Tools & Platforms
AI Is Creating a Dangerous Blind Spot for Global Companies (and Most Don’t Even Know It)
Organizations worldwide are racing to implement artificial intelligence. According to industry reports, 42% of organizations plan to invest in AI-related IT tools within six months, and 77% plan to implement AI initiatives within the next year. But there’s a critical problem most organizations haven’t considered: you can’t effectively deploy AI if you don’t know what IT assets you have.
As CEO of Teqtivity, an IT Asset Management (ITAM) solutions provider, I’ve seen firsthand how organizations struggle with this fundamental challenge. The rush to adopt AI technologies is creating a dangerous blind spot in enterprise technology management.
The Hidden Crisis in IT Asset Management
The current state of IT asset tracking across global organizations is alarming. Nearly 90% of IT administrators are concerned about devices or applications managed outside of IT, with 38% reporting they don’t have the ability or visibility to discover all applications in use. This lack of visibility becomes exponentially more dangerous when you add AI tools to the mix.
For international organizations, the complexity multiplies. Global IT teams must manage technology assets across different time zones, regulatory environments, and operational standards. When departments work in silos (for example: IT focusing on infrastructure, Finance tracking costs, HR managing employee equipment, and Security monitoring compliance), critical gaps emerge.
The financial impact is staggering. According to IBM’s Cost of a Data Breach Report, the average cost of a data breach has surged to $4.88 million, with 40% of these breaches involving data distributed across multiple environments. Meanwhile, 39% of organizations now spend 26-50% of their IT budget on licensing fees, up from 28% in 2024.
Why AI Makes Asset Management More Critical
Artificial intelligence implementations require unprecedented visibility into your technology ecosystem. AI tools need to integrate with existing systems, access data across platforms, and operate within security frameworks. Without proper IT Asset Management, organizations face several risks:
- Shadow AI Proliferation: Just as 88% of IT admins report concerns about shadow IT, unauthorized AI tool adoption is becoming a significant governance challenge. Employees are implementing AI solutions independently, creating security vulnerabilities and compliance gaps.
- Resource Misallocation: 85% of IT administrators want a single tool for IT management, yet 26% still use 11 or more tools. Adding AI solutions to an already fragmented technology stack without proper asset management creates operational chaos.
- Security Vulnerabilities: With 46% of organizations having experienced a cyberattack, 33% of those being AI-generated attacks, tracking every technology asset becomes critical for security teams.
International IT Asset Management Best Practices
Global organizations require sophisticated ITAM strategies that address cross-border complexities. Effective international IT Asset Management involves several key components:
- Unified Asset Visibility: Organizations need real-time tracking of hardware, software, and cloud resources across all locations. We recently worked with a client who improved their inventory accuracy from 13% to 95% within one month by implementing proper ITAM processes.
- Cross-Departmental Integration: Modern ITAM solutions must bridge departmental silos. When IT Asset Management systems integrate with HR onboarding workflows, Finance budgeting systems, and Security monitoring tools, organizations achieve better outcomes across all functions.
- Automated Compliance Tracking: For international operations, automated compliance monitoring ensures adherence to different regional regulations while maintaining operational efficiency.
- Lifecycle Management: Proper asset lifecycle management helps organizations optimize their technology investments, reduce waste, and maintain security standards across global operations.
Building the Foundation for AI Success
Organizations that establish robust IT Asset Management practices before implementing AI initiatives gain significant competitive advantages. While many leaders believe AI is outpacing their organization’s ability to protect against threats, companies with mature ITAM practices are turning this challenge into an opportunity.
Proper asset management enables:
- Strategic AI Deployment: Understanding your current technology landscape helps identify the best integration points for AI tools. Rather than adding AI solutions randomly across departments, organizations with complete asset visibility can map AI capabilities to existing workflows and ensure new AI tools complement rather than conflict with current systems. This prevents the IT sprawl that already affects teams.
- Risk Mitigation: Complete asset visibility supports security teams in protecting against AI-driven threats. With AI-generated attacks becoming more common, security teams need real-time visibility into every endpoint, application, and data flow. ITAM provides the foundation for security models by ensuring every asset is accounted for, monitored, and properly configured. When security teams know exactly what technology they have and where it’s deployed, they can respond to threats quickly and effectively.
- Cost Optimization: Clear visibility into technology spending helps organizations make informed decisions about AI investments. With licensing fees consuming an increasing portion of IT budgets, organizations cannot afford to add AI tools without understanding their current technology spend. ITAM enables teams to identify underutilized resources, consolidate redundant tools, and allocate AI budgets strategically.
- Compliance Assurance: Proper asset management supports regulatory requirements across different markets. As AI regulations evolve globally, organizations need comprehensive documentation of how AI tools access, process, and store data. ITAM provides the framework that compliance teams require to demonstrate responsible AI deployment across international operations.
- Operational Excellence: Mature ITAM practices enable the cross-departmental collaboration required for AI success. When IT, Finance, HR, and Security teams share real-time asset data, they can coordinate AI deployments that serve business objectives rather than departmental silos. This collaborative approach transforms AI from a technology experiment into a strategic business enabler.
Organizations that invest in foundational ITAM practices before pursuing AI initiatives are positioning themselves for sustainable competitive advantage.
The Path Forward
As AI reshapes every industry, organizations with complete asset visibility, cross-departmental alignment, and proactive technology management will set the pace while others struggle to catch up.
Before your organization makes its next AI investment, ask yourself: Do you know exactly what technology assets you have, where they are, and how they’re being used? If the answer is no, you’re not ready for AI. But with the right IT Asset Management foundation, you can position your organization to succeed in the AI gold rush while maintaining security, compliance, and operational excellence.
For more information about IT Asset Management solutions for global organizations, visit www.teqtivity.com.
Tools & Platforms
“Elon Musk Unleashes the Colossus!”: World’s Most Powerful AI Supercomputer Dwarfs All Rivals and Sparks Panic in the Global Tech Community
| IN A NUTSHELL |
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Elon Musk’s relentless pursuit of AI supremacy has taken a monumental step forward with the introduction of Colossus, a groundbreaking supercomputer. Boasting an astounding 100,000 Nvidia H100 GPUs, this AI powerhouse promises to redefine the landscape of artificial intelligence. As xAI, Musk’s brainchild, plans to enhance Colossus with an additional 100,000 GPUs, including the cutting-edge H200 chips, the stakes in the AI race have never been higher. This bold move is not merely a technological feat but a statement of intent, as Musk aims to outpace rivals such as OpenAI and Meta, cementing his place at the forefront of AI innovation.
The Birth of Colossus: A Supercomputer Like No Other
Launched in a mere four months, Colossus stands as a testament to the rapid advancements in AI technology spearheaded by Elon Musk and his team at xAI. Unlike other AI clusters, Colossus integrates its vast number of GPUs into a singular, cohesive system, allowing for unparalleled performance and efficiency. This supercomputer will serve as the training ground for xAI’s next-generation large language models (LLMs), including the upcoming Grok-3, which is poised to challenge OpenAI’s GPT-4 by December.
Elon Musk, ever the visionary, took to his social media platform, X (formerly Twitter), to laud the efforts of his team and partners. “Excellent work by the team, Nvidia, and our many partners/suppliers,” Musk declared, highlighting the collaborative nature of this monumental achievement. The creation of Colossus is not just a milestone for xAI but a significant leap for the entire AI industry, pushing the boundaries of what is possible.
Partnerships and Power: Behind the Scenes of Colossus
Colossus’s creation was made possible through strategic partnerships with industry leaders such as Dell Technologies and Super Micro Computer. Michael Dell, CEO of Dell Technologies, expressed immense pride in contributing to this groundbreaking project. Furthermore, xAI’s financial prowess was bolstered by a substantial $6 billion Series B funding round, led by top investors like Andreessen Horowitz and Sequoia Capital, elevating its valuation to an impressive $24 billion.
However, the supercomputer’s immense power requirements have sparked controversy. Environmental advocates in Memphis, Tennessee, where Colossus is housed, have voiced concerns over the use of gas-powered turbines to meet its energy demands. The Southern Environmental Law Center (SELC) has accused xAI of operating without the necessary air permits, potentially exacerbating local air pollution. These allegations underscore the delicate balance between technological advancement and environmental responsibility.
The Technical Edge: Nvidia’s Role in Colossus’s Supremacy
Nvidia’s cutting-edge technology is at the heart of Colossus’s impressive capabilities. The H100 and H200 chips, known for their exceptional memory and bandwidth performance, are instrumental in powering this AI behemoth. While Nvidia has recently unveiled its Blackwell chip, which surpasses the H200’s specifications, the H200 remains integral to Colossus’s architecture.
The AI community has reacted with enthusiasm to the launch of Colossus, viewing it as a pivotal moment in the industry’s evolution. Nvidia and industry luminaries like Cathie Wood, CEO of ARK Invest, have praised xAI’s groundbreaking achievement, recognizing Colossus as a significant milestone in AI development. This collaboration between xAI and Nvidia exemplifies the synergy between visionary leadership and cutting-edge technology, propelling the AI industry to new heights.
Environmental Concerns and Regulatory Hurdles
Despite its technological marvel, Colossus has ignited environmental and regulatory concerns. The SELC’s allegations regarding the turbines’ operation without proper permits cast a spotlight on the environmental impact of such massive computing infrastructure. Elon Musk’s vision of AI dominance comes with a considerable environmental cost, emphasizing the need for sustainable energy solutions as AI systems scale.
Musk, an advocate for responsible AI development, supports legislative efforts like California’s Senate Bill 1047, which aims to regulate AI technologies. This stance, however, has sparked debates within the tech community, with some fearing that it could stifle innovation. As xAI navigates these challenges, the balance between technological progress and ethical responsibility continues to be a focal point in the AI discourse.
As xAI continues to expand Colossus, the potential for groundbreaking advancements in AI research and development is immense. This supercomputer is not just a technological marvel; it embodies Musk’s ambition to redefine AI capabilities and secure a leading position in the AI sector. However, navigating complex regulatory landscapes and addressing environmental concerns will be crucial in fully realizing Colossus’s potential. What role will ethical and sustainable practices play in the future of AI development?
This article is based on verified sources and supported by editorial technologies.
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Dive Brief:
- Kroger will continue investing in AI as tools enable better product visibility and productivity, leading to reduced inventory loss or shrink and improved talent retention, executives said during the grocer’s Q1 earnings call in June.
- “We’ve seen good progress [around shrink],” SVP and CFO David Kennerley said during the call. “What we really attribute this to is we’ve made some investments in some AI-enabled technology and deployed new processes around that technology.”
- The company also launched a virtual AI assistant for its associates, which it partly credited for record levels of store and company retention during the quarter. “When our associates stay longer, they learn more, take on additional responsibilities and deliver a better customer experience, which leads to better sales,” said interim CEO Ron Sargent.
Dive Insight:
Kroger is doubling down on AI while keeping savings top of mind, joining a cost-conscious group of businesses making similar moves.
The grocer will close 60 underperforming stores by the end of next year as it reassesses capital allocation and “aggressively” finds ways to reduce costs throughout the company, according to the earnings call.
Kroger sees AI and other technologies as part of the solution, too.
“The other thing that will also contribute towards better cost performance is what I call ways of working and process improvement,” Kennerley said. “There’s a lot of opportunity here to work smarter, more efficiently, more tech-enabled, and we’ve already got some good proof points on that.”
Excluding fuel, identical-store sales ticked up 3.2% during Q1 2025, which ended May 24, compared with the same period last year. Kroger characterizes a store as identical if it operates without expansion or relocation for five full quarters.
Kroger’s once-sought-after merger partner, Albertsons, has similarly sharpened its technology focus while eyeing cost-saving measures.
“Our North Star is to use technology in everything that we do,” Albertsons CEO Susan Morris said during the company’s Q4 2024 earnings report in April.
As part of the strategy, the Idaho-headquartered grocer plans to increase AI use to enhance product quality and monitoring for freshness as it looks to drive higher sales and better customer experiences.
The efforts also align with Albertsons’ three-year plan to cut $1.5 billion in costs that rolled out after the merger failed.
Scientists leverage artificial intelligence to overcome a major hurdle in zinc-ion battery development, paving the way for cheaper, greener, and more efficient energy storage.
In a significant leap forward for battery innovation, scientists from Singapore’s Nanyang Technological University and China’s Huaiyin Normal University have teamed up to create an AI-powered system that could drastically improve how rechargeable batteries are made.
Led by Dr. Edison Huixiang Ang from the NIE/NTU, the team has harnessed artificial intelligence (AI) to solve one of the biggest challenges in zinc-ion battery technology, preventing dendrite growth.
Zinc-ion batteries are a promising alternative to today’s lithium batteries. They are cheaper, safer, and better for the environment. But they have one big problem-tiny spikes called dendrites can grow inside the battery when it charges. These spikes can cause the battery to stop working or even short-circuit.
To solve this, Dr. Ang’s team turned to AI. Instead of testing materials one by one, the AI quickly checked over 168,000 different combinations. This smart approach led them to a special material made from cerium and iron, called a metal-organic framework (MOF), that helps stop the dangerous spikes from forming.
“AI helped us discover the right material quickly and at a lower cost,” Dr. Edison Ang told Tech Explorist. “This allows us to create safer batteries that are more sustainable for the future.”
The team also created a thin protective layer using this material. In tests, the new battery design worked for over 4,300 hours and stayed almost 100% efficient after 1,400 charge cycles-much better than regular batteries.
This discovery could be useful for electric cars, phones, and storing solar or wind energy. As we move toward a greener world, having strong and reliable batteries is more important than ever.
“AI is helping scientists everywhere work smarter,” said Dr. Ang. “It’s opening the door to new ideas that can change the world.”
Journal Reference
- Jianbo Dong, Guolang Zhou, Wenhao Ding, Jiayi Ji, Qing Wang, Tianshi Wang, Lili Zhang, Xiuyang Zou, Jingzhou Yin and Edison Huixiang Ang. Machine learning-assisted benign transformation of three zinc states in zinc ion batteries. Energy & Environmental Science, 2025,18, 4872-4882. DOI: 10.1039/D5EE00650C
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