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What we Did when Employees were Displaced by Gen AI

Dismissed business people packing their belongings and leaving the office, a robot is sitting at the desk and working: the impact of AI on jobs

By Dr. Gleb Tsipursky 

When generative AI first captured the world’s attention in 2023, Ivanti didn’t respond with panic or denial. The global software company saw opportunity and responsibility in equal measure. At the center of this thoughtful approach was Brooke Johnson, Chief Legal Counsel, who also serves as Senior Vice President of Human Resources and Security. Wearing all three hats, Johnson led Ivanti’s effort to guide its workforce through a technological disruption that upended not just workflows, but roles.

Rather than simply react to the rapid deployment of Gen AI tools across the industry, Ivanti made a strategic decision: define what Gen AI would mean for its people before letting it reshape the company. In her interview with me, she described how Ivanti built a sustainable AI governance model, prioritized transparency and equity, and tackled the complex challenge of employee displacement—not with layoffs, but with reinvention.

Building Guardrails Before Acceleration

The executive team at Ivanti understood early that they needed more than a technical roadmap—they needed principles. Johnson orchestrated a company-wide initiative to examine Gen AI not just as a product enhancer, but as an internal force that could transform, or destabilize, the workplace. This meant asking hard questions: Would Ivanti allow Gen AI to replace jobs outright? Or would it find ways to transition affected employees into new roles?

Every new AI tool was to be evaluated, supervised, and developed like an employee, not simply deployed and forgotten.

The result was the formation of the AI Governance Council (AIGC), a cross-functional body designed to translate executive vision into practical policy. It wasn’t a legal body, despite being helmed by someone from the legal team. It included representatives from IT, privacy, product, security, and HR, ensuring that decisions weren’t just compliant but human-centered. Subcommittees focused on compliance, training, and intake—each tasked with helping Ivanti balance innovation with integrity.

One of the council’s foundational concepts came from HR: treat AI like a new hire. Every new AI tool was to be evaluated, supervised, and developed like an employee, not simply deployed and forgotten. This human-centric analogy drove the company’s approach to both onboarding AI and managing the impact it had on real people.

When Jobs Changed, People Stayed

The elephant in the room for every business embracing Gen AI is workforce displacement. But at Ivanti, the commitment to retaining talent was embedded in the company’s values. “We explicitly chose to stay committed to our people,” Johnson explained. “Even if their specific job was changed, our goal was to find another place for them within the organization.”

This wasn’t lip service. The company created a structured intake and review process to evaluate each potential Gen AI use case. Part of that evaluation included a return-on-investment analysis, not just in terms of dollars and hours saved, but in the human cost. Could Gen AI increase efficiency without diminishing employee value?

In many cases, yes. When an AI tool eliminated repetitive tasks, the employee whose work was impacted was retrained for a more strategic role. In fact, AI became a catalyst for internal mobility. “Reliable AI requires human oversight,” said Johnson. “We weren’t just reducing roles—we were redefining them.”

Ivanti’s employee base didn’t just accept the shift. They participated in it. Johnson led internal communication efforts to ensure everyone understood the process. No team could implement a Gen AI-powered solution without passing legal, privacy, and security review. And once approved, tools were deployed in pilot programs with clear metrics for success.

Legal Leadership in an Evolving Landscape

While many companies leave AI governance to technical or operational leaders, Ivanti’s choice to place legal in the lead reflects a deeper understanding of the risks. “We knew Legal couldn’t just come in at the end and sign off,” Johnson noted. “We needed to be part of shaping how AI was implemented from the start.”

That involvement proved crucial. Gen AI tools bring with them thorny issues around privacy, ethics, and bias—many of which sit at the intersection of law and technology. Johnson cited recruiting as a key area of concern. If a Gen AI-powered hiring platform is filtering candidates based on flawed or biased data, how can the company know? Without transparency, the risk of discriminatory outcomes becomes very real.

Gen AI tools bring with them thorny issues around privacy, ethics, and bias—many of which sit at the intersection of law and technology.

Ivanti’s legal team focused on making AI explainable. They selected vendors carefully, asking tough questions about training data, error rates, and mitigation of bias. And while the U.S. regulatory landscape remains uncertain, Johnson pointed out that being a global company means aligning with the EU AI Act and other emerging standards. “We’re not going to see the toothpaste go back in the tube on AI,” she said. “So we need to make sure we’re using it responsibly from day one.”

Measuring Impact with Intention

One of the most important challenges in the Gen AI era is quantifying the actual benefits. At Ivanti, that meant developing metrics that went beyond buzzwords and hype. The company tracks ROI through practical measures: hours saved, meetings avoided, and task completion times reduced.

In one example, employees were able to skip hour-long meetings and instead review a five-minute AI-generated summary, saving precious time. “It’s not magic, but it’s real,” said Johnson. “And it adds up.”

To validate these benefits, Ivanti set up a dedicated team to run controlled tests of Gen AI tools within specific teams. Feedback loops were established, and adoption was rolled out gradually to avoid disruption. “You can’t just buy every shiny new tool,” Johnson said. “You have to know if it’s actually worth it—for the business and for the people using it.”

Reimagining Work, Not Replacing Workers

Ivanti’s journey with Gen AI is a case study in how large organizations can approach innovation with empathy. The company embraced transformation without sacrificing its workforce, viewing Gen AI as a collaborator rather than a competitor. By creating governance structures, elevating legal and ethical oversight, and investing in employee adaptation, Ivanti demonstrated what responsible AI adoption looks like in practice.

“We never saw this as just a legal issue or a tech opportunity,” Johnson reflected. “It was always a people question.”

And in that answer, Ivanti found a way forward—one where AI enhances rather than erases human value.

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About the Author

Dr. Gleb TsipurskyDr. Gleb Tsipursky was named “Office Whisperer” by The New York Times for helping leaders overcome frustrations with hybrid work and Generative AI. He serves as the CEO of the future-of-work consultancy Disaster Avoidance Experts. Dr. Gleb wrote seven best-selling books, and his two most recent ones are Returning to the Office and Leading Hybrid and Remote Teams and ChatGPT for Leaders and Content Creators: Unlocking the Potential of Generative AI. His cutting-edge thought leadership was featured in over 650 articles in prominent venues such as Harvard Business Review, Fortune, and Fast Company. His expertise comes from over 20 years of consulting for Fortune 500 companies from Aflac to Xerox and over 15 years in academia as a behavioral scientist at UNC-Chapel Hill and Ohio State. A proud Ukrainian American, Dr. Gleb lives in Columbus, Ohio.

Trump Backs Controversial Nippon-US Steel Deal, Hikes Import Tariffs

Trump Backs Controversial Nippon-US Steel Deal, Hikes Import Tariffs

President Donald Trump traveled to western Pennsylvania on Friday to promote a pending agreement between US Steel and Japan’s Nippon Steel, calling it a “blockbuster deal” that would keep the historic American company under U.S. control — even as final terms remain unclear.

Speaking to a crowd of steelworkers in hard hats and safety vests outside a US Steel plant near Pittsburgh, Trump hailed the investment as a turning point for American manufacturing. “We want our future built with the pride of Pittsburgh, not cheap steel from Shanghai,” he said.

During the visit, Trump announced that tariffs on imported steel would double from 25% to 50%, a move aimed at protecting domestic production. “You understand tariffs better than Wall Street ever will,” he told the workers.

Despite the fanfare, Trump later admitted the deal has yet to be finalized. “I have to approve the final deal, and we haven’t seen it yet,” he told reporters after returning to Washington. Still, he described it as the largest investment in Pennsylvania’s history and framed it as a strategic partnership rather than a full acquisition.

US Steel executives echoed the president’s optimism. CEO David Burritt and Nippon vice chairman Takahiro Mori joined the event, with Mori calling the deal a “game changer” that would ensure US Steel remains “made in America by Americans.”

Yet the deal has drawn sharp criticism from the United Steelworkers union, which continues to oppose it. “Binding commitments are what matter — not speeches,” the union said in a statement, citing Nippon’s past violations of trade rules.

While national union leadership remains opposed, local officials near Pittsburgh have expressed support, arguing the investment will safeguard jobs and modernize aging plants. Reports suggest federal oversight through “golden shares” could allow the U.S. to retain control over board appointments.

Trump, who once opposed the deal, said he changed his mind after Nippon agreed to increase its investment. “It just kept getting better for the workers,” he said. “I’ll be watching over it. It’s going to be great.”

The president also linked steel production to national security, warning against reliance on foreign materials. “If you don’t have steel, you don’t have a country,” he declared.

Although US Steel, once a global industrial powerhouse, now employs just 14,000 workers in the U.S., it remains a potent symbol of American strength — and a political flashpoint in a key battleground state.

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Focus on Sustainability in Addressing Gen AI Ethics and Risks

AI ethics

By Dr. Gleb Tsipursky

As generative AI revolutionizes the way companies operate and engage with their stakeholders, organizations are grappling not only with the vast opportunities it presents but also the ethical risks that accompany its widespread adoption. Few leaders understand the complex interplay of innovation, responsibility, and sustainability as deeply as Prakash Arunkundrum, President of Logitech for Business. In an interview with me, Arunkundrum revealed how Logitech is navigating the Gen AI landscape with a strong focus on governance, transparency, and the long-standing values that define the company’s ethos.

Embedding AI Thoughtfully Into the Enterprise

Internally, Logitech has embraced generative AI with remarkable enthusiasm. Arunkundrum describes the current moment as “by and far the most transformative time” in the company’s history. Teams across the organization—from marketing to software development—are experimenting with AI tools to enhance efficiency and creativity. Logitech’s video conferencing and hardware development units, already steeped in machine learning for nearly a decade, are now expanding into more sophisticated applications powered by large language models.

To safeguard intellectual property and ensure responsible use, the company established an internal AI governance board.

Despite this enthusiasm, Logitech’s approach is anything but impulsive. To safeguard intellectual property and ensure responsible use, the company established an internal AI governance board. This body approves the use of models and tools while ensuring compliance with privacy and ethical standards. Arunkundrum himself uses multiple AI tools daily, but under a framework designed to protect both company assets and user trust.

Crucially, leadership support for AI adoption has been solid from the outset, stemming from Logitech’s identity as a technology company where innovation is not optional but existential. Yet this support has been balanced with caution—particularly regarding the protection of proprietary data and the prevention of bias in AI systems.

Addressing Ethical Concerns Through Sustainable Design

One of the most compelling elements of Logitech’s AI journey is its commitment to ethical practices rooted in sustainability. Arunkundrum draws a direct line between the company’s legacy of environmental stewardship and its current efforts to mitigate algorithmic bias and ensure fairness in AI applications. From Logitech’s long-standing sustainability impact reporting to its efforts in diversity and inclusion, the values that shape its environmental approach now inform its AI strategy.

For instance, in developing AI-powered features like facial recognition and audio optimization, Logitech has invested heavily in diversifying its training data sets. The goal is to ensure that devices recognize and respond accurately to all users—regardless of skin tone, lighting conditions, or accents. This is particularly important in Logitech’s core domains of audio, video, and input, where the hardware serves as the first touchpoint for data that will eventually be processed by AI systems.

“Bias in generative AI is not just a theoretical concern for us,” said Arunkundrum. “It affects the quality and equity of the user experience, especially in products designed for global use.” To address this, Logitech mandates a development model that separates the roles of data creator and data reviewer—an approach borrowed from its hardware quality assurance processes but now repurposed for AI training data.

Building Trust with External Stakeholders

Externally, Logitech’s commitment to responsible AI extends to its enterprise customers and broader ecosystem. The company was among the early adopters of the European Union’s Responsible AI Act, underscoring its intent to maintain transparency and accountability in the deployment of AI-powered products.

A key differentiator for Logitech is its approach to data privacy. “Even before AI became a buzzword, we were already careful about the data that organizations share with us,” Arunkundrum emphasized. This conservative data policy made it easier for the company to comply with emerging regulatory frameworks and customer expectations. Logitech’s devices—ranging from webcams and microphones to mice and keyboards—may generate the input for AI models, but they do so without retaining personal user information, reinforcing the company’s role as a trusted intermediary rather than a data miner.

Furthermore, Logitech collaborates closely with cloud service providers like Microsoft, Zoom, and Google to ensure clarity around data responsibility and security. These partnerships enable Logitech to enhance AI features without compromising user privacy, maintaining a distinct and well-defined role within the ecosystem.

Defining a Human-Centric Vision for Gen AI

What sets Logitech apart in its Gen AI strategy is its human-centric philosophy. The company’s mission—to extend human potential in work and play—serves as the guiding principle behind its AI efforts. Rather than competing in the crowded field of language model development, Logitech focuses on enhancing the user’s experience through smart hardware integrations that elevate productivity and inclusion.

Rather than competing in the crowded field of language model development, Logitech focuses on enhancing the user’s experience through smart hardware integrations that elevate productivity and inclusion.

Recent innovations illustrate this vision in action. The Logitech Sight video bar, for example, uses AI to manage camera angles in hybrid meetings, creating an equitable experience for remote participants. It combines Silicon Valley precision with Hollywood storytelling, automatically shifting the camera frame to capture the most relevant speaker. Another example is a headset with built-in AI that cancels out background noise on both ends of a call, focusing only on the human voice. This makes communication clearer and more inclusive, especially for users in diverse environments.

Logitech’s Streamlabs gaming products have also begun incorporating agent-based AI that functions as a personalized coach during gameplay, analyzing actions and offering real-time feedback. Across all these examples, the aim remains consistent: to make technology “just work”—invisible, seamless, and empowering.

Sustaining the Momentum, Responsibly

As the conversation with Arunkundrum made clear, Logitech sees generative AI not as an end in itself but as a tool to support human capabilities. That philosophy permeates everything from product development to policy design. By anchoring its AI strategy in the company’s sustainability values, Logitech offers a compelling model for other organizations grappling with the complexities of innovation and ethics.

“We’re not perfect,” Arunkundrum acknowledged, “but acknowledging that there’s more work to be done is the most important first step.”

In an era where AI innovation often moves faster than regulation, Logitech’s deliberate, values-driven approach offers a rare combination of pragmatism and principle. Its story is a timely reminder that the future of generative AI doesn’t just lie in new algorithms—it lies in the choices organizations make today about how, and why, they use them.

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About the Author

Dr. Gleb TsipurskyDr. Gleb Tsipursky was named “Office Whisperer” by The New York Times for helping leaders overcome frustrations with hybrid work and Generative AI. He serves as the CEO of the future-of-work consultancy Disaster Avoidance Experts. Dr. Gleb wrote seven best-selling books, and his two most recent ones are Returning to the Office and Leading Hybrid and Remote Teams and ChatGPT for Leaders and Content Creators: Unlocking the Potential of Generative AI. His cutting-edge thought leadership was featured in over 650 articles in prominent venues such as Harvard Business Review, Fortune, and Fast Company. His expertise comes from over 20 years of consulting for Fortune 500 companies from Aflac to Xerox and over 15 years in academia as a behavioral scientist at UNC-Chapel Hill and Ohio State. A proud Ukrainian American, Dr. Gleb lives in Columbus, Ohio.

Are Computer-Using Agents the Next Big Disruptor?

AI agent and generative artificial intelligence concept. Businessman using AI agents on screen, including chatbots, AI assistants, and data analytics tools on a laptop.

By Juras Juršėnas

Agentic AI is the newest AI development creating waves for developers. The potential this technology presents in terms of how organisations operate, scale, and optimise is limitless. However, the effect computer-using agents will have on the current SaaS market is still an open question. Do businesses have what they need to build systems that deliver on what customers are asking of them?

Artificial Intelligence (AI) has produced many strains of technology that are already changing how we do things at home and work. The changes expected in the near future are even more revolutionary. Agentic AI technology that allows AI tools to autonomously determine the best paths to perform tasks with minimal human oversight is the flagship of this next wave of changes.

One of the most dynamic ways agentic AI can be implemented is by creating and launching computer-using agents (CUAs). The expectations for these tools go as far as completely transforming how we interact with computers. Thus, naturally, AI companies race to position themselves as the best CUA developers while software-as-a-service (SaaS) providers pay close attention.

What are computer-using agents?

Computer-using agents (CUAs) are AI-driven systems that interact with software as a user would. These agents can navigate the user interface by pressing buttons, inputting information, and analyzing responses. Thus, they can autonomously execute operations on behalf of humans through the complex interplay between AI vision, machine learning, and data processing. As such, CUAs are a subcategory of Agentic AI systems, specializing in using existing software interfaces the way a human would.

After recent releases by the big players, such as OpenAI’s Operator and Microsoft’s Azure AI Foundry, CUAs are attracting increasingly more attention. They are expected to eventually disrupt the SaaS market. How warranted is this expectation?

CUAs – a one-size-fits-all AI system for optimization?

The words accompanying Operator’s launch make the case for CUA technology on the whole:

“CUA is trained to interact with graphical user interfaces (GUIs)—the buttons, menus, and text fields people see on a screen—just as humans do. This gives it the flexibility to perform digital tasks without using OS- or web-specific API’s.”

It is important to note their capacity to make decisions based on rules or learned behaviours and adapt to changing environments. Thus, their application horizons are truly huge, as seen in the examples below.

Network Security. CUAs could automate various security-related IT processes, such as updating and securely storing passwords and implementing other updates across the network. Additionally, they can manage user access and automatically handle many network security incidents while constantly logging all incident data.

Back Office Tasks. Various back office tasks involve interacting with software. AI agents can simplify engagement with CRMs and various other systems and databases based on CRUD (create, read, update, delete) operations. By automating these operations, CUAs can streamline the achievement of users’ goals while saving time and costs.

Financial Services. Use cases here are very wide, covering everything from transaction processing to customer verification and fraud detection. CUAs could also help streamline compliance checks and reduce operational risks while ensuring that all regulatory requirements are consistently met.

Web Scraping. CUAs can be integrated into web scraping platforms to fill in scraping parameters, navigate websites, and find the necessary information to extract. Dedicating these tasks to AI agents opens web scraping to more professionals beyond specifically trained developers. Meanwhile, the latter have more time to work on complex tasks and innovative solutions.

Furthermore, CUAs are built on constantly improving large language models (LLMs), allowing them to determine the best next move in a particular context. Thus, we can expect them to evolve rapidly when tested in real-life applications.

Building the next disruptor

The disruptive potential of CUAs is clear. Microsoft’s CEO himself sparked a debate by suggesting that AI agents will make SaaS as we know it obsolete by taking over CRUD tasks and moving seamlessly between databases and apps.

Other experts are more restrained. They point out that CUAs are more likely to transform SaaS rather than completely replace it, and that the scale of this transformation is still up in the air.

The answer to this question depends on the quality of the CUAs that the developers produce next. We can trace how CUAs function to better understand what developers must do to unleash the technology’s disruptive power. Additionally, this provides insight into how companies will try to advance against competitors.

In a nutshell, CUAs work by analyzing screen pixels to understand what’s being displayed and using virtual mouse and keyboard controls to execute actions. More generally, the agents must be built to excel at three iterative processes.

Information intake: CUAs take screenshots of the digital interface in order to understand the environment they’re operating in. They utilize computer vision and, by examining GUI screenshots, recognize the interface elements they need to complete tasks. Additionally, CUAs can extract and interpret text from screenshots. Web browser-using agents don’t even have to make the screenshots, as they can just analyze the HTML to understand how to navigate the website.

In order to interpret complex user requests, CUAs need high natural language processing (NLP) capabilities. The best CUAs should also be able to interpret multimodal requests that include text, imagery, audio, and other input types. Training models to have these abilities requires a lot of multimodal data. Thus, the race to build the next big disruptor is truly about the companies’ capability to efficiently extract and use such data for training.

Reasoning: Another crucial competition area for AI companies is training the best reasoning capabilities. Once the visual information has been processed, CUAs use step-by-step reasoning to determine the best course of action. They monitor progress through multiple stages and adjust their approach whenever the interface changes. Once again, the quality of training data will determine the robustness and utility of the upcoming tools.

Action: Ultimately, CUAs perform tasks using virtual mouse and keyboard inputs. They can conduct various actions, including entering text, selecting buttons, and navigating content. The most useful and flexible agents will seamlessly integrate with various APIs and external systems to perform complex tasks. Developing such agents will require innovative solutions to numerous challenges of integrating AI with legacy systems.

Thus, the rollout of these AI agents will once again showcase the human ingenuity and talent that various companies have at their disposal.

The takeaway

Computer-using agents are just one of the many AI innovations that are changing the face of modern business. The potential they present in terms of how businesses operate, scale, and optimise is limitless. The effect these agents will have on the current SaaS market is still an open question. Its answer depends on how well companies can extract and leverage multimodal data and other resources to build the next generation of agents. This race will also play a part in determining the power dynamics between the top players in AI development.

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About the Author

Juras JuršėnasWith over 16 years of experience in the IT field, Juras Juršėnas has established himself as an expert in SaaS product management and large-scale IT business operations. His ability to apply strategic problem-solving, critical thinking, and people management skills led him to become the COO at Oxylabs, a global web intelligence collection platform.

Cryptocurrency: An Impetus or Impediment Towards Financial Sustainability?

The plant and the bitcoin cryptocurrency coin

By Rafael Alfonso R. Remo and John Paolo R. Rivera

Cryptocurrency continues to redefine the global financial landscape. As digital currencies grow in adoption, institutions face a pressing question: does crypto drive sustainable financial progress or invite further instability? Rafael Alfonso R. Remo and John Paolo R. Rivera explore this tension, weighing its promise against the risks of volatility and disruption.

Since the introduction of cryptocurrency into the financial market, many institutions have seized the opportunity to grow and innovate amid rapid technological advancement and globalization. Is it possible for cryptocurrency to strengthen financial sustainability; or might it contribute to heightened volatility in the financial markets instead?

What is cryptocurrency?

Digital currency is any form of money or payment that exists only in spreadsheets (Zhong, 2022). On the other hand, cryptocurrency is a subset of digital currency that refers to any form of digital or virtual currency that can be obtained using cryptography for security (Beerbaum, 2023). It uses a decentralized system to create transactions. Urquhart and Yarovaya (2023) discussed that cryptocurrency becoming mainstream dates to the establishment of Bitcoin[1] in 2009. Its prominence grew in the late 2010s to early 2020s, paving the way for the establishment of other cryptocurrencies[2] (Urquhart & Yarovaya, 2023).

Cryptocurrency functions similarly to traditional transactions, such as those between institutions and banks (Beerbaum, 2023). The key distinction is that it operates without regulatory oversight and utilizes virtual currency rather than physical money. It involves placing digital entries or tokens of equivalent value into databases to represent deals or agreements (Zhong, 2022).

Since cryptocurrency operates without oversight from a national governing authority yet, it raises a critical inquiry about its legality. Like any institution that handles financial transactions, they are required to be licensed and registered (Terner, 2023). This grants them legitimacy and allows them to operate independently while remaining recognized by the government.

What is financial sustainability?

Financial sustainability refers to the absence of system-wide disruptions that lead to failures within the financial system, while also promoting sustainable finance for the effective management of money and assets (World Bank, 2017). It highlights an institution’s resilience to market-induced stress. As such, financial sustainability is a core objective that institutions aim to achieve through strategic frameworks and policies, such as securing stable sources of funding, income, and revenue, to ensure long-term viability (Financial Stability Board, 2022).

Digital finance refers to the impact of emerging technologies on the financial services industry (European Commission, 2024). It encompasses a broad range of products, applications, processes, and business models that have transformed traditional banking and financial services. Within this digital landscape, cryptocurrency operates using blockchain technology, which is an advanced database mechanism that enables transparent information sharing across a network (Reserve Bank of Australia, n.d.). This allows individuals to manage personal accounts and execute transfers without the involvement of a traditional financial institution (Kramarenko et al., 2019). Thus, blockchain facilitates secure, peer-to-peer transactions without a central authority, offering the potential for faster, more affordable, and accessible financial services.

Additionally, cryptocurrency enables individuals to make direct online payments to one another without the involvement of a governing body. Shin and Rice (2022) highlighted that in an evolving financial landscape, cryptocurrency holds the potential to drive market innovation, promote growth, and support long-term sustainability. As a socio-technical system, it introduces new and significant dimensions for social inquiry. Furthermore, with continued technological advancements, cryptocurrency may offer a range of benefits that surpass those of traditional financing, including enhanced security for consumers. However, despite these proactive developments, concerns around privacy, transparency, and cybersecurity persist.

Well-known forms of cryptocurrency

Jacoby (2025) noted that cryptocurrency began gaining traction in the financial market when Bitcoin emerged as the most widely traded digital currency, paving the way for the rise of others such as Ethereum, Litecoin, and Ripple (Aggarwal & Kumar, 2021). These developments helped establish cryptocurrency as a household name in the years that followed, contributing to significant shifts in market dynamics and prompting the adoption of new digital financing systems.

Since the introduction of Bitcoin, various organizations have entered the space thereby expanding the potential of cryptocurrency and solidifying its presence in the digital financial market. Its continued emergence underscores cryptocurrency’s growing development and. Despite speculative attacks and inherent risks, many continue to pivot toward this asset class due to its ability to reach broader consumer bases and its adaptability to technological innovation in modern financing.

Relevance of cryptocurrency towards financial sustainability

Shahzad et al. (2024) emphasized that cryptocurrency is not only a financial innovation but also a significant contribution to technological advancement. By introducing a new platform for seamless institutional transactions, it has expanded the use of digital space and redefined the concept and value of currency. As such, Javaid et al. (2022) noted that financial service providers are increasingly adopting blockchain technology to enhance authenticity, security, and risk management. Many institutions have begun integrating blockchain into trade and finance systems to implement smart contracts, improve efficiency and transparency, and unlock new revenue opportunities. With its unique recording capabilities, blockchain has the potential to render traditional clearing and settlement processes obsolete.

However, the innovation is not without its challenges. Alsalami and Zhang (2019) pointed out that cryptocurrency is characterized by a high degree of user anonymity, with no definitive record of the number of users on a platform. This incognito nature has raised concerns, particularly as blockchain technology itself does not inherently guarantee user anonymity. Despite this, major players like Bitcoin and Ethereum have continued to push for innovation in the financial sector, introducing updates aimed at enhancing user safety and privacy protection (Chuykov et al., 2024).

The mainstreaming of cryptocurrency, according to Shahzad et al. (2024), was driven by the rapid advancement of technology and globalization, with 2017 marking a pivotal year in its rise. Cryptocurrency heightened awareness of the potential of technology in transforming financial transactions, enabling faster processes with minimal government intervention—an aspect that remains a subject of policy debate (Bomer et al., 2023).

Ben-Ahmed et al. (2023) further observed that while cryptocurrency gained traction in 2017, it was the COVID-19 pandemic in 2020 that significantly accelerated its prominence in global markets. Its rise can be attributed to the intensification of globalization and the necessity brought about by lockdowns, which pushed people toward digital platforms as alternative sources of income (Dardouri et al., 2023).

During the height of the pandemic, cryptocurrency played a critical role in sustaining economic activity (Dardouri et al., 2023). Many businesses turned to cryptocurrency as a way to generate profits independent of government oversight (Masiha, 2022). However, this prompted debate about its reliability given its unconventional structure and absence of institutional regulation.

As cryptocurrency operates primarily through digital platforms (Bomer et al., 2023), questions have also emerged around user identity and the traceability of transactions. Shahzad et al. (2024) noted the lack of a clear transactional path, which complicates accountability and transparency. Nevertheless, Zakarneh et al. (2022) argued that the digital nature of cryptocurrency allows institutions to operate more efficiently, expand their digital footprint, and accelerate growth.

Comparing cryptocurrency with modern banking systems

Cryptocurrency has introduced numerous opportunities that have transformed the concept of money and reshaped how transactions are conducted between institutions (Wang et al., 2022). While these innovations offer significant advantages, they also present notable disadvantages, highlighting the dual nature of digital currency adoption.

One of the key advantages of cryptocurrency lies in its use of cryptography, which makes it nearly impossible to counterfeit or double-spend, which is a feature that strengthens transactional security (Zakarneh et al., 2022). Furthermore, Kumhof and Noone (2021) noted that most cryptocurrencies operate on decentralized networks through blockchain technology or distributed ledgers maintained by a network of computers. This allows for the efficient transfer of funds between parties without the need for intermediaries or regulatory oversight (Wang et al., 2022).

However, this lack of centralized control also gives rise to several disadvantages. Zakarneh et al. (2022) observed that many transactions are conducted anonymously or under fictitious identities, creating potential for misuse in criminal activities such as identity theft and fraud. Anonymity, if left unregulated, may weaken institutional safeguards and increase the risk of misinformation. Wang et al. (2022) added that the system is also vulnerable to cyber threats such as phishing, routing attacks, and malware, which pose serious security concerns.

Another significant drawback is the high price volatility of crypto-assets. Zakarneh et al. (2022) explained that due to the decentralized and speculative nature of cryptocurrency markets, assets often experience large price fluctuations within short periods. This volatility undermines financial predictability and limits institutions’ ability to rely on cryptocurrencies for stable returns (Kumhof & Noone, 2021).

Is cryptocurrency an impetus or impediment?

Cryptocurrency serves as a potential impetus for innovation in the financial system, yet it remains impeded from fully achieving financial sustainability. It has created more convenient avenues for conducting transactions and has pushed institutions to reconsider and expand the concept of currency in the virtual realm. However, despite its transformative potential, many institutions still lack the capacity to effectively incorporate cryptocurrency into their existing systems. This reflects the uneven applicability of digital currencies at present, with adoption varying widely across contexts and capabilities.

Significant risks and uncertainties remain, particularly regarding user identity, digital security, and regulatory oversight, which may discourage widespread adoption. The absence of a centralized authority contributes to operational arbitrariness and raises questions around reliability, accountability, and assurance. Furthermore, the market remains susceptible to speculative attacks and abrupt shifts in the perceived value of digital assets.

Nevertheless, cryptocurrency holds promise. It has the potential to contribute meaningfully to the creation of new financial systems that could support institutional resilience and long-term financial strength. Beyond improved networking capabilities, digital currencies may also lay the groundwork for more robust foundations that enhance their value and credibility. eventually reaching parity with physical currencies recognized by governments and monetary authorities.

Encouragingly, several economies have begun integrating cryptocurrency into legislative frameworks, with some classifying it as an asset under monetary authority’s regulation. This would allow for regularization, increase legitimacy, and drive investor confidence opening doors for broader opportunities in human capital development and resource mobilization, driving local economic growth. With further technological and financial innovations, such as improved user security, enhanced system protections, and reduced price volatility, cryptocurrency has a promising path. These developments may lead to a more sustainable and resilient digital financial market.

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About the Authors

Rafael Alfonso R. RemoRafael Alfonso R. Remo served as a junior economist at Oikonomia Advisory & Research, Inc. with a Bachelor of Science in Economics & Public Policy from San Beda University – Manila. His research interest is in maritime economics and human capital development of overseas Filipino seafarers.

John Paolo RiveraJohn Paolo R. Rivera is a senior research fellow at the Philippine Institute for Development Studies where he is involved in the study areas of macroeconomics, tourism development, trade and industry. He also founded Oikonomia Advisory & Research, Inc. He is the recipient of the 2024 Outstanding Young Scientist in the field of Economics by the Department of Science and Technology – National Academy of Science and Technology, Philippines.

References

[1] An innovative payment network and a new kind of money that uses peer-to-peer technology to operate with no central authority or banks; managing transactions and the issuing of bitcoins is carried out collectively by the network.

[2] Other forms of cryptocurrency include Ethereum, Litcoin, Ripple, among others.

Understanding Market Moves: A Look at Order Flow and Technical Analysis

Understanding Market Moves: A Look at Order Flow and Technical Analysis

Introduction

In the dynamic world of financial trading, understanding market movements is crucial for success. Traders have long relied on various methods to decipher these movements, with order flow and technical analysis being two of the most prominent approaches. This article delves into these methodologies, providing a comprehensive guide to understanding how they work individually and how they can be combined to enhance trading strategies.

The Basics of Order Flow

Order flow refers to the process by which buy and sell orders are submitted and executed in the financial markets. This concept involves tracking the orders that traders place to foresee potential market movements.

Key Concepts in Order Flow

  • Bid and Ask: The bid price is what buyers are willing to pay, while the ask price is what sellers want to receive.
  • Order Book: A list showing buy and sell orders at various price levels.
  • Liquidity: Refers to the ability to buy or sell an asset without causing significant price changes.
  • Volume: The number of contracts or shares traded in a security or market during a given period.

Understanding these concepts allows traders to predict possible price changes based on the activity of other market participants.

Tools for Analyzing Order Flow

Several tools help traders analyze order flow effectively:

  • Bookmap: A popular visualization tool that provides real-time insights into order book data.
  • Depth of Market (DOM): Displays the number of open buy and sell orders for a particular asset at different prices.
  • Time and Sales (or Tape Reading): Provides detailed information about each trade that has occurred, including time, price, and volume.

These tools offer traders an edge by providing detailed insights into market dynamics that are not visible through traditional charts.

Introduction to Technical Analysis

Technical analysis is the study of past market data, primarily price and volume, to forecast future price movements. Unlike order flow, which focuses on current market activity, technical analysis relies on historical data patterns.

Core Principles

  • Price Discounts Everything: All known information is reflected in current prices.
  • Price Moves in Trends: Prices follow trends rather than moving erratically.
  • History Tends to Repeat Itself: Historical price patterns often recur.

These principles form the foundation upon which technical analysis is built.

Key Technical Indicators

Technical indicators are mathematical calculations based on price, volume, or open interest that help traders identify market trends.

Popular Indicators

  1. Moving Averages (MA): Smooth out price data to identify trends over time.
  2. Relative Strength Index (RSI): Measures the speed and change of price movements.
  3. Bollinger Bands: Use standard deviation around a moving average to measure volatility.
  4. MACD (Moving Average Convergence Divergence): Shows changes in momentum by comparing different moving averages.

Each indicator provides unique insights into market conditions, helping traders make informed decisions.

Combining Order Flow and Technical Analysis

While order flow provides real-time insights into current market sentiment, technical analysis offers a broader historical perspective. By combining these methodologies, traders can gain a more holistic view of the markets.

Benefits of Combination

  • Enhanced Decision Making: Access to both real-time data and historical patterns leads to more informed decisions.
  • Improved Risk Management: Understanding both current sentiment and historical trends helps better anticipate potential risks.
  • More Accurate Predictions: The dual approach increases the likelihood of accurate predictions by considering multiple data points.

This combination strategy allows traders to maximize their analytical capabilities for improved trading outcomes.

Real-World Applications

The integration of order flow with technical analysis finds extensive application across various trading scenarios:

  1. Day Trading: Short-term traders use order flow for immediate decision-making while relying on technical indicators for trend analysis.
  2. Swing Trading: Medium-term traders benefit from identifying reversals using both methodologies.
  3. Algorithmic Trading: Algorithms can be programmed to incorporate both techniques for automated decision-making processes.

Traders in different domains leverage these strategies according to their specific needs and trading styles.

Case Study: A Day in the Life of a Trader

Consider a day trader who starts their morning by analyzing pre-market order flow using Bookmap to gauge early sentiment among major players. They notice increased buying interest at specific levels for Tesla stock. Simultaneously, they check technical indicators like moving averages and RSI on their charts.

During market hours, they observe live order book changes through Depth of Market (DOM) alongside continuous updates from Time & Sales feeds displayed on multiple screens surrounding them—each providing crucial insights into real-time developments within seconds as trades occur around prices approaching significant support/resistance zones identified earlier via combined analyses earlier mentioned above this section’s narrative example setup contextually detailed above here today!

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BaaS as the Next Fintech Gold Rush

Interactive Brokers Desktop App
Photo by Tech Daily on Unsplash

Once based on phone calls, paper contracts, and in-person consultations, the brokerage industry, like many others, has undergone a dramatic transformation over the last two decades. The rise of digital platforms, apps, and AI accelerated this process even further, and today, everybody can and wants to be an investor. This revolution of financial markets, going hand in hand with the evolution of modern banking, is not only about convenience, but also about inclusion.

New fintech companies and start-ups, even those not financially inclined, look to offer their clients investment possibilities directly on their platforms. But building all the structure and tools necessary for offering such services is not a walk in the park, it requires investing a lot of time and resources, which not every rising FinTech actor has. That’s where Brokerage as a Service comes into action. Just like “Banking as a Service”, this model has instantly gained popularity, and it’s hard to overestimate its potential. To put it simply, BaaS allows companies to integrate investing functions into their platforms without the need to build a complex brokerage infrastructure themselves. This way, you can turn virtually any app into an investment platform.

Massive Market Demand

Investing is no longer reserved only for the Wall Street “Wolves” who act as the gatekeepers of all the essential tools and real-time data needed for investing. The rise of new-fangled commission-free investing platforms, global access to financial education, and the investing boom that came with the pandemic created a new generation of retail investors. This new class of consumers expects their financial platforms to be multifunctional, and they want to invest directly from their budgeting or banking apps, which have to keep up with the demand if they want to stay relevant and keep making a profit. BaaS seems like a no-brainer for those who want to make the necessary updates quickly.

Lowering the Entry Barriers

Building a brokerage firm no longer requires immense capital, years of infrastructure development, and tons of regulatory licences. Brokerage as a Service tore those barriers down. Today, a new bank or any fintech startup can launch investing features within months, simply by hiring a BaaS provider and letting them handle the custody, trade execution, compliance, and clearing. This has significantly lowered the threshold for competition and innovation in the investing area, and we can see more and more actors entering from sectors previously not connected with finances, including wellness apps, telecom services, or gaming platforms.

Revenue Opportunities

Brokerage features offer more than just user engagement. They can be a direct revenue stream. Platforms can now monetize through transaction fees, interest on uninvested cash, or revenue sharing with their BaaS provider. These new investment tools also boost LTV (lifetime value) and user stickiness, which is another term for user retention. This can turn any given financial product from a one-time service into a long-term relationship.

Global Scalability

Even though it was born in the US, Brokerage as a Service spread across the globe like a wildfire, democratizing the investing world. In areas like Africa, Asia, and Latin America, where traditional brokerage access has been limited, companies like Nigerian Bamboo, Indian Vested are now using BaaS providers to bring global equities to users who were previously shut out of the market.

Considerations and Challenges

Looking ahead, it’s easy to tell that Brokerage as a service is bound to grow explosively, but despite all its promises and shiny-looking future, BaaS is not without its complexities. One especially challenging subject is how varied the legal landscape is in each country and how difficult it is to navigate it for a BaaS provider without exposing any of their clients, or themselves, to legal risks. Security and data privacy are also key, and any company that wants to enter into the business must take the highest measures and invest in a robust cybersecurity infrastructure to avoid losing their clients’ trust.

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Court Strikes Down Trump’s Emergency Tariffs, Citing Overreach

Close up of wooden judge gavel over the american

A federal court on Wednesday blocked former President Donald Trump’s sweeping global tariffs, ruling that he overstepped his authority under emergency economic powers. The decision, issued by the U.S. Court of International Trade in Manhattan, halts key levies on goods from China, Mexico, and Canada and casts doubt on the future of Trump’s controversial trade agenda.

A three-judge panel unanimously declared that Trump’s use of the International Emergency Economic Powers Act (IEEPA) to impose import duties was unlawful. The ruling targets the so-called “Liberation Day” tariffs and other emergency measures enacted earlier this year to curb fentanyl trafficking and retaliate against trade partners.

“The worldwide and retaliatory tariff orders exceed any authority granted to the President by IEEPA,” the court wrote in its opinion, issuing a permanent injunction to block their enforcement. A 10-day window was granted for administrative adjustments.

The administration quickly appealed the decision Wednesday night, leaving the status of the tariffs in limbo and signaling a likely legal battle that could reach the Supreme Court.

The court’s decision does not affect tariffs on autos, steel, aluminum, or other items imposed under separate trade laws. However, the halted duties—30% on China, 25% on select Mexican and Canadian goods, and 10% across most imports—had weighed heavily on both businesses and consumers.

Stock markets surged after the news. Dow futures climbed 500 points in afterhours trading, with broader indices also showing gains.

The lawsuit was led by libertarian legal group Liberty Justice Center and brought on behalf of small businesses, including wine importer VOS Selections. A parallel suit by twelve Democratic-led states, including Oregon, challenged the constitutionality of Trump’s unilateral tariff actions.

“This ruling reaffirms that our laws matter, and that trade decisions can’t be made on the president’s whim,” said Oregon Attorney General Dan Rayfield.

Legal experts were surprised by the verdict. “The reason it’s a surprise is that plaintiffs almost never win in challenges to presidential emergency powers,” said Gary Clyde Hufbauer of the Peterson Institute for International Economics.

Critics of the decision called it judicial overreach. “The judicial coup is out of control,” wrote Trump adviser Stephen Miller on X.

Still, the ruling was hailed as a potential turning point for small and mid-sized businesses struggling under rising import costs. “They want certainty,” said Jeffrey Schwab, lead attorney for Liberty Justice Center. “This decision offers that hope.”

The case now moves to the U.S. Court of Appeals for the Federal Circuit. If upheld, it could significantly rein in executive power on trade and reshape U.S. tariff policy for years to come.

Related Readings:

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Reciprocal tariffs, trade war between The United state of America and China. Trump Trade Tariffs policy.

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Trump Weighs New Russia Sanctions as Peace Memo Fails to Materialize

USA and Russia ceasefire

President Donald Trump is considering fresh sanctions on Moscow after Russian President Vladimir Putin failed to deliver a promised ceasefire proposal more than a week after a phone call between the two leaders, according to US officials.

The expected “memorandum of peace” — which Putin reportedly agreed to send outlining Russia’s conditions for halting its war on Ukraine — has yet to arrive in Washington, fueling frustration in the White House.

Trump, angered by Russia’s intensified missile and drone assaults over the weekend that left dozens dead, signaled Sunday that he might escalate pressure. “He’s killing a lot of people,” Trump said of Putin. “I don’t know what’s wrong with him.”

The president also lashed out on Truth Social, warning the Kremlin: “He’s playing with fire!”

Despite mounting pressure from both Republican and Democratic lawmakers to enact stricter penalties, Trump has not finalized any new measures. His aides say he remains concerned that harsher action could derail fragile diplomatic progress.

Still, options for expanded sanctions — including those targeting Russia’s banking system and nations buying Russian energy — remain on the table. A bipartisan Senate bill backed by over 80 lawmakers seeks to impose sweeping penalties, including steep tariffs on Moscow’s oil trade.

The diplomatic row spilled onto social media Tuesday, with Russian official Dmitry Medvedev warning Trump’s envoy Keith Kellogg of “WWIII” in response to the president’s post. Kellogg pushed back, saying the US still awaits Russia’s proposal and urging an immediate ceasefire.

Russia’s foreign ministry confirmed it is drafting a memorandum that would outline principles for ending the war, but gave no timeline. Ukraine has dismissed the move as a stalling tactic.

European leaders, once aligned with Trump’s hesitation, now appear to be losing patience. French President Emmanuel Macron said Monday he hopes Trump will “translate his anger into action.”

Related Readings:

Trump to Lift Sanctions on Syria After Assad Regime's Fall

U.S. Shifts Ukraine Policy at UN

Why More Kiwis Are Choosing Real Money Casinos Over Free Games

New Zealand High Resolution Casino

New Zealand, 26 May 2025 – A growing number of online players in New Zealand are making the switch from free casino games to real money casinos, as the appetite for authentic gaming experiences and the thrill of real wins continues to rise.

Recent trends show that Kiwi players are no longer content with demo slots and practice rounds. Instead, they are increasingly seeking out real money casinos in New Zealand that offer licensed, secure, and mobile-friendly platforms with actual cash payouts.

What Real Money Casinos Offer That Free Games Don’t

The difference between free and real money casino games goes far beyond stakes. Real money platforms offer a more complete and rewarding experience:

  • Real cash prizes: The most obvious benefit — you can actually win and withdraw real money.
  • Exclusive features: VIP programmes, cashbacks, and progressive jackpots are only available when playing with real funds.
  • Live dealer games: These immersive, studio-quality games are rarely, if ever, offered in free mode.
  • Higher-quality gameplay: Many software studios reserve enhanced features like bonus rounds and full RTP versions for real money play.

This richer gaming environment is one reason players are migrating from casual demo platforms to full-featured real money casinos.

Expert Insight: What the Data Shows

“We’ve noticed a significant increase in traffic from users searching for legitimate real money casinos in New Zealand,” says Terri Radford, site analyst at PlayCasino.co.nz. “More players are looking for platforms that are licensed, safe, and payout-focused — and they’re willing to deposit real funds for a premium experience.”

He adds: “A lot of users tell us they started on free games, but once they understood how bonuses worked, they wanted to try real money casinos. Our guides and reviews help them make informed choices and avoid risky or unlicensed operators.”

Why Real Money Casinos Are Trending in NZ

Several factors are contributing to this national shift:

  • Increased trust in online casinos new zealand platforms due to tighter global regulation.
  • Easier payments via NZ-friendly options like POLi, bank transfers, and crypto.
  • Mobile-first design, allowing seamless real money play on phones and tablets.
  • Better bonuses: Real money players can access deposit bonuses matches, free spins casinos, and exclusive promotions.

As more New Zealanders explore these benefits, the real money segment is quickly outpacing free-to-play alternatives.

How to Start Playing at Real Money Casinos Safely

If you’re ready to try real money play, here are three key steps:

  1. Choose a licensed NZ-friendly site: Look for casinos regulated by respected bodies like the MGA or UKGC.
  2. Start small: Begin with a modest deposit and use a welcome bonus to stretch your budget.
  3. Understand the terms: Bonus wagering requirements and withdrawal limits can vary.

Where NZ Players Can Find the Best Real Money Casinos

With hundreds of sites online, it can be difficult to know which casinos are safe, fair, and actually worth your time. That’s why savvy players are turning to PlayCasino.co.nz — New Zealand’s most trusted resource for discovering real money casinos.

The site offers expert reviews, comparisons, bonus rankings, and transparent safety checks, helping players confidently choose the right platform for their needs.

Whether you’re a casual player ready to make your first deposit or a seasoned gamer searching for better rewards and faster payouts, PlayCasino.co.nz makes it easy to find the best real money casinos in New Zealand.

A Broader Shift in NZ’s Online Gambling Landscape

This migration toward real money gaming reflects a broader change in how Kiwis approach digital entertainment. As mobile data gets cheaper, payment systems improve, and regulatory awareness grows, more players are embracing the full experience of real money gaming and mobile casinos — not just for the thrill, but for the genuine rewards.

Industry analysts expect New Zealand real money casino market to keep growing steadily through 2025 and beyond.

For more information or to explore the top-rated real money casinos in NZ, visit PlayCasino.co.nz.

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