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Three key questions on the road to AI adoption

By Gert-Jan Wijman, VP & GM EMEA, Celigo

In the world of IT, there is rarely a period when some technology trend isn’t promising to deliver greater efficiency, productivity, and competitive advantage.

Few trends, however, have ever been met with the level of attention, expectation, and investment that AI is currently receiving. Usually, we would expect to see diversity in how businesses react to new technologies as they learn and experiment, but in a recent survey of more than 1,200 global enterprise Operations and IT leaders, Celigo found that 97% of respondents already view AI as ‘critical to driving operational improvements in the coming year’. That’s amazing when you consider that less than 10 years ago, there weren’t machines considered reliable enough to provide language or image recognition at a human level.

Gert Jan Wijman

Of those 97%, the vast majority are already well into the swing of actively investing in AI: over three-quarters of businesses indicate that they have dedicated specific resources and budget to AI, while over four-fifths have a formal strategy or roadmap in place for AI implementation. However, usage does not automatically turn into benefits, and the sheer level of interest and effort in AI adoption only raises the stakes for businesses that need to show real ROI from their exploration of this new technology.

The data, and our experience based on working with IT customers, suggest that there are a few key questions which can point the way towards successful strategies that overcome roadblocks on the path to AI adoption.

Who leads the AI charge?

Whether the technology in question is a tailor-made solution or a plug-and-play tool,  the process is usually driven by IT teams. However, there are signs that for AI that isn’t the whole story. Just 26% of businesses, in fact, say that IT is at the forefront of their AI mandate, and over half allow users to implement AI solutions without formal IT oversight.

There are multiple reasons for this. For one, IT teams are often overburdened as it is, leaving them with little breathing room to take charge of something as all-encompassing as AI adoption. But at the same time, part of the promise of AI is the way that it can democratise access to technology, making complex processes more intuitive.

Indeed, 68% of businesses say they approve of a Citizen Developer mindset, in which knowledge workers are empowered to innovate processes in ways that were typically reserved for technology specialists. Such an approach has obvious benefits in terms of sharing the workload, and has the advantage that departments and teams are the experts in what capabilities would best augment their own workflows.

While there are clearly advantages to allowing citizen developers to play a role in implementing AI, it also exacerbates risks, particularly on grounds of security and data governance.To empower Citizen Developers safely, businesses first need a modern approach to integration.

Where does AI happen?

All AI applications start with good data. While any given department will have its key platforms for gathering and managing data – customer relationship management platforms, enterprise resource planning platforms, collaboration and productivity platforms, and so on – the best results will come when those data sources are brought together in a holistic way that can generate deeper insights.

The challenge of integration has been growing for a long time, as businesses lean on ever more cloud services to carry out day-to-day business. Having many specialised tools available can help teams to excel in their work, but it also makes connecting the business’s IT infrastructure together in a unified way exponentially more complex.

The arrival of AI is adding real urgency to this challenge: while employees may be able to find ways of navigating across many data sources, AI needs data to be available in a more frictionless way. Our survey found that businesses are expecting to exploit a huge diversity of data sources and types through their AI adoption, from cloud platforms and APIs to user interaction tracking and user feedback data.

In this context, investing solely in the end-goal of AI implementation risks either outcomes that underperform due to a lack of data or outcomes that create governance issues through inexpert data integrations. Attention should also be paid to technologies like Integration Platforms-as-a-Service (iPaaS), which can significantly simplify and normalise the underlying data integration challenge. Organisations should also place attention on the upskilling of staff through training so as to maximise the benefit of AI to the business.

How are AI benefits shared?

While security was the most common risk identified by respondents to our survey, 46% said that fears around jobs being replaced by AI are a concern in their organisations. As the Citizen Developer mindset suggests, however, AI is no different to any other technology in that it is ultimately by and for people.

Just as the adoption of specialised platforms by different teams can create data silos and integration challenges, permitting unchecked team-level innovation without IT oversight can ironically reinforce the very barriers that data integration aims to dismantle. This paradox highlights the delicate balance between fostering innovation and maintaining a cohesive, interconnected IT ecosystem. While team autonomy can drive rapid advancements and tailored solutions, it may inadvertently perpetuate isolation and fragmentation across the organisation’s data landscape. The challenge lies in cultivating an environment that encourages innovation while simultaneously ensuring new technologies and processes align with broader organisational goals for data accessibility and integration.

In order to maintain security while promoting the freedom to self-implement, it’s imperative that companies have a clear strategy on balancing the two. Establishing a clearly documented AI policy, for instance, can alleviate uncertainty over what is and isn’t allowed as people explore the technology. Creating an open culture of learning and experimentation can be helped with social feedback loops like lunch-and-learns, where non-technical employees share what has worked for them and IT leaders can offer their expert advice.

Over time, almost every business will experience AI as a critical driver of operational improvement. When so many businesses are investing so heavily, though, the real winners will be those who take the smartest path to the destination.

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Business

The Security Talent Gap is a Red Herring: It’s Really an Automation and Context Gap

by Tom Gol, Senior Product Manager Armis

We constantly hear about a cybersecurity staffing crisis, but perhaps the real challenge isn’t a lack of people. It might just be a critical shortage of intelligent automation and actionable context for the talented teams we already have.

The Lingering Shadow of the “Talent Gap” Narrative

It’s almost a mantra in cybersecurity circles: “There’s a massive talent gap!” Conferences echo it, reports reinforce it, and CISOs often feel it acutely. This widely accepted idea suggests we simply don’t have enough skilled professionals, leading to overworked teams, burnout, and, most critically, persistent organizational risk. The default response often becomes a relentless cycle of “buy more tools, tune more tools, and staff more teams”—a cycle that feels increasingly unsustainable and inefficient.

But what if this pervasive “talent gap” is actually a clever red herring, distracting us from a more fundamental issue? We’ve grown so accustomed to the narrative of a human deficit that we often overlook a crucial truth: current technology is already capable of significantly narrowing this very gap. My strong conviction is this: the true underlying problem isn’t a shortage of available talent, but a profound and crippling gap in intelligent automation and actionable context that prevents our existing cybersecurity professionals from operating at their full potential. What’s more, advancing on the technology side now presents a demonstrably better return on investment than simply trying to out-hire the problem. Fill that gap with smarter tech, and watch the perceived talent shortage shrink.

Misdiagnosis: When More People Isn’t the Answer

For too long, the cybersecurity industry’s knee-jerk reaction to mounting threats has been to throw more human resources at the problem. Yet, the attack surface continues its relentless expansion. Threat actors become more sophisticated. And our SOCs are constantly drowning in an unfiltered deluge of alerts. This creates an overwhelming workload that even the most seasoned experts find impossible to manage effectively, often resulting in burnout and, ironically, talent attrition rather than retention.

The issue isn’t that a lack of bright minds are joining the field. It’s that those brilliant minds often find themselves mired in monotonous, low-value tasks. They’re forced to operate in a thick fog of incomplete information, constantly sifting through noise. When security teams lack clarity on exactly what assets they own, how those assets connect, what their true business criticality is, and which threats are genuinely active, even the most experienced professional struggles. Their effectiveness diminishes, not from a lack of inherent skill, but from a fundamental absence of visibility and intelligent support.

Automation and AI: The True Force Multiplier for Human Talent

The real power move against the overwhelming tide of cyber threats lies not in endless recruitment, but in the intelligent application of automation and AI. Leading industry discussions increasingly highlight that the purpose of AI in cybersecurity isn’t about wholesale human replacement. Instead, it’s about augmenting our existing staff, turning them into a far more potent force. This approach fundamentally allows organizations to scale their expertise and impact without being shackled to proportional headcount increases. Let’s unpack how this transformation plays out.

Freeing Up Human Capital from the Mundane

Imagine a security analyst whose day is consumed by hours of manual investigation, enriching alerts, triaging false positives, responding to routine questionnaires, or laboriously transitioning tickets. These are precisely the kinds of non-human, deterministic, and highly repetitive tasks ripe for intelligent automation. AI agents can seamlessly take on this soul-crushing burden, liberating human analysts. They are then free to pivot towards higher-value, creative, judgment-based, and genuinely strategic work. This transforms security teams from reactive task-runners into proactive problem-solvers. Projections suggest that common SOC tasks could become significantly more cost-efficient in the coming years due to automation—a shift that’s not merely about saving money, but about amplifying human potential.

Supercharging Productivity and Experience

Modern AI, particularly multi-agent AI and generative AI, can proactively offer smart advice on configurations, predict the root causes of complex issues, and integrate effortlessly with existing automated frameworks. This empowers security professionals, making their work not just more efficient but also more engaging and less prone to drudgery.

The Indispensable Power of Context: Lowering the “Expertise Bar”

While automation tackles the sheer volume of work, context provides the vital clarity that fundamentally reduces the need for constant, deep-seated expertise in every single scenario. When security professionals have immediate, rich, and actionable context about a vulnerability or an emerging threat, the path to intelligent prioritization and decisive action becomes remarkably clearer.

Consider the profound difference this context makes:

  • Asset Context: Knowing not just that a vulnerability exists, but precisely which specific device it resides on—is it a critical production server, or an isolated, deprecated test machine?
  • Business Application Context: Understanding the exact business function tied to that asset, and the tangible financial or operational impact if it were to be compromised.
  • Network Context: Seeing the asset’s intricate network connections, its precise exposure level, and every potential path an attacker could take for lateral movement.
  • Compensating Controls Context: Having a clear, real-time picture of which existing security controls (like network segmentation, EDRs, or Intrusion Prevention Systems) are actually in place and effectively working to mitigate the vulnerability’s risk.
  • Threat Intelligence Context: Possessing real-time, “active exploit” intelligence that doesn’t just theorize, but tells you if a vulnerability is actively being exploited in the wild, or is part of a known attack campaign targeting your industry.

With this deep, multidimensional context, a significant portion of the exposure management workload can be automated. Crucially, for the tasks that still require human intervention, the “expertise bar” is dramatically lowered. My take is that for a vast majority of cases—perhaps 90% of scenarios—a security professional who isn’t a battle-hardened, 20-year veteran can still make incredibly effective decisions and significantly improve an organization’s cyber posture. This is because they are presented with clear, actionable context that naturally guides prioritization and even recommends precise actions. The result? A drastic reduction in alert noise, faster detection and response times, and a palpable easing of the burden on the entire security team.

Navigating the Human Element: Skills Evolution and Burnout

This powerful shift towards automation and AI naturally brings legitimate questions about skills erosion. Some experts prudently point out a valid risk: a significant portion of SOC teams might experience a regression in foundational analysis skills due to an over-reliance on automation. This underscores a critical truth: we must keep humans firmly in the loop. For highly autonomous SOCs, a “human-on-the-loop” approach is recommended, reserving human intervention for complex edge cases and critical exceptions.

CISOs, therefore, face an evolving mandate:

  • Future-Proofing Skills: It’s less about filling historical roles and more about nurturing new competencies like prompt engineering, sophisticated AI oversight, advanced critical thinking, and strategic problem-solving.
  • Combating Burnout: Beyond just tools, effective talent retention demands proactive measures to address burnout. This includes intelligent workload monitoring, smart task delegation, and genuine wellness initiatives. The ultimate goal isn’t just to fill empty seats; it’s to ensure that the people in those seats are effective, sustainable, and thriving.

A New Mindset for CISOs: Embracing the “Chief Innovation Security Officer” Role

The ongoing “talent gap” discussion should be a catalyst for CISOs to adopt a fundamentally new mindset. Instead of simply focusing on cost-cutting or the perpetual struggle of recruitment, they must evolve into “Chief Innovation Security Officers.” This means daring to rethink how work gets done, leveraging AI and automation not merely as tactical tools but as strategic enablers for scaling cybersecurity capabilities and unlocking the full potential of their existing talent. This strategic investment in technology, driven by an understanding of context, offers a superior ROI in bridging the cybersecurity “gap” compared to the increasingly futile effort to simply hire more people.

Building robust AI governance frameworks and achieving crystal-clear visibility into existing AI implementations and technical debt are crucial foundational steps. Ultimately, solving the perceived talent gap isn’t about endlessly hiring more people into an unsustainable system. It’s about empowering the talented individuals we do have—making them more efficient, more effective, and more strategically focused—through the intelligent application of automation and unparalleled context. It’s time to stop chasing a phantom gap and start truly empowering our digital defenders.

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Business

Beyond compliance: why the shift to ISO 20022 is more than a messaging upgrade

Maria-Christine Diaz, Senior Business Strategy Manager at Eastnets, explores why ISO 20022 is more than a mandate – it’s a catalyst laying the groundwork for future-proof payment services

The SWIFT-mandated migration by November 2025 is set to end MT message processing for interbank cross-border payment instructions and cash management reporting (CBPR+). Yet, according to SWIFT as of December 2024, only 33% of organisations had adopted ISO 20022 for CBPR+. It highlights a deeper issue: many organisations still see it as a technical obligation when really, the migration implications stretch far beyond protocol upgrades and format translations.

ISO 20022 is not a one-off project. It is a multi-year, cross-functional transformation program touching every part of the business. It’s a strategic opportunity and a chance to rethink how financial institutions manage payments infrastructure, compliance and customer value propositions in a rapidly evolving digital economy.

However, it demands a coordinated, business-wide response.

Why tactical fixes won’t solve strategic shifts

At its core, ISO 20022 replaces the flat, ambiguous MT messaging format with structured, contextualised data that applies across all payment types, domestic and cross-border. It allows institutions to capture and exchange richer details – from payment purpose code and country of origin to beneficiary information – with far greater quality, accuracy and completeness.

That quality creates tangible value. It promises to strengthen Straight-Through Processing (STP) efficiency and dramatically improve the effectiveness of fraud detection and anti-money laundering (AML) processes. How? By reducing the number of investigation cases and false positives that have long strained operations teams. ISO 20022 also supports regulatory focus on real-time transaction monitoring and incident transparency, something central to frameworks like the EU’s Payment Services Directive 3, the AML Directives and the Digital Operational Resilience Act (DORA).

But ISO 20022 doesn’t just support regulatory alignment, it fundamentally alters the operational risk landscape. Most institutions still rely on compliance processes and infrastructures built for MT messages, which are poorly suited to handle the granularity and structure of ISO 20022 data. And when this richer data is simply “bolted on” to legacy systems, problems quickly arise.

Many banks are pursuing a tactical fix for what is a strategic shift – it’s like trying to put a square peg into a round hole. Systems and processes were built around the limited MT format which are flat, fixed and often ambiguous. Existing rule sets designed for flat MT messages begin to break down, triggering too many false positives and overwhelming compliance teams with noise instead of insights.

To realise the full value of ISO 20022, institutions need to map how payment data flows across their organisation. This helps identify legacy workarounds, uncover operational risks and pinpoint where ISO 20022 adds complexity or unlocks new opportunity. Therefore, a comprehensive business-wide impact assessment is essential to strengthen AML, sanctions screening and fraud detection processes.

With that foundation, banks can sharpen customer insights, strengthen fraud and risk controls, and develop new value-added services. As sanctions lists and fraud rules update in near real-time, combined with financial crime compliance costs surpassing $1 trillion in 2024, the ability to act on cleaner, more contextual data has become business-critical.

Therefore, making ISO 20022 work for the business means moving beyond retrofitting and honing in on three areas that drive real transformation.

More impact than meets the eye

The real opportunity begins when ISO 20022 data is integrated into core systems, not just translated at the edges. Payments data now impacts every business line – from retail and corporate banking to capital markets and trade finance – influencing every process from front to back office.

Again, migration is not a one-off project but something that touches every part of the business, from reconciliation processes to customer-facing services. The key challenge of this transformation is knowing where the payment is, its status, without ambiguity, at any moment. Think of it like tracking an Amazon parcel delivery. To manage this, institutions need lightweight analytics tools to monitor and track payment messages in real-time across systems, to reduce reconciliation errors, manual workarounds and operational risk.

The true value lies not in seeing the information, but in using it to streamline operations, resolve issues faster and deliver better outcomes.

The path to optimised financial crime detection

As ISO 20022 fundamentally offers richer information, one of the most immediate benefits lies in financial crime prevention.

To take advantage, institutions must recalibrate financial crime systems to work with clearer, structured and contextual ISO 20022 data. This isn’t just about better information, it’s about better precision. Finetuning these systems through precise finetuning techniques to improve detection precision and strengthen risk mitigation, all while reducing and operational costs.

Take Sohar International, a bank operating in the Middle East, as an example. It reduced its false positives by 67%, helping to distinguish between legitimate and suspicious transactions, simply by optimising screening strategies and using structured ISO 20022 data. That kind of result creates space for smarter, faster decisions across the organisation, all while strengthening its AML compliance framework.

An opportunity for leaner payment processes 

Additionally, ISO 20022 presents the perfect opportunity to modernise payment infrastructures with a modular orchestration layer – a flexible, business-agnostic workflow engine that seamlessly translates and routes messages across systems. This shields core business applications from changes in formats, protocols and standards, reducing maintenance overhead and operational risk and accelerating ISO 20022 adoption without disrupting core operations.

Moreover, it enables real-time monitoring, detection and investigation of issues such as duplicate payments or delayed messages, providing transaction integrity across the entire lifecycle. Having infrastructure agility translates directly into business performance, which can lead to increased cross-jurisdiction visibility in real-time and optimised STP rates, making sure payments move securely, efficiently and in line with market expectations. .

By building this agility, financial institutions lay the groundwork to rapidly adapt to future market changes, new services and customer demands without overhauling core systems. It also provides real-time visibility and transaction integrity, making sure payments move securely, efficiently and in line with market expectations.

Unlocking the true value of ISO 20022

Treating compliance as the end goal is a strategic misstep.  So, without a coordinated business-wide transformation strategy, supported by optimised financial crime tools, a lean orchestration layer and real-time monitoring, institutions risk operational disruptions and regulatory scrutiny impacting their bottom line.

What’s ultimately at stake is more than a messaging upgrade. It’s the opportunity to reshape financial infrastructure for an era defined by sustainable growth and operational resilience.

The real value of ISO 20022 lies not in translating messages, but in transforming the business. Those who embrace the shift – not just to adopt, but to adapt – will be best positioned to unlock smarter, data-driven growth in the years ahead.

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Business

The Quiet Strength of Being Clear – Why Assertiveness Matters More Than Ever for Founders

By Rebecca Sutherland, CEO and Founder of HarbarSix

There’s a word that often makes people shift a little in their seats. Assertiveness. It can sound sharp, maybe even a bit harsh, like something that belongs in boardrooms filled with ego or in negotiation books gathering dust on someone’s shelf. But in truth, assertiveness, when you really understand it, is one of the most compassionate tools we have as leaders.

Because at its core, assertiveness isn’t about being pushy. It’s about being clear.

And when you’re building something, a business, a team, a dream that lives outside the ordinary, that kind of clarity becomes essential. Without it, you end up drifting, making decisions that don’t feel quite right, saying yes when you mean no, and slowly watching the thing you once felt lit up by become a source of tension or exhaustion.

I’ve seen it happen more than once. A brilliant, creative founder full of drive and vision, slowly ground down by too many compromises, too much people-pleasing, too little space to breathe. They don’t lack skill or ambition. What they’re missing is that anchor, the ability to be assertive without feeling like they have to apologise for it.

So, let’s unpack that, because I think we need to talk about how to lead from a place that’s both strong and soft. Firm but open and rooted in who you are.

Assertiveness starts with self-trust

Before you can speak clearly to others, you must be clear with yourself. What do you stand for? What kind of culture are you trying to build? What do you value, not just on a branding level, but deep in your bones?

Because if you don’t know that, you’ll find yourself pulled in all directions. You’ll agree to partnerships that don’t serve you, hire people based on panic rather than alignment, and find it hard to hold boundaries when the stakes feel high.

But when you do know—when you’ve taken the time to understand what really matters to you—it becomes easier to communicate it, calmly and confidently, even when it’s uncomfortable.

Saying what you mean isn’t unkind—it’s respectful

There’s a misconception, especially among founders who want to be “good” leaders, that being direct is somehow abrasive. That if you’re too clear, you might upset people. But in my experience, the opposite is true.

When you wrap your truth in too many layers of softening or delay saying the hard thing because you’re worried about how it will land, you actually create more confusion, not less. People want to know where they stand. Your team, your investors, your clients—they respect leaders who can speak with warmth and certainty.

You don’t need to bark orders or dominate a room. But you do need to be able to say, “This isn’t working for me,” or “This direction doesn’t feel right,” or even, “I’ve changed my mind.” That kind of honesty is a form of care. It protects your energy, and it gives everyone around you a clearer playing field.

Boundaries aren’t barriers—they’re invitations to trust

One of the most powerful forms of assertiveness is knowing when to say no. Or not yet. Or not like this.

As founders, we’re often wired to keep giving—to clients, to our team, to the business itself. But that constant giving, without boundaries, leads to burnout. And more than that, it models a kind of unsustainable leadership where overextending becomes the norm.

Boundaries, when set with intention, are not walls. They’re signals. They say, “This is how I work best,” or “This is what I need to stay at my best,” or “Here’s the line where my role ends and yours begins.” And far from pushing people away, they create the safety and trust needed for real collaboration.

Not everyone will like it—and that’s okay

Here’s the part that might sting a little: not everyone will like your assertiveness. Some people will bristle when you stop bending over backwards. Others may be used to you saying yes to everything, and might struggle when you start to reclaim your space.

Let them. Your job isn’t to be liked by everyone. Your job is to build something honest, sustainable, and true. And the people who are meant to walk alongside you? They’ll stay, in fact, they’ll probably thank you for the clarity.

Practice before you need it

Like any skill, assertiveness gets easier with practice. Start small. Have that conversation you’ve been avoiding. Say no to the next thing that doesn’t feel aligned. Express a need clearly without over-explaining. And then do it again. Not perfectly, just consistently.

If you’re not used to it, it might feel clunky at first. That’s okay. Clarity is a muscle. The more you use it, the stronger it gets.

The most powerful leaders are not the loudest

They’re not the ones who dominate meetings or chase visibility for its own sake. They’re the ones who know who they are. Who can sit in discomfort without losing their footing. Who can say the hard thing with softness and stay true to their vision when the noise gets loud.

Assertiveness isn’t about power over others—it’s about being in your own power. And when you lead from that place, it changes everything.

For your business. For your team. And most importantly, for you.

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