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Tag: Technological debt

  • Technology debt is on the rise. Why is 278 days of delay a risk to business?

    Technology debt is on the rise. Why is 278 days of delay a risk to business?

    Today’s software development dynamics resemble a race in which the event horizon moves faster than the navigation systems can process it. In a culture focused on instant market gratification, the term Time-to-Market has become one of the main markers of success. However, beneath the shiny façade of innovation, in the foundations of digital ecosystems, there is a growing phenomenon that, in financial terms, could be described as toxic variable-rate credit. The latest data from Datadog’s ‘State of DevSecOps’ report casts a harsh light on this reality: not only is the tech industry failing to close the security gap, it is actually allowing it to expand freely.

    The illusion of speed in the digital arms race

    A common cognitive error in strategic management is to equate the speed of implementation of new functionality with the overall agility of the organisation. Meanwhile, modern software is rarely a work of authorship in the full sense of the word. Rather, it is an intricate construction erected from prefabricated components – libraries, modules and external services. This modularity, while providing unprecedented speed of work, introduces elements into the company’s bloodstream over which control is often illusory.

    Today, almost nine out of ten companies operate in a production environment that has at least one known and actively exploited security vulnerability. This is a statistic that should be a cause for concern not only in technical departments, but especially in boardrooms. For it means that the majority of the digital assets of a modern business are operating in a state of permanent exposure to risk, which is not a fault of the system, but a structural feature of it.

    A new unit of risk measurement: Anatomy 278 days

    A key indicator of the health of digital infrastructure has become the ‘backlog’ of dependencies, which has extended to an alarming 278 days in the last year. That’s almost ten months during which an organisation is using solutions with known flaws, while their safer alternatives are already available on the market. The increase in this delay by more than two months in just one year is indicative of the progressive inefficiency of upgrade processes.

    From a business perspective, these 278 days are when technology debt becomes a real burden on the balance sheet. Every out-of-date library is an ‘open door’ through which an uninvited visitor can pass at any time. Such a long delay in systems maintenance is a form of gambling in which the operational continuity of the company is at stake.

    The trap of ‘free’ components and trust architecture

    The open source model and off-the-shelf workflows such as GitHub shares have revolutionised programming efficiency. They allow small teams to build systems at a scale that a decade ago required armies of engineers. However, what is free in the licensing sense is rarely free in the accountability sense. Half of today’s enterprises deploy new versions of external libraries almost as soon as they are published, often without in-depth analysis of the code changes.

    This approach sets a dangerous precedent. CI/CD pipelines, the digital arteries through which code flows from the developer to the customer, are becoming a critical hotspot. The lack of rigorous control over the versioning of external components means that changes made by third parties, not necessarily with pure intentions, can seep into the organisation. In this way, the software supply chain ceases to be a secure tunnel and becomes an exposed commercial tract.

    The transparency paradox and the role of artificial intelligence

    Contrary to popular belief, the main obstacle to building secure systems is not the speed of development per se, but the lack of clarity in the maze of technological interconnections. Cloud environments have reached a level of complexity that is beyond the perceptual capabilities of a single individual or even entire expert teams. Herein lies the tension field between the need for automation and the need to maintain critical judgement.

    The phenomenon of over-warning, where safety systems generate thousands of ‘critical’ alerts, has led to a kind of decision-making desensitisation. When everything is on fire, the focus is on extinguishing the nearest flames, not necessarily the most dangerous ones. The data shows that only a small fraction of theoretical vulnerabilities have a real bearing on the ability to take control of a production service. The key, therefore, becomes analytics backed by artificial intelligence that can sift the noise from the signal, pinpointing those few truly significant risks. This shift from quantitative to qualitative security management is currently the biggest challenge for technology leaders.

    Exit strategy

    A modern security strategy must evolve towards processes that are an immanent part of value creation and not just a cumbersome add-on at the end of the production cycle. This requires a redefinition of the concept of software quality. A product that is functional but based on outdated foundations should be considered defective in today’s market reality.

    A key element of this transformation is the implementation of a strict component inventory, known as the Software Bill of Materials (SBOM). Knowing exactly what the company’s technology stack consists of allows for a rapid response in moments of crisis. Furthermore, it becomes essential to prioritise so-called contextual security. Instead of blindly following the recommendations of tool vendors, organisations must learn to assess risks through the prism of their own architecture and business specifics.

  • Lenovo targets technology debt. New offensive in the area of storage and HCI

    Lenovo targets technology debt. New offensive in the area of storage and HCI

    In mid-December 2025, the IT infrastructure market received a clear signal from Lenovo that the Chinese giant intends to aggressively address the gap between the growing ambitions of AI and the outdated hardware back-up of enterprises. The company announced a major refresh of its ThinkSystem and ThinkAgile portfolios, addressing two of the most pressing concerns of today’s CIOs: insufficient storage performance for AI workloads and strategic uncertainty in the area of virtualisation.

    The decision to introduce new solutions is no accident and is a direct result of hard market data. According to IDC analysts, as much as 80 per cent of storage deployed in the last five years is still based on traditional rotating disks (HDDs). In the era of generative AI, such infrastructure is becoming a bottleneck, effectively stifling innovation. Lenovo is responding to this with its new ThinkSystem DS series of disk arrays. These are all-flash systems designed for SAN environments to eliminate data latency, while offering a simplicity of deployment that is often lacking in enterprise-class solutions.

    Equally important, the new offering is a response to the market turmoil around virtualisation platforms. Stuart McRae, executive director at Lenovo, directly points to the “unclear virtualisation strategy” in many organisations as a barrier to modernisation. The answer is to be found in the new release of hyperconverged infrastructure (HCI) from the ThinkAgile FX family. A key differentiator of these systems is their open architecture, allowing seamless migration between VMware and Nutanix solutions without replacing the hardware layer. For the partner channel, this is a strong sales argument, offering end customers real security against vendor lock-in and flexibility in their choice of software provider.

    The portfolio is complemented by solutions targeting the Microsoft and Nvidia ecosystem. The ThinkAgile MX series, integrated with Microsoft Azure Local and equipped with NVIDIA RTX Pro 6000 GPUs, clearly positions Lenovo as an infrastructure provider for edge AI processing. And for customers who prefer a Nutanix environment, there is the ThinkAgile HX series with the Nutanix Enterprise AI suite, which is expected to reduce the time to deploy machine learning models from weeks to minutes.

    Complementing the hardware offensive is the expansion of the services layer. Aware of the Gartner statistic that 63% of companies do not have adequate data management procedures for AI, Lenovo is emphasising consulting and implementation services. The whole thing is bundled with the TruScale model, which is part of the market trend away from one-off CAPEX outlays to a flexible consumption model. The December launch is Lenovo’s attempt to move forward – the company doesn’t want to be just a ‘box’ supplier, but the architect of a transformation in which hardware ceases to be a brake on business aspirations.

  • Drowning in alarms: why your SOC needs context, not data

    Drowning in alarms: why your SOC needs context, not data

    For years, there was an unwritten dogma in the cyber security industry: ‘visibility is everything’. IT departments strove to collect every byte of data, believing that full logs were a guarantee of security. Today, this strategy is becoming our biggest pitfall. With billions of connected devices, the hybrid cloud and the expansion of AI, we are drowning in alerts rather than gaining knowledge. When supply chains are as fragile as ever, the key to survival is no longer the amount of information gathered, but the speed of understanding its context.

    If we look back, the 1980s may seem like a technological idyll. Not because the systems were better – they were just finite, tangible and, most importantly, isolated. It was a time when a ‘security incident’ often meant the physical theft of a floppy disk, and fixing a bug required being physically present at the terminal. You could draw a map of your infrastructure on a piece of paper and be sure it reflected reality. You were in control of this environment because we were able to embrace it with our minds.

    The end of an era of isolation

    However, this idyll is now prehistoric. Nostalgia for the simplicity of those years is understandable, but today’s IT reality no longer resembles an orderly archive – it is a living, chaotic organism that is evolving faster than we can take note.

    Modern infrastructure has lost its boundaries. There are no longer moats and fortified walls. Every company has become a node in a global network of dependencies. Every new API connection, every SaaS service deployed by the marketing department without IT’s knowledge(Shadow IT), every IoT device plugged into the production network changes the organisation’s risk profile in real time.

    The problem is that the speed at which this landscape is changing has long outstripped the human capacity to manage it manually. We are trying to navigate this storm using maps from a decade ago. In effect, instead of controlling the environment, we are merely reacting to its convulsions.

    The digital Upside Down and technology debt

    The situation is complicated by the fact that beneath the shiny surface of modern applications, artificial intelligence and the cloud, there is a dark layer of technological ‘legacy’. This is our digital ‘Upside Down’ (referring to pop culture metaphors). We have built digital skyscrapers on foundations that remember a very different technological era.

    Many key processes in critical infrastructure, banking or logistics still depend on systems that were developed at a time when the internet was a curiosity rather than the bloodstream of the economy. This creates a dangerous paradox: an ecosystem that is simultaneously ultra-modern and historically ‘polluted’. This reflection of a modern attack surface in an outdated technical base means that it only takes one crack in an old, forgotten component to open wide the gates for attackers to the latest cloud resources.

    The butterfly effect in the supply chain

    Just how fragile this arrangement is has been amply demonstrated in recent months. Global failures, such as the CrowdStrike incident or the disruption to Amazon Web Services, have proven a brutal truth: in today’s IT, no one is an island. A bug in code at an external supplier can paralyse operations on another continent in a matter of minutes.

    A small vulnerability becomes a fuse with a disproportionately large field of fire. Cybercriminals understand this perfectly. They have stopped wasting time pushing through the main gates of the best-guarded companies. Instead, they use automation and machine learning to scan widely branching supply chains for the weakest link.

    For security teams, this means fighting an enemy that is faster and more precise. Defenders are suffering from ‘alert fatigue’ (alert fatigue). Security systems generate thousands of alerts a day. When everything is a priority, nothing is. Signals of actual attacks, which – supported by AI – are executed with surgical precision, are lost in this information noise.

    Context is the new king

    In the face of these challenges, the traditional approach of collecting data and patching every vulnerability found (CVE) is a road to nowhere. It is Sisyphean work. To regain control of the digital chaos, organisations need a paradigm shift: from incident collection to Cyber Exposure Management.

    The decisive factor ceases to be the ‘what’ (what vulnerability it is) and begins to be the ‘where’ and ‘how’ (in what context it occurs). Real security in 2024 is about being able to answer the question, “Does this particular vulnerability in an old printer in a warehouse allow an attacker to jump into our cloud database?”.

    That’s what context is. It’s understanding the attack pathways and the relationship between IT (information technology), OT (operational technology) and the cloud.

    This is where artificial intelligence must enter the game, on the defenders’ side. Not as a marketing add-on, but as a necessity. Only AI can analyse these billions of dependencies in real time, map the paths of potential attacks and point security managers to the 5% of threats that can realistically stop a business.

    Resilience is understanding

    Technologies from the 1980s can be sentimental, recalling a time when digital systems could be grasped by eye. Today, however, the reality is different – faster, denser and infinitely more complex. Companies that understand this are no longer pursuing the impossible goal of ‘complete security’ based on defensive walls.

    Instead, they build resilience through full visibility of their digital ecosystem. Those who can capture their assets in their entirety – from legacy to cloud – and classify risk in the right context, will remain capable. Whether the threat comes from AI, a vendor error or a forgotten server in the basement. In a digital world, the winner is the one who understands the connections instead of panicking.

  • Hidden IT costs a silent brake on business. They absorb up to 7 per cent of turnover

    Hidden IT costs a silent brake on business. They absorb up to 7 per cent of turnover

    In every growing organisation, the same familiar feeling emerges. A sense of ‘digital debt’, where teams spend more time maintaining, integrating and patching existing systems than creating new value. It’s a frustrating feeling that, despite a growing number of increasingly powerful tools, the job is not getting any easier.

    Until now, this has been mainly a subjective feeling, the subject of corridor conversations and sighs during project meetings. Today, however, we know what it costs.

    We can call it the ‘complexity tax’ – the systemic cost of organisational and technological friction that every scaling company pays. The recent‘Cost of Complexity Report‘ conducted by Freshworks puts a tangible price on this phenomenon. And these are no small ones. The analysis, based on responses from 700 IT, finance and business professionals, shows that this silent brake is becoming a strategic threat to competitiveness.

    Hidden R&D budget equivalent

    Let’s start with the numbers, which should give any leader food for thought. The report shows that companies lose an average of 7 per cent of their annual turnover not through market failures or bad business, but through their own internal complexity of processes and systems.

    This is not the ‘fault’ of the IT department. Rather, it is the natural entropy of growth – the larger the organisation, the greater the tendency to complicate structures. The problem is that this lost 7% is almost the exact equivalent of the amount that companies typically spend on research and development (R&D) budgets.

    The conclusion is as simple as it is worrying: the resources that should drive innovation are being consumed by internal friction. Before a company can invest in the future, it must first ‘pay back’ the costs of its complicated present. In the US alone, these losses amount to almost a trillion dollars a year, showing that this is not a peripheral problem, but a global challenge for the entire digital economy.

    The anatomy of friction, or the 15 application syndrome

    How exactly is this ‘tax’ collected? At several levels.

    The first is the ‘focus tax’, paid daily by employees. The report indicates that the average employee has to use an average of 15 different software solutions and four separate communication channels to complete their tasks. This generates a gigantic cost of context switching overhead. Employees lose almost seven hours a week to this – that’s almost one full working day given up to fighting the tools that were supposed to make this work easier.

    The second level is direct budget wastage. Around 20 per cent of all software expenditure is simply wasted. From an IT perspective, it’s not just classic shelfware (licences bought and lying on the shelf). It’s also the cost of spectacularly failed implementations, forced integrations between systems that were never meant to talk to each other, and increasing redundancy – when different departments buy their own tools to do essentially the same thing.

    The result? Digital silos are emerging. Almost half of the teams surveyed admit to working in isolation. A third suffer from a chronic lack of a central, reliable source of information. For technology teams, this means a degradation of role: instead of being architects of business value, they become ‘data plumbers’, spending their time thwarting information flows between mismatched systems.

    When the technology stack hits the human stack

    However, the biggest cost of complexity is not dollars or wasted man-hours. It is the human cost. Complexity is not a problem that stays in Excel or server architecture – it realistically affects people.

    The report brings alarming data: as many as 60 per cent of employees are considering leaving their company in the coming year. When we look at the reasons, organisational overload, frustrating and inflexible processes and permanent exhaustion caused by constant adaptation to new systems appear alongside salaries.

    This is a common pain point for business and IT. Almost one in five people surveyed admitted that they had witnessed someone close to them resign or suffer burnout due to a failed software implementation. This is a common failure. The company loses twice: once by a failed project, and a second time by losing a motivated and competent person who was fed up with fighting the system. This loss of knowledge and motivation undermines innovation in the long term more than any budget deficit.

    Simplification as an investment, not a cost

    For the past decade, we have been living in a ‘digital transformation’, often understood as an imperative to add more tools. The data clearly show that we are entering a new phase: ‘digital optimisation’. Continuing to add complexity is no longer delivering returns.

    Simplifying the IT landscape and processes is not a ‘cost-saving project’ today. It is a strategic imperative to regain agility, respond faster to customer needs and, above all, retain talent within the company.

    A company’s greatest innovation potential may not lie in the next expensive R&D project. It may lie in reclaiming that 7% of revenue – time, money and people energy – that is today wasted on a ‘complexity tax’. This is not cost-cutting. It is ‘refactoring’ the company’s operating model so that it can think about future growth at all.

  • The slogan: ‘LOUVRE’. How technological debt and years of neglect have put the Louvre at risk

    The slogan: ‘LOUVRE’. How technological debt and years of neglect have put the Louvre at risk

    The recent theft of the crown jewels from the Louvre in Paris has revealed a problem much deeper than just physical gaps in security. The IT sector’ s attention was drawn to reports of fundamental negligence in cyber security that had been ignored for years at one of the world’s most important cultural institutions.

    The French daily Libération, citing confidential documents, revealed findings sounding like the script of a 1990s hacker movie. The access password for the server managing the museum’s entire video surveillance system was ‘LOUVRE’. Other reports indicate that the password “THALES” was used for software supplied by the Thales arms company.

    These are not new problems. Already in 2014, an audit by the French national cyber security agency (ANSSI) alerted that the museum’s systems had numerous vulnerabilities and relied on extremely weak passwords.

    A key problem proved to be a deep technological debt. The Louvre’s internal networks were supposed to rely on operating systems such as Windows 2000 or Windows XP. Both of these systems have not received any security updates from Microsoft for over a decade, making them a trivial target for attackers.

    While there is no official confirmation yet whether these particular software vulnerabilities have been exploited by thieves, the situation exposes a failure in IT risk management. The fact that the basic principles of digital hygiene have been ignored for years shows that even the most prestigious institutions are not immune to the consequences of neglecting to upgrade their technology infrastructure.

  • Western banks are drowning in technology debt. A lesson that Poland cannot ignore

    Western banks are drowning in technology debt. A lesson that Poland cannot ignore

    A quiet drama is unfolding in the US and the UK. Despite trillions of dollars pumped into digitalisation, the banking sector there is losing customers on an alarming scale. Baringa reports that as many as 62% of consumers are prepared to abandon their bank for a better digital experience.

    The reason? A technological foundation from the 1960s and a code that remembers the days before the internet. This is a powerful warning and at the same time a priceless lesson for Poland, which, although in a completely different place today, must not succumb to the illusion of eternal security.

    Looking from a Polish perspective, these problems may seem remote. Our banking sector is regularly praised internationally and, according to reports such as Deloitte’s Digital Banking Maturity, is one of the world’s digital leaders.

    We are ahead of many countries in terms of the sophistication of mobile applications or the ease of opening an online account. We have managed to leapfrog an entire generation of outdated technologies that today cripple innovation in the West. This gives us a huge advantage. The question is: for how long?

    Underneath the shiny façade of award-winning applications, there is also a challenge in Poland known as technological debt. Although it is not as dramatic as in the West, it exists and is a hidden threat. Research shows that Polish financial institutions still see digitalisation as a way of catching up with their infrastructure.

    This means that even if our interfaces are state-of-the-art, the core systems on which they run are often not ready for the revolution that is coming.

    This is where the lesson from overseas becomes crucial. The banks there, spending more than $2.8 trillion, have not created true innovation, but a ‘sea of sameness’. They have achieved the digital standard, but have not built an advantage because their old systems prevent true data-driven personalisation.

    Poland, despite its leading position, also risks falling into this trap. Our banking applications, although excellent, are starting to look and act very similar. They lack the breakthroughs, based on artificial intelligence, that could turn the bank from a passive tool into a proactive, intelligent financial partner.

    The crisis in Western markets is invaluable insight for us. It shows that investing solely in the facade, while ignoring the ageing technological ‘engine’, leads to a dead end. Instead of resting on the laurels of digital leadership, the Polish banking sector needs to treat its current advantage as a starting point for deeper modernisation.

    The race for the customer of the future will not be about adding more features to applications. It will be won by those institutions that have the courage to rebuild their technological foundations for the era of generative artificial intelligence and hyper-personalisation. The West is showing us what failure in this field looks like.

    We have a unique opportunity to learn from their mistakes and prove that our digital maturity is more than just an efficient interface.

  • IT’s hidden enemy. How is automation overcoming technology debt?

    IT’s hidden enemy. How is automation overcoming technology debt?

    IT departments find themselves in the eye of the cyclone. Growing macroeconomic pressures, the explosion of remote and hybrid working and ever-evolving cyber threats are creating an environment where traditional approaches to infrastructure management are no longer sufficient. IT teams must support increasingly complex ecosystems with shrinking budgets and limited human resources. The answer to this challenge, increasingly seen not as an option but a necessity, is strategic automation.

    Automation in IT is no longer just a fashionable buzzword. The global IT automation market, valued at more than $20 billion in 2023, is forecast to grow at a rate of several per cent per year, demonstrating the scale of the phenomenon. It is no longer just the domain of technology giants, but a key element in the strategy of companies of all sizes that want to remain competitive.

    At its core, automation is about using software to perform repetitive, time-consuming tasks without the need for human intervention. The spectrum of applications ranges from optimising daily workflows and handling helpdesk requests, to scaling complex administrative processes, to guaranteeing regulatory compliance and strengthening security.

    A classic example is endpoint management. In the era of remote working, the corporate network consists of hundreds or even thousands of laptops, smartphones and virtual devices. Manually configuring each of them, installing software and deploying security patches is not only a tedious process, but also one with a high risk of error. Automation allows these operations to be standardised, ensuring consistency and freeing up IT professionals for more strategic tasks. The aim is not to replace humans, but to enhance their capabilities.

    You won’t build a palace on a swamp

    However, the road to effective automation is full of pitfalls, the biggest being poor foundations. Implementing modern automation tools on outdated infrastructure and software is like fitting a jet engine to a century-old automobile. Over time, older systems, often lacking modern APIs and relying on closed protocols, become a source of so-called technology debt that cripples innovation.

    Companies face a choice: upgrade internally or work with an external partner to help migrate to the cloud and restructure processes. Whichever path is chosen, a key part of the preparation is organising the data. Automation feeds on data – it needs to be accurate, well-organised and categorised. Market analyses indicate that organisations that achieve a high degree of maturity in data management are able to automate up to 70% of their IT processes.

    Security as a starting point

    Another pillar is cyber security. Every automated process and connected device is a potential attack vector. Therefore, the implementation of security mechanisms at an early stage in the design of automation processes is absolutely crucial. The ‘Security by Design’ approach ensures that automated systems are not only efficient, but also resilient and trustworthy.

    Moreover, automation itself is becoming a powerful tool in the arsenal of security teams. Automated endpoint management platforms offer a complete view of the state of the entire infrastructure, both modern and legacy. This allows for faster identification of security gaps, inefficiencies and potential threats, as well as automatic incident response, reducing response times from hours to minutes.

    A process, not a one-off project

    The biggest mistake organisations can make is to treat automation as a one-off project with a defined end date. It’s an ongoing process that requires constant improvement and optimisation. An automated workflow that was effective a year ago may no longer fit with changing business objectives or new systems architecture today.

    Therefore, mature organisations establish regular review cycles for their automated processes. They analyse performance indicators (KPIs), look for bottlenecks and opportunities for further improvements. It is crucial that every automated task delivers measurable value – whether through cost reduction, increased productivity or improved safety levels.

  • Tech debt bankrupcy: time to zero out technology debt

    Tech debt bankrupcy: time to zero out technology debt

    In 2025, companies are not just cutting IT costs – they are increasingly saying: we are resetting everything. Technology leaders are stopping updating outdated systems and starting to make decisions that would have been considered too risky not long ago: instead of patching and extending the life of the old, it is better to declare ‘technological bankruptcy’ and build the IT ecosystem from scratch – lighter, more flexible and ready for the AI era.

    It’s not just a metaphor. Forrester’s 2026 Budget Planning Guides report indicates that there is a growing number of organisations that, rather than maintaining legacy systems, are shifting resources to technologies that enable growth: automation, analytics, generative models and edge computing solutions. IT leaders put it bluntly: every line of code and every server rack must make a business case – otherwise it stops being an investment and becomes a waste.

    Reset instead of maintenance

    Technology debt is nothing new. The problem is that in 2026 it has ceased to be a marginal cost hidden in IT department budgets. It has become a strategic burden. Older systems are increasingly incompatible with the requirements of modern applications, more difficult to maintain, more expensive to integrate with the cloud and – crucially – delaying the deployment of AI. In a reality of inflationary pressures, geopolitical tensions and economic uncertainty, no one wants to maintain IT that does not drive growth.

    Forrester encourages leaders to take a more radical approach: instead of investing in maintenance, ditch the outdated stack, outsource its minimal support to external providers and build a new architecture – cloud-optimal, AI-native, data-driven.

    This approach is not yet the norm, but it is spreading rapidly. For companies with scale and the right organisational readiness, it is a way to leapfrog efficiency, cost and competitive advantage.

    What exactly is ‘technological bankruptcy’?

    This is a strategic concept – it means stopping investment in systems and processes that do not support key business objectives. It’s not just about closing server rooms. Often, it’s also a decision to abandon monolithic ERP systems, rewrite applications to microservices, migrate data to edge-ready solutions or completely overhaul the digital architecture.

    In practice, declaring ‘technological bankruptcy’ means three moves:

    • We are cutting off funding and development of older systems.
    • We outsource their basic maintenance or migration.
    • We are building a new system layer from scratch, based on modern technologies.

    For IT teams, it is a major challenge, but also an opportunity to break free from years of increasing complexity. For finance departments, a reason to optimise the cost structure and accountability of technology spending.

    Who can afford it?

    Large organisations in industries with high transformation pressures are most likely to take this route: finance, healthcare, telco. They have bigger budgets, more incentive to implement AI, and more to lose if they miss the moment.

    Examples? Banks moving to core cloud-native banking, healthcare companies investing in AI for image recognition and documentation automation, or retail chains ditching their own POS systems in favour of unified SaaS platforms with open APIs.

    But the approach is also gaining adherents among medium-sized companies that previously could not afford such a transformation. Today, the availability of low-code tools, integration services and off-the-shelf AI components makes it possible to carry out a ‘technological reset’ faster and cheaper than ever.

    What does this mean for the IT channel?

    For integrators, resellers and technology providers, this is a moment of changing sales rhetoric. It is no longer enough to offer ‘modernisation’ or ‘digital transformation’. – the customer needs someone to help them decide: what do we leave behind, what do we remove, and what do we build from scratch.

    It is also a huge opportunity for companies specialising in migration, integration, IT project management or change management. The customer is no longer looking solely for technology – they are looking for a partner who will guide them through the full process of ‘cutting the cord’ and building a new working environment.

    The winners will be those partners who, in addition to providing hardware or software, can advise on restructuring the IT environment, suggest new cost models (e.g. OpEx vs CapEx) and support in training teams in new tools.

    Not everyone should declare “bankruptcy”

    This approach has its risks. Giving up legacy systems too quickly without a migration plan can end up in operational paralysis. Data loss, incompatible systems, overloaded teams – these are real risks.

    Not every organisation is ready for a full-blown ‘bankruptcy’ – but every organisation can rethink which components of today’s IT can be sidelined, frozen, moved to focus budgets and resources on what really creates value.

    In many cases, the right solution will be a hybrid model – combining the new with the well-controlled old. The key point, however, is that the old system can no longer govern the budget, strategy or rhythm of IT operations.

    The future builds faster without baggage

    Declaring ‘technological bankruptcy’ is not a failure – it is a conscious strategic decision. It is the courage to say: what got us here will not get us further.

    IT leaders shedding technology debt today are not just improving their cost structure. They are gaining space to invest in future technologies: agent-based AI, edge intelligence, decision automation.

    As the pace of change accelerates, organisations with lightweight, adaptive IT environments are winning not because they are more innovative – but because they can react faster, experiment and deliver value to customers. And that is today’s greatest asset.