI-related jobs and skills across the economy(Australia’s Artificial intelligence ecosystem report -National Artificial Intelligence Centre NAIC 2025)
The German AI landscape is anchored by the German Research Centre for AI (DFKI), while Denmark has established the Danish AI Ecosystem (DARNISH AI). Luxembourg and France have launched their national AI strategies, complemented by the broader Pan-European and Pan-Canadian Artificial Intelligence Strategies. These initiatives foster an environment ripe for innovation, extending into advanced domains such as space and Earth system science. Notably, projects like the Artificial Intelligence/Integrated Forecasting System (AIFS), the Advanced Land Observing Satellite (ALOS), and Adaptive Network-Based Fuzzy Inference System (ANFIS) exemplify the expansive scope of AI’s geopolitical influence across scientific frontiers.
A Nanjing University of Aeronautics and Astronautics team published a study that alleges 99 Chinese satellites could disrupt 1,400 Starlink satellites within a 12-hour period, targeting not individual satellites, but large sections of the Starlink constellation. (Space Threat Assessment 2025 Clayton Swope, Kari A. et all CSIS -CENTER for Stategic and international studies)
There is no AI [artificial intelligence] journey without a data journey, and there is no data journey without a cloud journey. Duncan Eadie, managing director of cloud-first and infrastructure engineering for Asia Pacific, Accenture plc (Navigating the Generative AI Landscape Global Strategies for Implementation and Scaling HARVARD BUSINESS REVIEW 2025)
EXISTING AI Regulatories
UK Data (Use and Access)Act 2025
GDPR EU
EUDPR India
HIPPA
FTC Act
National A.i initiative Act of 2020
EU AI ACT 2022
CHIP ACT 2020
Telecom ACT
UK AI ACT
African Commission on Human and Peoples’ Rights (ACHPR) 437
Digital Charter Implementation Act (Bill C-27) Canada
the Artificial Intelligence & Data Act (AIDA). Canada
GENIUS Act Guiding and Establishing National Innovation for U.S. Stablecoins of 2025
Defense Production Act (DPA) US
Treat data privacy and differences in regional regulation seriously; While concerns about risks, security, and data privacy are all over the map, some industries and regions face more stringent regulation than others do. (Harvard Business Review Analytic Services. (2024). Navigating the generative AI landscape: Global strategies for implementation and scaling. Sponsored by Red Hat.)
Canada's Bill C-4 reaffirms a national, uniform, and exclusive framework governing how federal political parties handle personal information-ensuring a standardized approach to data collection, use, and disclosure across Canada.” (Canada Elections Act, s. 446.2) While framed as modernization, it risks might eroding democratic trust
GEO-Political Quest for AI Supremacy - Global worldview
ALL Road Leads to StarGate- The Largest AI investment in History!!
The multipolarity of Ai's Hegemoney approach reiterates the need for safety hence The US Executive Order on the Safe, Secure, and Trustworthy Development and Use of Artificial Intelligence emphasizes critical measures for AI safety, including risk management, robust cybersecurity protocols, transparency, fairness, and international collaboration (The White House, Oct 2023), which was recently removed and revoked, Aggressively shifted its AI policy landscape. On January 23, 2025, Executive Order 14179, Removing Barriers to American Leadership in Artificial Intelligence, Instead, EO 14179 calls for an AI ecosystem “free from ideological bias or engineered social agendas,” aiming to reassert U.S. global AI dominance. accelerating data center development, clean energy supply, and domestic chip sourcing further signaling a pivot toward AI as strategic infrastructure. (Source Whitehouse.gov)
AI Factory Integrated to Data centre will produces intelligent Tokens - Nnvidia Juen GTC Paris Keynote at VivaTech 2025
Stargate, proposed as one of the largest AI-dedicated data centers globally, is set to launch in Abilene, Texas. Owned by OpenAI, SoftBank Group, Oracle Corporation, and MGX, the project is estimated to cost between $500 billion and $1 trillion, with completion expected by mid-2026. The facility will require around 1.2 gigawatts of power, advanced water-based cooling systems, and house nearly 400,000 high-performance GPUs and CPUs. Designed to support cutting-edge AI research and large-scale model training, Stargate aims to significantly expand the computational infrastructure powering the AI revolution.
DOE & AI for Energy The U.S. Department of Energy’s AI for Energy (April 2024) initiative highlighted key frameworks for leveraging AI across mission areas such as power grid optimization, energy materials discovery, nuclear energy safety, and carbon management. The DOE categorized AI use cases into three severity tiers: High Consequence, Urgency, and Complexity, reinforcing the need for resilient, cross-disciplinary systems to uphold AI supremacy in national energy resilience.
Nvidia, Cisco, and OpenAI have announced plans to collaborate on building the "UAE Stargate," a next-generation artificial intelligence data center set to launch in the United Arab Emirates by 2026.
Water plays a large part in the making and operations for efficient Datacenter, as Techniques and algorithms applied in water management ANN-vision models or large-scale transformer models for weather predictions, AI in water management, Narrow AI such as a model that is able to reproduce the connections between rainfall, evapotranspiration, and infiltration to generate water level estimates in a river and because of water’s essential role in ecosystems, energy production, and human needs UNesco Water management - however there is a large variety of complex examples, from full (AI techniques for water management UNESCO /Deltares 2025 Report on Application of AI water management(Artificial Intelligence as a tool for leveraging sustainable water resources management)
Image Source: AI techniques for water management UNESCO /Deltares 2025 Report on Application of AI water management(Artificial Intelligence as a tool, for leveraging sustainable water resources management)
Pan-Canadian AI Strategy focuses on Developing an Artificial intelligence Strategy for the Government of Canada (DDN3-39) it positions to Drive the adoption of AI across Canada's Economy and Society the Strategy focuses on 3 Pillars Commercialization, Standards and Talent and Research
Canada’s AI investment exceeds CAD 2.5 billion, including CAD 443.8 million under Phase II of the Pan-Canadian AI Strategy and CAD 2 billion for the 2024 AI Compute Access Fund and Sovereign Compute Strategy. Core funding includes CAD 60 million for Amii, Mila, and Vector Institutes, CAD 160 million for talent (via CIFAR), and CAD 125 million for innovation clusters. These investments target AI research, talent retention, compute access, and global competitiveness.
June 17, 2025 Kananaskis statement, G7 leaders committed to “human-centric,” secure AI by launching the GovAI Grand Challenge and a shared AI Adoption Roadmap focused on SMEs, energy, data trust, and digital inclusion -(G7 Leaders. (2025, June 17). G7 Leaders’ Statement on AI for Prosperity. Government of Canada.)
Paris AI Summit 2025 France and India co-led a declaration signed by 58+ countries to promote inclusive, sustainable, and human‑centred AI, focusing on transparency, ethical standards, and global cooperation
The EU’s 2025 Pan-European AI Action Plan allocates €200 billion for AI development, including €20 billion to fund up to 5 AI gigafactories and 13 AI factories supporting startups, industry, and research (European Commission, 2025).
“WE WANT THE UAE TO BECOME THE WORLD’S MOST PREPARED COUNTRY FOR ARTIFICIAL INTELLIGENCE.” His Highness Sheikh Mohammed bin Rashid Al Maktoum UAE Vice President and Prime Minister and Ruler of Dubai (UAE NATIONAL STRATEGY FOR ARTIFICIAL INTELLIGENCE 2031)
Threat Actors like SweetSpecter, CyberAv3ngers, STORM-0817 where identified According to OpenAI Oct 2024 Influence and cyber operations- The unique insights that AI companies have into threat actors can help to strengthen the defenses of the broader information ecosystem.
Controvesy surounding on the sale of the most advanced Nvidia chips to China in October 2022. But Nvidia has responded by designing new semiconductors for the Chinese market - including those DeepSeek likely used to build its R1 artificial intelligence model. | REUTERS
Africa’s Continental AI Strategy, endorsed by the AU in July 2024, sets a five-year roadmap to build sovereign AI ecosystems, develop ethical governance and data infrastructure, and support capacity-building for public and private sectors with UNESCO focal point to the AU AI Working Group.
ASEAN promotes AI for public good through regional cooperation, guided by Singapore’s Model AI Governance Framework for Generative AI, emphasizing trust, accountability, and innovation, with initiatives like AI Verify advancing shared ethical standards (IMDA, 2024).
Big Data, Cloud & Datacenters your Best BET!
The Quality of Data is Key to Clean, Correct, Consistent Data Assurance.. Hence ensuring appropriate data handling and responsible data processing practices is implemented on AI and Data Lifecircle thus creating A Responsible AI with data fidelity.
Model = Algorithm(Data) Brownlee, J. (2016–2018). Difference Between Algorithm and Model in Machine Learning.
Data is foundational to artificial intelligence, serving as the initial pipeline in the machine learning process. As the raw material AI learns from—be it text, images, numbers, or sensor input—data shapes outcomes. Algorithms, driven by people, process, philosophy, and performance, transform this data into actionable intelligence.
BIG DATA = MARKET VALUE + INTELLIGENCE EXTRACTS
The Four Pillars (Tetragrammaton) of AI Function: D - A - C - L (Data, Algorithms, Computing, Learning)
Computing Power The hardware and infrastructure (CPUs, GPUs, cloud servers, semi-conductor, microchip etc) enables processing of large datasets and complex models efficiently. AI improves its performance by extracting patterns from data.
NVIDIA GB200 Grace Blackwell Superchip, introduced at GTC 2024, is capable of delivering up to: 30 PFLOPS (petaflops) of AI performance, Designed to power massive LLMs, trillion-parameter models, and foundational AI infrastructure NVIDIA GTC 2024 Keynote – Jensen Huang
Do You Know Data is the most attacked surface;
Data the Life blood of Ai - enabling Information Assurance can limit Unethical use of LLM and Data provenance as Data as machine readable information Artificial intelligence uses data from multiple disciplines to design algorithms prediction and decision.
In 2024, GADM alone collected data covering over 8 million flights, 500,000 incidents, and $11 billion in maintenance costs. With artificial intelligence, each new piece of data or information collected carries even more potential to make flying even safer. (Global Aviation Data Management) International Air Transport Association Annual Review 2025
AI Not creating a new problem, its creating a new Data Source run a readiness assessment, Implement DSM- Data Security Management.
AI value alignment involves continuous integration of human principles throughout the AI development life cycle. this includes Healthcare(patient autonomy), Credit Scoring, Autonomous driving (AI Value Alignment: Guiding Artificial Intelligence Towards Shared Human Goals) World Economic Forum October 2024 White Paper.
The bottom line is if you can't trust Data don't build on it.
INNOVATE WITH AI- What's your AI Problem-Solving Strategy?
Cassandra More than AI human Assistance (Netflix)- IMAGE SOURCE collider-com)
AI -Understanding is the ability of a machine ability to have conscious awareness of what it is doing and thinking. Nevertheless, because ai operates based on programmed Rules and Data which might lack the inherent moral judgement that humans have Algorithmic transparency controls.
AI enroute to permanent Memory Capabilities reaching 80%–90% of their proficiency By 2030–2032, as AI systems will achieve recursive self-improvement, writing and optimizing their own code. - Ex Google Ceo Eric Schmidt Schmidt
Alan Turing’s paper, “Computing Machinery and Intelligence” published October 1950, was the first to ask this question and introduce the idea of the Imitation Game – aka the Turing Test.
Meta project that the majority of its code will be written by AI by 2026- FTC - FTCs' Caution on Ai Monopoly (ANTITRUST AND AI: FOUNDATIONAL PRINCIPLES MEET FOUNDATION MODELS JUNE 3, 2025 KEYNOTE ADDRESS AT THE US AI SUMMIT 2025 WASHINGTON, D.C)
eVTOL (electric Vertical Take-Off and Landing) aircraft leverage AI to optimize flight paths, reduce energy use by up to 30%, enable autonomous navigation, and streamline predictive maintenance - advancing aviation’s ESG goals of carbon-neutral growth and a 50% cut in CO₂ emissions by 2050. (i.e can also be used to curb wildfires)
True Nature of Intelligence in (Coginitive Science and Enginering)
Noam Chomsky...emphasize that “the human mind is not, like ChatGPT and its ilk, a lumbering statistical engine for pattern matching, gorging on hundreds of terabytes of data…” Instead, they argue, human cognition is "surprisingly efficient and even elegant," operating on minimal input and driven by explanatory logic rather than brute correlation (“Noam Chomsky: The False Promise of ChatGPT”Chomsky et al. (2023))
AI Evolution Stages
Narrow (ANI)- Artificial Narrow Intelligence they are very good at only one or a few closely related tasks specifically designed for a narrow use.
General (AGI) - Artificial General Intelligence good at a vast range of things, much more similar to human intelligence and not focused on specific tasks.
Super(ASI)- Artificial Super Intelligence able to learn independently at a very quick rate, and exponentially improve on their own without human intervention AI would be capable of vastly outperforming the best human brains in practically every field.
Alan Turing’s - Turing Test October 1950 , was the first to ask this question and introduce the idea of the Imitation Game – aka the Turing Test.
Agentic AI- AI agent automated entity that senses and responds to its environment and takes actions to achieve its goals.(iso/iec 22989:202E2) this AI Systems accomplish task on users behalf, it core core charasteristics allows it to act reliably and consistently, as it leverages LLM to mange workflow execution. 3 Core Component of Agent -highlighed by OPenAI Model,Tools and Intrustions.
Workflows: A sequence of steps that must be executed to meet the user's goal.
Agent2Agent (A2A): protocol addresses a critical challenge in the Al landscape by enabling different Al agents to communicate and collaborate effectively. uses JSON-RPC 2.0 over HTTP(S) for standardized communication, agent cards for capability discovery, and supports various interaction patterns including synchronous, streaming, and asynchronous push notifications.
Model Context Protocol (MCP) : connects the agent to its tool. MCP operates on a simple client-server architecture
other Proctol such as Agent Network Protocol (ANP) enables decentralized, trustless peer-to-peer agent interactions over open networks, and Agent Communication Protocol (ACP) supports centralized, session-aware agent workflows with structured message exchange
AI has entered its third wave – agentic AI – where agents can make decisions with minimal human oversight and execute complex tasks (The trajectory of AI technologies- Transforming consumer induries in the Age of AI Word Economic Forum White Paper 2025)
Physical AI refers to artificial intelligence systems embedded in hardware devices, such as robots, autonomous cars, and drones, which enable them to control and move physical objects or perform tasks involving physical movement in the real world.
Top Generative AI platforms driving productivity includes Anthropic, OpenAI, Manus, DeepMind, Google Notebook LLM, SCALE AI, and Perplexity. A well-defined strategy focusing on scaling these technologies is essential to unlock their full business potential and drive measurable productivity gains.
Looking ahead, digital identity, digital currency, quantum computing, blockchain etc, were highlighted are poised to reshape the technological landscape. i.e DeepMind’s AlphaGo exemplifies the power of reinforcement learning in AI research, underscoring the transformative potential of these innovations.
Cybersecurity with AI
Artificial intelligence (AI) can improve government's cyber security, but it can also help threat actors looking to interfere or undermine trust in our democratic system, immigration, and other critical infrastructure.
Hence the mitigating AI system vulnerability, is ensuring Confidentiality, Integrity and Availability of AI Systems, while implementing security methodologies and control thus creating a Responsible AI.
ENISA Report on-(cybersecurity OF AI and standardization 2024) identifies three dimensions ; cybersecurity of AI, AI to support cybersecurity, and malicious use of AI
ISC2 surveyed more than 1,000 cybersecurity practitioners to examine the impacts of AI on the work they do every day and how the technology could shape cyber operations in the future. A majority (82%) expect AI to improve job efficiency and half (56%) expect it to make some parts of their jobs obsolete. (SC². (2023). Cybersecurity Workforce Study 2023)
Ai in Cyber can be used to investigate, identify, report and remediate cyber threat using machine learning.- SOAR AI/ML, SOC AI
ENISA Captures several key Cyber areas such as identifying risk, analyzing, threat intelligence, detecting and prioritizing threats, Summarizing security data (NIS INVESTMENT 2024 ENISA)
Prompt injection and Prompt Leaking are particularly unique attack techniques against AI and LLM Systems (Japan AI Safety Institute sep. 2024 Japan AI Red-Teaming)
"It is evident that Artificial Intelligence has introduced new complexity to the threat landscape."
Aotearoa New Zealand’s growing connectivity of devices and networks, alongside the adoption of emerging technologies (such as artificial intelligence and machine learning), has made our domestic cyber landscape more complex, and our nation continues to experience cyber threats from an increasing number of sources.(Cyber Threat Report 2023/2024 NCSC- The National Cyber Security Centre).
The Cloud Security Alliance (CSA) has identified 12 critical threat categories for agentic AI systems, including authorization hijacking, goal manipulation, memory poisoning, and multi-agent exploitation. These threats highlight the complex security challenges posed by autonomous AI agents, necessitating advanced red teaming techniques and mitigation strategies (Cloud Security Alliance, 2025)
AI INSURANCE NOT CYBER INSURANCE: Cyber insurance creates a redundant solution for AI Risk nevertheless AI insurance is a stand-alone object that overlaps with cyber insurance.
The reason for the necessity of a hollistic portfolio model are the mutiple interdependencies of cyber lossess resulting i.e from common attack vectors of cyber actors or interconnedtedness of IT Systems as the resulting Portfolio-loss distribution is strongly influced by the dependecies between individual plicies and the policy port folio loss distribution needs.- (Cyber insurance – Models and methods and the use of AI - European Union Agency for Cybersecurity (ENISA)2024)
AI CYBER TOP RISKS
The NIST 600-1 sp AI Risk Management Framewok suggests how to manage AI risk by governing, mapping, measuring and managing.
AML- Adversarial machine Learning: adversarial manipulation of training data; the provision of adversarial inputs to adversely affect the performance of the AI system; and even malicious manipulations, modifications, or interactions with models to exfiltrate sensitive information from the model’s training data or to which the model has access
Predictive AI Attacks and Generative AI Attacks Taxonomy such as Availability Violations, Integrity Violations, Privacy Compromises, Supply Chain Attacks, Generative AI Attacks Taxonomy Data posioning etc (NIST Trustworthy and Responsible AI, NIST AI 100-2e2025.)
Risk of AI to Critical Infrastructure (such as Dams, Nuclear Reactor, Emergency Service, Transportation Systems)can be categories 1) Asst-Level Risk, 2) sector risk 3) systemic/cross-sector risk 4) Nationally Significant Risk- assess adverse impacts (Roles and Responsibilities Framework for Ai in Critical Infrastructure by US Dept of Homeland Security DHS 2024)
Fundamental rights impact assessments (FRIAs) are a requirement under Article 27 of the EU Artificial Intelligence Act (‘the AI Act’, ‘the Act’), and must be conducted in certain circumstances for high-risk AI systems- These Domains include Human Diginity, Freedom, Equality, Justices, Citizens rights and solidarity (Confederation of EU Data Protection organization)
Gartner identifies critical pillars essential for AI success: AI Strategy, AI Values, AI Organization, AI People and Culture, AI Governance, AI Engineers and Data, and AI Maturity and Roadmap.(AI Strategy and governance framework: Keys to AI excellence. Gartner Research 2024)
Recommedation: Careful setup and configuration requires funding and technical expertise, mitigation should be adopted to specific use case and threat profile. AI system must be updated and adabtive to meet and address changing risk.
A risk management framework is the structured approach used by an entity to identify, assess, manage and mitigate its cybersecurity risks- (TECHNICAL IMPLEMENTATION GUIDANCE 2025 ENISA)
In a dynamic threat environment the goal is to create a safety plan to respond and recover ahead or during incidents; Using CISA's Cross-sector Cybersecurity Performance Goals (CPG's) functions to Set, Priortize investment and Reduce Risk. which is to Govern, Identify, Protect, Detect, Respond and Recover.
By setting outcomes, risk addressed, scope and recommeded action and Implementing Proper security, Risk Controls AI Systems can mitigate and manage ineqiutable outcomes.
Implementing security, Principle guarded controls to specifically to deal with intelligent AI Systems risk. As AI systems with the potential to escape human control, including those with self-improvement and selfreplication capabilities are assessed and tested promptly.
Microsoft’s AI Risk Assessment outlines a robust framework of administrative and technical controls; spanning data collection, processing, model training, deployment, monitoring, incident response, and business continuity, mapped across the AI lifecycle and adapted from ISO/IEC 27001:2013, NIST 800‑53, PCI‑DSS, and FedRAMP(Microsoft Security. (2024). AI Security Risk Assessment: Best practices and guidance to secure AI systems.)
Furthermore, the risk are evoliving certain legacy systems are vunerable to Dark Analytics, RogueAI, Web Crawl, Bioterorrist, .etc acquiring tools for AI privacy, security and risk management integration of GenerativeAI into security products can enhance security posture and workflow.
COLLABORATION AND COMMUNITY - The Way Forward!
To harness AI's potential fully, priorities depend on countries’ development levels (Gen-AI: Artificial Intelligence and the Future of Work-IMF Staff Discussion Notes SDNs JAN 2024)
Ensuring AI's commitment to safeguarding human rights and operate in an ethical, responsible manner such that ethical practices is instilled and culture of corporate sustainability.
(Joint Cyber Defense AI Collaboration Playbook CISA Jan, 2025)
Sharing knowledge and experiences can lead to responsible safe use of Ai, robust security strategies and a better understanding of emerging threats that can mitigate inequatable outcomes. Collaboration ensure AI aligns with global public goods, human rights, and equitable development.
United Nations in the intenational AI governance ecosystem encasulate 3 enabling connectors in Common understanding , Common ground and common benefits.
2024, global cooperation on AI governance intensified, with organizations including the OECD, EU, U.N., and African Union releasing frameworks focused on transparency, trustworthiness, and other core responsible AI principles. (Artificial Intelligence Index Report 2025 HIA Stanford University Human-Centered Artificial Intelligence)
AI Lifecycle and Key Players The AI landscape is shaped by critical frameworks and industry leaders including NIST, DOD, OECD, NVIDIA, DeepSeek, AWS, Anthropic, Google Gemini, Plantir, Microsoft, IBM, OpenAI, Oracle, and AMD. These entities collectively influence AI governance, technological advancement, and ethical deployment across sectors.
From Biological Neurons to Neuromorphic Computing As AI approaches singularity, the evolution from traditional neural models to neuromorphic architectures underscores the necessity of "future data" that closely mimics human cognition. Technologies such as digital twins and agentic systems—exemplified by Salesforce’s Agent—enable creative problem solving and deep algorithmic exploration aimed at discovering what might be called the "divine algorithm."
Emerging AI Applications and Challenges (2023–2025) Recent developments illustrate AI’s dual potential. On one hand, AI-driven emotional intelligence tools, such as therapeutic bots, enhance empathy and human support. On the other, AI-generated misinformation, exemplified by DeepFake political robocalls like the Biden incident, poses significant risks to democratic processes and public trust.
Ethical Considerations and Human Values The rise of algorithmic elitism and control highlights the critical need to embed emotional intelligence, empathy, and core human values into AI systems. AI must be recognized as a tool that augments rather than replaces human agency and moral judgment.
Industry 4.0 and the Path Forward From Q2 2023 through Q2 2025, breakthroughs such as Elon Musk’s Neuralink brain implant trials and the proliferation of generative AI deepfakes mark a recalibration of Industry 4.0. The future trajectory involves training AI systems grounded in human beliefs, ethics, and values to foster trustworthy and beneficial outcomes.
Elon Musk’s Neuralink is set to start human trials of its brain implant, pushing the boundaries of human-AI integration
Neuralink Lunches Telepathy( aims to help people with disability operate computers) and Blindsight( help for vision in humans) while centred on Reduce Human Suffering, Enhanced human capabilties, Understand consciousness and mitigate risk of AI(Elon Musk, Neural Linke Update 2025)
Contrary to AI-phobia myths, AI is bridging gaps across sectors from customer support to medical research, enhancing efficiency and access. meaning more free time and maybe Unversial income reducing or totally eradicating poverty.
Governance Along the value Chain(Ahead of the the curve: Governing AI Agents under the EU ACT The Future Society Report June 2025)
The last decade of the Brain: The Decline of human intelligence due to massive augmention of human intelligence Hence the new age of Digital intelligence is borne.
Moores law in AI -context, as the computional units and storage for the human brain is 10"11 neurous compare to super intelligent computer as Thebrain’s numbers are essentially fixed, whereas the supercomputer’s numbers have been increasing by a factor of 10 every 5 years or so, allowing it to achieve rough parity with the brain. according to Blue Gene supercomputer resecher by IBM
OpenBrain uses 6% of their compute to run 250,000 Agent-3 copies, which autonomously write, test, and push code at superhuman speed.(AI 2027, AI Fuutures Project, by Daniel Kokotajlo Scott Alexander Thomas Larsen Eli Lifland Romeo Dean, 2025).
AMD is deepening its partnership with Microsoft, bringing Ryzen and Radeon together to power next-gen Xbox gaming across consoles, handhelds, PCs, and the cloud.
the Robot Industrial Park of Liuzhou Northern Ecological New District, China’s Guangxi Zhuang Autonomous Region, the production workshop of UBTECH Robotics in Liuzhou has officially launched the mass production of industrial humanoid robots. This industrial humanoid robot, named "Walker S1", is the first industrial humanoid robot manufactured in Guangxi Zhuang Autonomous Region.
AI is socio-technical in nature they are influenced by societal and human behaviour-(NIST AI RMF)
Cognitive Limits & Philosophical Framing
Drawing on Chomsky’s view that the human mind isn’t just a statistical engine, we recognize that our brains learn like children grasping language, limited in scope and conceptual depth. Rats can’t solve chess or prime numbers mazze game because they lack abstract cognition. Even with augmented intelligence, AI may unify knowledge but cannot transcend fundamental human cognitive domains. - (The machine, the ghost, and the limits of understanding” (University of Oslo, Sep 2011)
AI is not just a mantra ala carte; it demands comprehensive understanding and responsible governance beyond materialism.
Geoffrey Everest Hinton “It’s going to be like the Industrial Revolution but instead of our physical capabilities, it's going to exceed our intellectual capabilities. … But I worry that the overall consequences of this might be systems that are more intelligent than us that might eventually take control” (BBC, 2024).
AI Assurance Mechanisms and Regulation - The UK Department for Science, Innovation, and Technology emphasizes AI assurance mechanisms, focusing on the safety of AI from development through deployment.
As AI continues to evolve, it is essential to stay ahead of its curve by understanding its implications, enhancing its benefits, and mitigating its risks. The collaborative efforts of global stakeholders are crucial in navigating the future of AI in cybersecurity, and other vertical and horizontal sectors. Hence AI should remain a tool, not a replacement, embedded with human empathy, emotional intelligence, and moral values.
Disclaimer: This article insight was generated and inspired by months of reading cyber publications and credibly Cybersecurity research sources such as NIST, CISA, OECD, UNESCO,Bloomberg, WEF, DoD, SANs, CSA, GOA, ICO, CIS, CMMC, NIS2, OPENAI, KPMG, IBM Security, EU-GDPR, ITU, IC3, ISC2 DHS, SANS, ISACA, ENISA, INFOSEC, CISA,CMMC, etc., and was written solely for educational purposes, without little on no use of Artificial intelligence
References:
. NIST AI 800 -218A: Secure Software Development Practice for Generative AI and Dual-Use foundation models
NIST AI 100- 5: A Plan for Global engagement on AI Standards outlining Strategies for international collaboration with GenAI.
CISA: Cybersecurity Infrastructure Agency (AI Cybersecurity Collaboration Playbook JCDC)
NIST AI 100- 1:AI RMF. 1.0
NIST AI 600-1: Initial Public Draft, Artificial Intelligence Risk Management Framework: Generative Artificial Intelligence Profile, 2024.
ENISA Report on Cybersecurity of AI and Standardization: 2024.
World Economic Forum: Unlocking Cyber Resilience in Industrial Environments: Five Principles, November 2023.
Executive Order on the Safe, Secure, and Trustworthy Development and Use of Artificial Intelligence: The White House, October 2023.)
Embrace the change stay ahead of the Curve Be Productive with A.i
AI Regulation: focus on Safety Ai from development, deployment, and use safety.