Technology

• ExpressVPN study finds 85% of bosses admit to using employee monitoring software
• Employers think it builds trust, morale and productivity
• Workers feel stressed and anxious, faking productivity

New research has revealed a shocking 85% of bosses monitor staff online activity through software.

The figures from online privacy company ExpressVPN relate to all types of workers, with the research following previous data from the company revealing 78% of remote workers are monitored, too.

Bosses are now widely tracking emails, websites, keystrokes and even monitoring screens in real-time to keep an eye on their workers’ productivity, however nearly half of workers are feeling the pressure, and the surveillance could actually be causing them to be less productive.

Employee monitoring software is all too common

Two in five (42%) workers believe that monitoring should be considered unethical, with more than half (51%) willing to quit if they’re being subjected to online monitoring. However, four in five (83%) employers enforce monitoring without the option for employees to opt out.

A clear disconnect has been identified, with 70% of employers believing that monitoring boosts trust, morale and productivity. On the flip side, 46% of workers feel stressed or anxious about it.

Over a third (35%) feel that they lack their employer’s trust, and one in four (26%) feel pressure to do work quickly rather than thoughtfully. Pressure to be active rather than productive and pressure to work longer hours were also identified, raising questions over how effective monitoring tools are at determining productivity, rather than just working hours.

Scheduling emails to send later, logging into communication apps on mobile devices and setting up automated status changes are just some of the ways workers are now using to fool monitoring systems.

Employer observations aren’t just being used to keep tabs on perceived productivity, though – 38% use the data for performance reviews, with 30% of employees facing warnings and 17% facing pay cuts or suspensions as a consequence of misbehavior.

Looking ahead, workers are calling for stronger government regulation to protect their privacy: “The call for regulation reflects a deep-seated desire for accountability, fairness, and respect in a workplace where privacy can often feel like a luxury.”

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Cybercrime is a costly affair, with nearly £11.5 million stolen last Christmas alone, according to the UK's National Cyber Security Centre. That’s £695 on average per victim. With the festive season in full swing, the rush to snag post-Black Friday bargains and buy Christmas gifts online has led to a sharp rise in threat levels. For cybercriminals, this is the perfect opportunity to deploy their latest techniques, targeting unsuspecting shoppers to steal money and personal data.

UK Fraud Minister Lord Hanson issued a stark warning in November on the dangers of holiday scams. However, the sheer volume of online interactions, the sophistication of cyberattacks, and the increasing reliance on digital shopping during the holiday season make it far more challenging to identify a scam at first glance.

AI-Driven Phishing: More Deceptive Than Ever

Phishing has long been one of the most common forms of cybercrime, but the emergence of AI has revolutionized the way these attacks are carried out. Previously, phishing emails were easy to spot, often riddled with spelling mistakes and strange phrasing. However, with AI, cybercriminals can now analyze the communication styles of businesses, studying their marketing emails and messages to replicate the tone, branding, and even the content of legitimate communications.

Attackers can now seamlessly impersonate colleagues, executives, and even customers, making it harder for targets to identify a scam. It has become easier–and cheaper– than ever to undertake these targeted spear-phishing attacks, which are much more likely to succeed.

AI and Human Behavior: Exploiting Vulnerabilities

AI’s ability to analyze human behavior has also made it easier for cybercriminals to exploit psychological triggers. By studying past interactions and identifying patterns in behavior, attackers can craft messages that play on an individual’s emotions. For example, during the busy holiday season, cybercriminals exploit the stress of missed package deliveries. Imagine receiving a seemingly legitimate text from a courier service, urging payment for redelivery. One victim, distracted and eager to resolve the issue, entered card details on a convincing fake site—only to realize later the text came from an unknown mobile number, not the courier. It’s a reminder that vigilance can’t take a holiday.

AI can also be used to time phishing emails or fake social media ads to coincide with busy shopping periods such as Black Friday and Christmas sales. Cybercriminals can also create fake websites offering massive discounts or time-limited offers, hoping to lure in shoppers eager to make a purchase quickly. Under pressure, people are more likely to fall for scams.

In the same way, AI can be used to create fake bank alerts or financial notifications that play on a customer’s fear of fraud or account security issues. These phishing attacks, which often contain urgent warnings or threats, push the recipient into a state of panic, encouraging them to click on a malicious link or provide sensitive details. It can also be very hard to spot when the destination site or notifications look identical to the official source.

In fact, while it may seem simple to check if a website is secure by looking for the HTTPS prefix or a padlock icon, these are no longer foolproof indicators of a secure site. Cybercriminals have become adept at creating fake sites that look identical to trusted brands, making it easy for consumers to be misled.

Deepfake Technology: Social Engineering with a New Face

Alongside phishing, AI is increasingly being used in social engineering attacks, particularly through deepfake technology. Earlier last year, ARUP lost $25 million to fraudsters after an employee was tricked into believing he was carrying out the orders of his CFO. And everyday people aren’t immune either. A kitchen fitter from Brighton was scammed for £76,000 because he believed a deepfake advert purporting to be Martin Lewis, the money-saving expert.

This method is highly effective because it bypasses traditional security measures we rely on, such as email filters, multi-factor authentication, or the ‘sniff test’, which means that something is awry. Deepfakes create a sense of urgency and authority, making it easier to manipulate people into taking actions they would otherwise refuse. And their realism, especially when duplicate social media profiles are concerned, makes such scams harder to detect, even for those with extensive training.

Protecting Against AI-Enhanced Threats

As the sophistication of AI-driven phishing and social engineering attacks grows, it is essential for both businesses and consumers to adopt proactive security measures. For individuals, vigilance is key. Avoid clicking on links in unsolicited and junk emails, texts that claim to come from businesses or government agencies, or even ads seen on social media platforms. Always manually type in the URL of a website, rather than clicking on embedded links, to ensure that you are visiting a legitimate site.

Multi-factor authentication should also be implemented wherever possible, as it adds an additional layer of security beyond traditional login credentials. Password managers can also help users create and store strong, unique passwords for each account, reducing the risk of credential theft. Passkeys, which rely on biometrics and device management, are the next level of protection that is slowly being adopted.

For businesses, investing in advanced threat detection and response systems is essential. These systems can identify and mitigate phishing and social engineering attacks before they cause significant damage. Machine learning algorithms within these systems can detect patterns of malicious activity that traditional security measures might miss. Regular employee training is also crucial, as the human element remains one of the most vulnerable points of attack.

Moreover, businesses should work to ensure that their employees and customers are aware of the risks posed by deepfakes and other forms of AI-driven social engineering. Implementing robust verification processes, such as requiring multiple confirmations for financial transactions, can also help reduce the risk of falling victim to these kinds of scams. Ultimately, staying ahead of evolving AI threats requires collective vigilance and a stronger commitment to safeguarding personal information.

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This article was produced as part of TechRadarPro's Expert Insights channel where we feature the best and brightest minds in the technology industry today. The views expressed here are those of the author and are not necessarily those of TechRadarPro or Future plc. If you are interested in contributing find out more here: https://www.techradar.com/news/submit-your-story-to-techradar-pro

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• Nvidia's new RTX 5080 GPU performs better than AMD's Radeon RX 7900 XTX at raw rasterization and ray tracing
• DLSS 4 performance takes it further, while the RX 7900 XTX only has FSR 3 for now
• Scalping could leave many people buying AMD GPUs instead

The best of Nvidia's RTX 5000 series GPUs are finally here, with the RTX 5090 ($1,999 / £1,939 / AU$4,039) and the RTX 5080 ($999 / £939 / AU$2,019) launching yesterday. With comparisons now out in the wild, it's clear to see that the RTX 5080 defeats AMD's Radeon RX 7900 XTX while sitting at the same listed price - although the chances of finding one at that price are slim.

At both raw rasterization and (unsurprisingly) ray tracing performance, Team Green's RTX 5080 comes out on top against its rivals' flagship RX 7000 series GPU in several games as evident in Gamer Meld's comparison on YouTube (available below). Whilst it isn't by a huge margin (at least in raw rasterization), it completes the job the previous generation's RTX 4080 Super set out to do.

Examples of this are notable in Black Myth: Wukong, as the RTX 5080 scored an average frame rate of 42fps versus the RX 7900 XTX's 32fps at 4K max graphics settings with no upscaling or ray tracing, a 27% performance difference. With RT Overdrive enabled in Cyberpunk 2077 at 4K max graphics settings and upscaling on (performance mode for both), the RTX 5080 had an average of 59.84 fps versus the 7900 XTX's 30.02 fps.

It's worth noting that this is while Team Green's powerhouse GPU was using DLSS 4 and the RX 7900 XTX was using FSR 3 - you could call it an unfair comparison, but Team Red's FSR 4 will only be available for RDNA 4 GPUs (at least for now), and the GPU in question isn't one of them. We will have to wait just a little longer for more information on what the new RX 9070 series offers (especially while using FSR 4), and whether this could stack up to Nvidia's offerings.

Unless you're lucky enough to grab an RTX 5080 FE before scalpers, you likely won't get it at its listed price

Now, this may be a circumstance where I'd recommend sticking with AMD's RX 7900 XTX if you already own the GPU - the RTX 5080 FE would likely be the better option going forward (especially if DLSS 4 is better than FSR 4), but the scalpers will likely be the main obstacle to stop you from purchasing it at reasonable prices.

We've seen this happen on numerous occasions with Nvidia's GPUs and other PC hardware, so expect it to be the same case here. It'll likely be much worse for those chasing the RTX 5090 with its $1,999 / £1,939 / AU$4,039 price (which I frankly don't think is worth it if you already own an RTX 4090).

While Nvidia's RTX 5080 is the stronger GPU, the RX 7900 XTX doesn't stray too far behind in raw rasterization - ray tracing and upscaling are great don't get me wrong, but I've already stated that this shouldn't be the deciding factor for a GPU purchase.

Both GPUs are at the same listed price, with third-party options of the RX 7900 XTX at lower prices (since it's been out for 2 years) so it would be the easy and most affordable option in this case - but once more users catch wind of performance comparisons, you'll likely see the RX 7900 XTX disappear from online retailers too with low stock. A potential purchase of the RTX 5080 is entirely down to whether you own AMD's GPU already or a GPU that's weaker on either Team Red or Team Green's end.

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Traditionally seen as number crunchers handling compliance and bookkeeping, accountants are now evolving into strategic advisers, helping businesses navigate challenges and identify growth opportunities. This shift is being driven by tools like automation, artificial intelligence (AI), financial management software (FMS) and cloud-based systems, which enable accountants to deliver insights and advice far beyond traditional expectations.

According to the 2024 Intuit QuickBooks Accountant Technology Survey, 50% of accounting firms plan to increase their technology investments in the coming year. This demonstrates the growing importance of technology in enhancing efficiency and equipping accountants to meet the increasingly complex needs of businesses.

Financial management systems (FMS) are one of the most transformative tools helping businesses to automate routine tasks, provide real-time financial insights, and empower accountants to move beyond transactional roles, becoming proactive, forward-looking advisers who deliver significant value to their clients.

Here are three ways that FMS enable accountants to provide greater value and become trusted business partners for SMBs:

1. Automating Time-Consuming Tasks

For decades, accountants spent much of their time on routine tasks such as bookkeeping, tax preparation, and data reconciliation. While these activities are critical, they often leave little room for strategic planning or advisory work. Today, automation tools and FMS are transforming this dynamic by taking over repetitive processes, allowing accountants to focus on delivering meaningful value.

Automation reduces the potential for errors while significantly increasing efficiency. With routine tasks streamlined, accountants can spend more time providing timely, actionable insights tailored to their clients’ needs. For SMBs, this access to precise financial data and expert advice is invaluable, enabling them to address unique challenges with confidence outside of simply accounting. This shift allows accountants to dedicate their expertise to areas like profitability analysis and long-term financial planning, cementing their role as proactive advisers.

2. Guiding Clients on Cash Flow Management

Cash flow is the lifeblood of any business, and effective management is often the key to success. Modern FMS tools provide real-time financial insights that empower accountants to help clients monitor their income and expenses more effectively. This capability allows businesses to predict potential cash shortages, plan for upcoming financial needs, and maintain overall stability.

By leveraging real-time data, accountants can identify and address cash flow issues before they become critical. Through close collaboration with their clients, they implement strategies to optimize cash reserves and reduce unnecessary costs. This hands-on approach not only enhances financial stability but also fosters a sense of trust between accountants and the businesses they support. As a result, SMBs are better equipped to navigate day-to-day operations and prepare for growth opportunities.

3. Delivering Insights Beyond Compliance

Gone are the days when accountants were solely focused on ensuring regulatory compliance. With technology adoption, accountants can analyze financial trends, model different scenarios, and offer tailored recommendations that directly impact business performance. These capabilities allow accountants to confidently guide businesses, helping them make informed decisions that drive success.

This evolution from reactive to proactive service delivery has redefined the accountant-client relationship. Accountants are no longer responding to financial events as they occur but are instead anticipating challenges and identifying opportunities. This transformation aligns their services with the strategic priorities of modern businesses and solidifies their role as indispensable partners in growth and innovation.

First Things First: Speak to an Accountant

Despite the clear benefits, some small business owners remain cautious about adopting FMS due to concerns over cost, complexity, and implementation. Speaking with an accountant or financial advisor is an essential first step in overcoming these barriers and ensuring the best tools are chosen for your business goals. These professionals offer expert guidance to help you identify scalable, customizable solutions tailored to your specific business needs.

They simplify the transition process, breaking implementation into manageable steps and providing training to ensure confidence in using the new system. Moreover, they can share real-world success stories and demonstrate how similar businesses have benefited from adopting these tools. This expert support ensures a smoother transition, empowering small businesses to embrace technology to drive growth and efficiency.

The Long-Term Implications of Technology Adoption

The integration of technology into accounting is not just a trend; it’s a necessity for long-term success. Accountants who embrace these tools can deliver high-value services that strengthen client relationships and foster business growth. For SMBs, adopting FMS means achieving operational efficiency, reducing errors, and gaining the insights needed to make confident, strategic decisions. Together, these advancements position both accountants and SMBs to thrive in an increasingly complex financial landscape.

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This article was produced as part of TechRadarPro's Expert Insights channel where we feature the best and brightest minds in the technology industry today. The views expressed here are those of the author and are not necessarily those of TechRadarPro or Future plc. If you are interested in contributing find out more here: https://www.techradar.com/news/submit-your-story-to-techradar-pro

Back in October, I met with a young German start-up CEO who had integrated the open-source approach by DeepSeek into his Mind-Verse platform and made it comply with German data privacy (DSGVO) standards. Since then, many rumors have been circulating that China has chosen a different architectural structure for its foundation model—one that relies not only on open source, but is also much more efficient, requiring neither the same level of training data nor the same compute resources.

When it comes to DeepSeek, this is not a singular “breakthrough moment.” Rather, AI development continues on an exponential trajectory: progress is becoming faster, its impact broader, and with increasing investment and more engineers involved, fundamental breakthroughs in engineering and architecture are just beginning. Contrary to some market spokespeople, investors, and even certain foundation model pioneers, this is not solely about throwing infinite compute at the problem; we are still far from understanding core aspects of reasoning, consciousness, and the “operating model” (or software layers) of the human mind.

Additionally DeepSeek is (was) not a government-sponsored initiative; supposedly, even the prime minister was surprised and visited Hangzhou to understand what was happening. Although Scale AI founder Alexander Wang claims that China already has a significant number of powerful H100 GPUs (about 50,000), yet—based on U.S. export laws—this fact is not publicly acknowledged. DeepSeek is reported to have only about 150 engineers, each earning in the range of $70–100k, which is eight to ten times lower than top engineering salaries in Silicon Valley.

So, regardless of whether they have powerful GPUs or whether $6 million or $150 million was invested, it is nowhere near the billions—or tens of billions—poured into other major AI competitors. This example shows that different engineering and architectural approaches do exist and may be waiting to be uncovered. Most likely, this is not the ultimate approach, but it also challenges the current VC narrative that “it’s all about compute and scale.” Moreover, the open-source mindset behind DeepSeek challenges the typical approach to LLMs and highlights both the advantages and the potential risks.

Sam Altman is rumored to be hosting a “behind-closed-doors” meeting with the Trump administration on January 30th, where he plans to present so-called “PhD-level” AI agents—or super agentic AI. How “super” this will be remains unclear, and it is unlikely there will be any public declaration of achieving AGI. Still, when Mark Zuckerberg suggests Meta will soon publish substantial progress, and Elon Musk hints at new breakthroughs with Groc, DeepSeek is just another “breakthrough” that illustrates how fast the market is moving.

Once agentic AIs come online, they introduce a structural shift: agentic AI is not about merely responding to a prompt, but about pursuing a goal. Through a network of super agents, massive amounts of data are gathered and analyzed, while real products and tasks are delivered autonomously. What is interesting about Sam Altman not making a public appearance and release, his meeting with the U.S. The government hints at potential risks and consequences.

We are at the Verge of Hyper-Efficiency and Hyper-Innovation

What we are seeing is the compound effect of investment and ever-growing teams working on these models, with few signs of a slowdown. Needless to say, any quantum breakthroughs would be the next frontier—essentially “AI on steroids”—where the magnitude of change could increase exponentially. On the positive side, this can unleash innovations in health and medicine like never before in human history.

In the near future, broader access to AI tools will probably benefit infrastructure providers and hyperscalers such as AWS. It is unclear if this will put NVIDIA at a disadvantage or actually benefit it: as “everyone” joins the AI race, there could be more demand for compute, not just from big U.S. tech players like OpenAI. Meanwhile, Anthropic and OpenAI run closed ecosystems, but DeepSeek’s public paper shares many of its core methods.

The greatest risk to the U.S. and its current AI dominance is that China does have talent and the strong work ethic to keep pushing forward. Trade sanctions won’t stop that. As more engineers come together and keep working, the odds of major breakthroughs increase.

The Battle of Distrust

Globally, the U.S. is losing trust. The “don’t trust China” narrative is fading in many parts of the world. While Donald Trump on the surface gains respect, global leaders are quietly looking for alternatives in the background to mitigate. Europe and other Asian nations don’t want to be “hostage” to U.S. technology and will open up to new options.

Technology doesn’t evolve overnight, and we’ve only seen the start of the breakthroughs to be announced by Groc, Meta, and OpenAI. Simultaneously, new capital will continue pouring in, and other regions will join the race, now that it’s clear money alone isn’t everything. The future might not necessarily be bad for NVIDIA, either, since data centers could appear everywhere, enabling a more global roll-out of AI and creating opportunities for many.

From Prompting to Action

There are still numerous smaller AI companies that have received massive funding purely on hope and hype. Yet new approaches to foundation models—via architectural and engineering innovation—can continue to drive progress. And once we “hack” biology or chemistry with AI, we may see entirely new levels of breakthroughs.

Looking toward the rest of 2025, we can expect more “super-agent” breakthroughs, as agentic AI and LQMs (Large Quantitative Models) push generative AI beyond fun language-based tools to genuine human worker replacements. Not only will financial modeling and analysis be optimized, but also execution—the entire cycle of booking, planning, and organizing—could shift to autonomous agents. Over time, these integrated, adaptive agents will replace more and more use cases where humans currently remain in the loop. This might also be one of the biggest threats to society: coping with extreme pressures on market economies under hyper-efficiency and hyper-innovation. In 2025, we are likely to see breakthroughs in education, science, health, consulting, and finance. With multiple compounding effects in play, we’ll likely experience hyper-efficiency and widespread growth.

However, the looming threats are real. Agentic, at-scale AI can still fall victim to hallucinations, and now anyone with a few million dollars can build their own model—potentially for malicious use. While a global, open approach to AI can be positive, many engineering and research challenges remain unsolved, leaving high risks. With the U.S. laser-focused on AI, the race to surpass human-level intelligence is on.

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This article was produced as part of TechRadarPro's Expert Insights channel where we feature the best and brightest minds in the technology industry today. The views expressed here are those of the author and are not necessarily those of TechRadarPro or Future plc. If you are interested in contributing find out more here: https://www.techradar.com/news/submit-your-story-to-techradar-pro

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