This platform consists of two main modules:

• Citizen portal: an open online space that makes all published information available to the public, promoting transparency and universal access.
• Internal management application: facilitates the collection, classification, storage, and publication of content submitted by collaborating departments, ensuring structured and reliable management.

The technological platform is designed to be robust and secure, integrating multiple data sources from Public Administrations, Autonomous Communities, Local Entities, and the Social Security system.

One of the key achievements of the project is that, despite handling a large volume of data, the system remains easy for end users to operate, and queries are fast and accurate.

This initiative is part of the SGTIC’s strategy to modernize the Ministry’s systems, leveraging the possibilities offered by current technologies.

With projected revenue of €100 million in Spain this year, Getronics develops applications and delivers AI projects for numerous public and private organizations such as AENA, the Ministry of Health, the Ministry of the Interior, the Community of Madrid, the Regional Government of Andalusia, as well as private IBEX 35 companies across multiple sectors including energy, banking, and retail.

The post New Data Bank Developed & Implemented for Ministry of Finance in Spain appeared first on Getronics.

2026 won’t be short on data — but it will be short on clarity.
AI adoption continues to accelerate: according to McKinsey, 71% of organisations now use generative AI in at least one business function. Yet scaling remains a challenge. Gartner predicts that at least 30% of generative AI projects will be abandoned after proof of concept by the end of 2025, often due to unclear business value, weak governance, or poor data foundations.

The lesson is clear: AI doesn’t fail because of a lack of intelligence. It fails because organisations struggle to turn signals into decisions. 

When data is more trouble than it’s worth 

Across industries, people start their day facing operational data that doesn’t always line up with what they’re seeing in real life. Abundant data is a blessing. But it becomes a curse when teams are overloaded with information that lacks proper context and interpretation. This often just leads to confusion and unnecessary work. Here are a couple examples: 

• In banking, AI can detect fraud patterns in seconds — but only if models are explainable and auditable. In manufacturing, predictive maintenance only delivers value when sensor data is standardised and continuously monitored. In retail, demand forecasting improves margins only when decision-makers understand model confidence levels and risk thresholds.  
  
  The common denominator is not automation. It is decision intelligence — the ability to combine reliable data, transparent models, and accountable processes into actionable insight.

• A manufacturer might see a rise in defects across several lines. They’ve got data on machine performance, supplier batches, operating conditions and more, but it’s all spread across multiple systems. How can they spot where the problem really lies and decide what needs to change? 

These situations show how data can actually complicate things when it should really be helping people decide what to do next. AI is getting better and better at connecting information from different systems, identifying trends that develop slowly and alerting us when something doesn’t fit the pattern. It’s becoming a strategic decision-making aid everywhere from banking and insurance to manufacturing, retail and beyond.

Organisations are not suffering from a lack of information. They are suffering from fragmented systems, inconsistent definitions, and unclear ownership. Research from IBM suggests that poor data quality costs organisations millions annually — not only in financial impact, but in delayed or misguided decisions. When AI is trained on inconsistent data, it scales confusion instead of clarity.

From forecasting to enhancing decision-making 

The more we work with AI, the more realistic we are about what it can and can’t do. Many organisations start their AI journey expecting for AI to be a crystal ball that accurately predicts future scenarios. But that expectation doesn’t hold up in markets that shift as quickly as the ones we’re moving into in 2026. The good news is: AI doesn’t have to provide your teams with a perfect forecast as long as it gives them a reliable sense of where they stand today, so they can respond to what comes next. 

In retail, this comes up when teams try to understand sudden changes in customer behaviour. Online activity, store traffic and loyalty data often point in different directions, and the usual dashboards rarely explain why. When these sources are viewed together, the patterns become easier to interpret. Retailers can see whether they are dealing with a short-lived spike or a genuine change in demand, which helps them focus their time where it actually matters. 

In insurance, the issue is the pace at which risks evolve. Claims patterns can shift quickly after severe weather or policy changes. A handler might see an unusual cluster of claims in one region and have no immediate context for why it’s happening. Tools that compare current cases with broader trends can highlight what stands out and why, but the reasoning needs to be visible. If a system flags a risk without explaining the factors behind it, the handler still has to do the interpretation manually. 

Making AI work for you 

No matter what the use case, to make AI really work for your organisation, it takes a three-layered approach: 

• Transparency: People can only trust an output if they can see how the system reached its conclusions. In banking or insurance, for example, analysts cannot act on a flagged transaction or a rejected application unless they can explain the decision to customers. Without a reliable, logical explanation, the output will have to be rechecked by hand anyway. 
  
  Trust is not a soft factor — it is a scaling requirement. McKinsey reports that 40% of organisations cite explainability as one of the top AI-related risks, yet only 17% actively work on mitigation strategies. Without explainability, AI recommendations remain suggestions. With transparency, they become decisions.

• Governance: The data your AI tool works with must be clean, current and complete. It also takes continual monitoring to make sure the model is still behaving as expected. Otherwise, the AI’s output starts to lose touch with reality. In manufacturing, for instance, if production and supply chain systems are siloed, engineers may receive alerts based on old or incomplete data. When that happens, they’ll wind up spending more time investigating the source of an alert instead of addressing the problem itself. 
  
  In Europe, 2026 is not only about capability — it is about compliance readiness. The EU AI Act introduces phased obligations for high-risk AI systems, with major enforcement milestones beginning in 2025 and 2026. Organisations deploying AI without structured governance frameworks may soon face not only operational risk, but regulatory exposure.
  
  Governance is therefore not a constraint. It is a strategic enabler for sustainable AI deployment.

• AI literacy: By now, it’s clear that AI is a supplement and not a replacement for human judgment. It takes dedicated training to ensure people are using AI to help them do their jobs better and not simply relying on its output without ever questioning it. We know that AI can speed up information-gathering and analytical tasks, but ultimately, it’s not about automating decisions. With careful implementation, AI serves as a clarity engine. It cuts through complexity so that your people are better equipped to make decisions for themselves. 

Starting 2026 with a clearer view 

Organisations that will succeed with AI in 2026 will not be those with the most pilots — but those with the clearest decision frameworks.

A practical starting point?

• Identify one critical decision process and assign ownership.
• Assess data quality and governance maturity.
• Introduce explainability standards before scaling automation.

AI does not remove complexity. It makes complexity manageable — when built on clarity.

At Getronics, we see that successful AI initiatives combine technical implementation with governance design and organisational enablement. Decision support is not just about deploying models — it is about building systems that people trust and use.

Thanks for joining us in this series on the Five Actual Truths About AI. Be sure to check out our previous articles on how AI multiplies skills, builds trust at scale, powers workplace personalisation and drives efficiency under pressure. 

The post Clarity in complexity: Making better decisions with AI in 2026 appeared first on Getronics.

This gap is not about tools — it is about maturity. Many digital workplace strategies were originally designed to ensure connectivity and remote access. Today, the challenge is fundamentally different: organisations must align technology, workflows, leadership behaviours, and employee experience to sustain productivity, collaboration, and resilience at scale.

The hybrid workplace is at a crossroads. The question is no longer whether it works. The question is whether organisations are ready to evolve their digital workplace strategies from operational enablement to strategic capability. 

The workforce strategy lens reinforces the urgency. Upskilling is the most common strategic response to macrotrends, selected by 85% of surveyed employers. Automation acceleration is the second most common at 73%. Employers also plan to complement and augment the workforce with new technologies (70%) and hire staff with new skills (63%). These are structural investments that depend on a coherent digital workplace to pay off.  

Even the employer brand dimension has moved. Offering remote and hybrid work opportunities within countries is explicitly used by 43% of organizations as a lever to increase talent availability, alongside measures like wellbeing and reskilling. The takeaway here for leaders is that flexibility and capability-building are now fundamentals of competitiveness, not perks. 

From the CEO’s chair, the mandate is to professionalize the digital workplace: build culture for a distributed context, measure outcomes not presence, harden support and security, and put governance around the whole system so it keeps improving. The following five areas define that maturity journey.

Culture & Cohesion — Rituals, remote leadership, and communication principles 

Culture used to ride on proximity. In a hybrid world, it rides on design. The organizations that are winning have stopped treating culture as something that only happens in offices and started engineering repeatable rituals and leadership behaviors that make distributed teams feel part of one company. 

The risk to cohesion is real. Employers themselves list culture and resistance to change as the second most common barrier to their transformation plans at 46%, which translates into day-to-day friction: misaligned expectations, uneven manager capability, and collaboration debt across locations and time zones. The takeaway is that culture is a transformation dependency rather than a soft afterthought. 

There is also an uncomfortable truth about presence mandates. According to Gartner’s Future of Work Trends for 2025 report, on-site workers report lower satisfaction with workplace interactions than hybrid or remote peers every year since 2021. That pattern reinforces the point that unstructured co-location does not fix weak relationships or poor communication; it merely adds commute time to a broken experience. Leaders need to replace nostalgia with operating mechanisms that create belonging. 

The culture lever connects directly to talent and performance. When employees feel part of a coherent system, you reduce voluntary churn, increase knowledge flow, and improve execution under pressure. Those outcomes are compounding in a cycle where the digital workplace is both the medium and the message. How you communicate, decide, and deliver becomes how people experience your organization daily.  

CEOs should treat cultural cohesion as a program dimension of the digital workplace with explicit objectives, owners, and metrics tied to engagement and collaboration quality. The market context makes this a board-level priority, not an HR side project.  

Proximity & Accountability — OKRs and outcome-based rather than activity-based measurement 

Hybrid work breaks legacy performance models. If the system still rewards visibility over value, leaders unintentionally incentivize noise. Maturity is the pivot to outcomes. 

Employers are already recoding their strategies around capability and impact according to WEF’s report. Upskilling sits at 85% adoption over 2025–2030 because companies know they cannot execute without modern skills; automation sits at 73% because the intent is to increase throughput and quality by removing friction from workflows. Those bets only yield results if performance systems measure outputs, customer impact, and innovation velocity rather than time at the desk. OKRs provide the spine for that shift by connecting strategic intent with measurable results at the team and individual levels. 

The people side of performance needs equal weight. Employers expect enhanced productivity in 77% of cases from training investments, and improved competitiveness in 70%. Retention is also a top-three outcome at 65%. If the digital workplace increases digital friction or erodes well-being, those outcomes degrade. Mature organizations therefore pair outcome-based measurement with EX indicators so that success does not come at the cost of sustainability.  

A note on governance: Culture and resistance to change, cited by 46%, will undermine any move to outcome-based management if leaders keep sending mixed signals. If the company says outcomes matter but managers still reward presenteeism, the system reverts. CEOs need to hard-wire outcome logic into planning, reviews, and rewards so managers can coach to clarity, not proximity.  

Employer Brand & Reputation — Hybrid work as a differentiator in the talent market  

The talent market now treats hybrid not as a benefit but as table stakes. Globally, 43% of employers offer remote and hybrid roles within countries to expand talent availability, and additional flexibility levers like better working hours and support for caregivers are rising on the same list. Companies are also planning for cross-border flexibility, with 27% signaling remote work across countries as part of the strategy. In practice, that means your digital workplace is an external brand asset: candidates infer trust, agility, and inclusion from how you work, not just what you say. 

This is reinforced by broader transformation planning. Skills shortages remain the top barrier at 63%, and hiring staff with new skills is a strategic priority for 63% as well. Employers that bake flexibility into the work system improve their odds of reaching scarce talent and accelerate ramp-up through better onboarding and learning in the flow of work. If your digital workplace frustrates people, you pay twice — once in the labor market and again in attrition. Treat hybrid credibility as a competitive differentiator you can prove in your process, not a slogan on your careers page. 

For CEOs, employer brand is now intertwined with the operating model. Investors and customers infer management quality from how you run the company. A disciplined, human-centric digital workplace with clear goals, smart tooling, sensible flexibility, and measured outcomes signals control and momentum in a way that shows up in bidding, partnerships, and M&A conversations as much as it does in recruiting pipelines.  

Strategic Alignment & Investment — Priorities (support, security, and automation) 

The tool stack is not the strategy; alignment is. Employers are committing to capability and capacity at a structural level: 85% plan to upskill the workforce, 73% to accelerate automation, and 70% to augment people with new technologies, according to the WEF report. Those numbers set the investment agenda for CEOs: prioritize platforms and services that reduce friction, raise quality, and make modern skills usable at scale.  

Support must be reimagined for hybrid reality. Training investments are expected to enhance productivity in 77% of cases and improve competitiveness in 70%, which means learning needs to be embedded in the workflow, not treated as an off-site. Digital adoption, knowledge discovery, and performance support should be designed as first-class components of the employee experience so that upskilling translates into output.  

Security and data foundations are equally strategic. A full third of organizations cite inadequate data and technical infrastructure as a barrier to transformation, a reminder that analytics, identity, and integration are the bedrock of trust and velocity in a hybrid model. With work now spread across devices, networks, and clouds, identity-centric access, endpoint hygiene, and auditable collaboration are prerequisites for continuity and compliance. 

Governance & Measurability — Steering committees, metrics, and continuous improvement 

Maturity requires an operating model. Without governance, the digital workplace drifts into tool sprawl and culture drift. The fix is cross-functional ownership with teeth, where HR, IT, operations, security, and finance work off one roadmap, with employee voices represented and a clear line to enterprise outcomes. Gartner’s future-of-work guidance emphasizes that proximity mandates alone won’t repair cohesion and that organizations should actively guide interactions and collaboration norms. 

Measurement must move beyond activity logs. Employers already know what outcomes they are chasing: higher productivity, improved competitiveness, and better retention from training investment. Use those outcomes as your north star and wire them into dashboards that triangulate platform telemetry and business KPIs. If culture is a known barrier at 46% and data infrastructure is a barrier at 32%, then tracking inclusion, belonging, and data quality should sit alongside cycle time and cost in your executive pack.  

Continuous improvement is the cadence that keeps the system honest. Treat the digital workplace like any mission-critical program with quarterly reviews, clear owners, remediation backlogs, and a budget you can reallocate toward what works. Tie investment gates to proof of impact, not vendor claims. That discipline is how you convert a hybrid policy into a performance engine, and it’s how you signal to your organization that modern work is a core competency, not a passing phase.  

Your Role as the CEO 

A mature digital workplace is the junction where culture, process, and technology reinforce each other. It creates cohesion without co-location. It measures value rather than visibility. It invests in people, not just platforms. And it runs on governance that keeps the whole system improving. The market data shows why this matters: skills shortages at 63%, culture friction at 46%, data foundations at 32%, and a strategic tilt toward upskilling at 85% and automation at 73%. Those numbers map directly to CEO responsibilities.  

Your role is sponsor and pace-setter. Set the bar for outcome-based performance. Back the investments that reduce friction and raise quality. Put culture on a program footing. And insist on governance that aligns everyone to the same scoreboard. 

If you want a practical start, use a one-page Hybrid Workplace Maturity (CEO) checklist with five lanes — Culture, Performance, Employer Brand, Strategic Investment, Governance — each with two or three must-pass tests tied to the metrics above. Or set up a short working session and we’ll map your current state to those lanes and build a prioritized, metrics-anchored plan. The ad-hoc phase is over. The maturity phase is how you win.  

The post The Hybrid Workplace at a Crossroads: Why Digital Workplace Strategies Must Now Mature (CEO Perspective)  appeared first on Getronics.

A proven partnership more than a decade in the making 

This renewal marks over 12 years of continuous collaboration, a rare tenure in the rapidly shifting world of airport technology. What began as a service relationship has steadily grown into a strategic partnership shaped by shared ambition, straight talking, and a track record of keeping critical airport operations running smoothly. 

Stuart Deignan, Group CEO at Getronics, captured the spirit of the partnership: 

“Ten years together is no small thing, and it’s a testament to what real partnership looks like. With AGS Airports, it’s always been straight talking, shared drive and getting results that matter. We appreciate the trust they’ve placed in us, and we’re fired up for what we can achieve together next.” 

Across the years, Getronics has delivered a wide range of services, including: 

• 24×7 Service Desk 
• ITIL service processes
• On-site and Field Engineering
• Software Asset Management
• Remote Infrastructure Management
• Public Cloud and Security Services 

Much of this work supports Critical National Infrastructure – requiring elevated security, deep expertise and locally embedded engineering teams. 

Gavin Revell, Chief Information Technology Officer at AGS Airports, reflected on the collaboration: 

“This extension will ensure we continue to deliver value to our business, its partners, and most importantly, our customers. Getronics has been one of AGS Airports’ Key partners following the business’s inception in 2014. The success has been founded upon transparency and a shared commitment to drive performance and service excellence. We are excited about the opportunities that have been identified as we continue to innovate new products and services.”

Extending the journey through 2028 

The renewed contract strengthens that forward momentum and includes: 

• €3.2M renewal of services for two years 
  
• €932K minimum commitment for additional services and projects 

Delivering today while shaping tomorrow 

Getronics’ role in modernising AGS’s technology landscape – and our commitment to continual improvement – remains central to the relationship. The renewal is a clear signal of shared confidence and a continued focus on innovation across airport operations. 

Getronics Airports Solutions: Enhancing the Traveler Experience

LEARN MORE

The post Getronics UK extends 12-Year strategic partnership with AGS Airports Ltd  appeared first on Getronics.

Strong progress across key ESG areas 

Our 2025 EcoVadis score shows significant improvements across all evaluated topics: 

• Environment: +21 points 
• Labor & Human Rights: +12 points 
• Ethics: +17 points 
• Sustainable Procurement: +20 points 

This achievement is particularly meaningful as we are being measured alongside larger organisations with dedicated ESG teams and resources. 

Our ESG journey 

Today’s award demonstrates meaningful progress under high standards, and highlights our commitment to continuous improvement in environmental, social, and governance practices. 

Key initiatives that contributed to our success include: 

• Updated Procurement Policy and ESG supplier assessments 
• First living wage analysis across our workforce 
• Reduction in carbon footprint through office and data centre efficiencies 

The Bronze badge is a milestone, but not the finish line. Getronics remains committed to enhancing our ESG practices and building on this strong foundation. We will continue to innovate, collaborate, and lead responsibly in our industry. 

Get to know the Getronics ESG initiatives in detail

SEE OUR ESG REPORTS

The post Getronics awarded EcoVadis Bronze badge: Advancing our ESG commitment  appeared first on Getronics.

“A clean audit and strong results across our key metrics reflect the hard work, discipline, and collaboration of our teams. These aren’t just numbers – they demonstrate that we’re running a business our clients and partners can trust, today and in the future.” 

Stuart Deignan, Group CEO

• Clean audit confirmation: Our Group Accounts have been independently reviewed and validated. 

• Customer satisfaction: Demonstrated through the positive experiences and loyalty expressed by our customers. 

• Security & data protection: Ongoing adherence to industry-leading standards to safeguard our data and that of our clients. 

• Service uptime: Reliable operations with consistently high system availability. 

These metrics reinforce that our operations are stable, well-governed, and designed to support our clients and partners with confidence. 

Discover our series of webinars on digital transformation, offering insights and strategies to drive innovation and growth in your business.

WATCH WEBINAR RECORDINGS

The post Trust round-up: Proof points from our business operations   appeared first on Getronics.

The end-of-year efficiency gap is rarely caused by a lack of effort. It is typically the result of structural bottlenecks, fragmented workflows, and delayed decision cycles — areas where AI can provide value, but only under the right conditions.

This year, more organisations are looking to AI to relieve end-of-year pressure — but the real differentiator is not the tool, it is the discipline behind it. Gartner predicts that at least 30% of generative AI projects will be abandoned after proof of concept by the end of 2025, often due to poor data quality, inadequate risk controls, escalating costs, or unclear business value.

That is why “efficiency with AI” should not start with automation. It should start with clarity: which workflows are truly ready, what data reflects reality, and where human judgement must remain in the loop. Otherwise, rushed deployments and over-automation don’t remove work — they amplify it.

So, how can organisations strike the right balance? The answer begins with focus. Not every process benefits equally from AI, and not every efficiency gap is technological in nature. According to McKinsey’s State of AI research, organisations that prioritise a small number of high-impact use cases — rather than spreading AI investments thinly across departments — are significantly more likely to report measurable performance improvements.

AI should therefore be treated as a capability that enhances well-defined workflows, not as a blanket optimisation layer. Efficiency gains emerge when organisations identify decision bottlenecks, repetitive workload clusters, and data-intensive tasks where automation and augmentation can realistically deliver value. 

The endless quest for efficiency 

Since the beginning of the Industrial Age, efficiency has become the holy grail in the business world. As the scale of mass production grew in the early 20^th century, famous industrialists like Henry Ford became obsessed with finding a single, optimal way of doing things. Ford famously invented the moving assembly line, slashing production time for the Model T from 12 hours to just about 90 minutes.  

The efficiency mindset gave us major breakthroughs in productivity, like standardised workflows and, eventually, tech-driven, automated processes. Still, no matter how ‘optimal’ a process is today, it can inevitably be made even more efficient later. Especially as new technologies like AI reach maturity.  

Efficiency pressures manifest differently across industries — but the structural pattern is the same. Financial institutions struggle with legacy systems that slow decision cycles and increase compliance overhead. Insurers face rising claim volumes combined with tighter regulatory scrutiny. Retailers operate on shrinking margins and volatile demand forecasts. Manufacturers manage supply chain fragility and fluctuating energy costs.

What distinguishes organisations that improve efficiency from those that merely automate is not sector — it is execution maturity. Research from IBM highlights that poor data quality alone costs organisations millions annually in lost productivity and misinformed decisions. When AI systems are layered onto inconsistent data or fragmented workflows, they amplify inefficiencies instead of resolving them.

Sustainable efficiency emerges when three foundations are in place: reliable data that reflects operational reality, workflows designed for adaptability rather than rigidity, and teams that understand how AI outputs are generated and where human judgement must intervene. 

Are quick wins too good to be true? 

AI success stories are increasingly visible — from faster mortgage processing at NatWest to accelerated claims handling at Aviva. These examples demonstrate what is possible when AI is applied with discipline. However, scaling those outcomes requires more than replicating tools. It requires replicating governance.

Research from McKinsey shows that organisations achieving the strongest returns from AI are those that combine technological deployment with risk management, explainability, and human oversight frameworks. Quick wins are rarely the result of automation alone — they are the outcome of structured implementation.

In highly regulated industries such as banking and insurance, efficiency gains must coexist with accountability. Regulators increasingly expect transparent decision logic and documented model behaviour. The EU AI Act, for example, introduces explicit requirements for high-risk AI systems, reinforcing the need for explainability and traceability.

Data quality remains the silent multiplier. According to IBM, poor data quality costs organisations millions annually in operational losses and decision errors. AI systems trained on incomplete or biased data may perform well under stable conditions, but can deteriorate rapidly when market dynamics shift.

Across industries, the pattern is consistent: sustainable efficiency is not created by removing humans from the loop — it is created by redefining their role. Organisations must continuously ask: What is the model using? What assumptions does it make? Where does accountability remain human? And what safeguards exist if predictions fail? 

Making efficiency sustainable 

Efficiency will always be dynamic. As organisations optimise one process, new bottlenecks inevitably emerge elsewhere. AI can relieve operational pressure — but only when deployed within a structured governance and capability framework.

Sustainable efficiency depends on three enduring principles: disciplined data management, clearly prioritised use cases, and defined human accountability. Organisations that formalise oversight — clarifying who owns model performance, how outputs are monitored, and when interventions are required — reduce the risk of unintended consequences while strengthening long-term value creation.

Governance is not an administrative burden. It is a performance safeguard. The EU AI Act reinforces this direction by introducing increasing expectations around transparency, traceability, and risk management for high-impact AI systems. Enterprises that embed these principles early will not only remain compliant — they will scale more confidently.

As year-end pressure builds, the most resilient organisations will resist the temptation of short-term optimisation at the expense of structural clarity. AI does not replace judgement. It augments it. And when built on accountability, adaptability, and continuous learning, it becomes a durable efficiency advantage rather than a seasonal quick win.

If you are evaluating how AI can strengthen operational resilience and performance in your organisation, our team can help you assess readiness, governance maturity, and practical next steps.

The post Efficiency under pressure: Can AI fill your end-of-year efficiency gap?  appeared first on Getronics.

At the same time, ransomware groups are shifting focus toward operational technology (OT) environments, recognising that production downtime creates immediate financial leverage. As manufacturing accelerates digital transformation, cyber resilience is no longer a technical concern — it is a board-level priority.

“In the next 12 months, cybersecurity risk will intensify, driven by AI-powered attacks, expanding connectivity, and geopolitical disruption. Quantum computing, climate volatility, and digital supply chains are adding new layers of exposure that will test operational resilience across the sector.”

What’s changing

AI Amplification: attackers now use AI to automate reconnaissance and craft convincing phishing campaigns. Expect faster, more targeted intrusions, especially through suppliers and contractors.

Quantum Computing: quantum isn’t breaking encryption yet, but the clock is ticking. Manufacturers should begin cataloguing where cryptography protects critical data and plan for post-quantum migration.

Hyper-Connectivity: the growth of IoT and OT-IT convergence widens the attack surface. Remote access for maintenance and connected suppliers increases lateral-movement risk.

Geopolitics: global tension is driving more state-linked and ideologically motivated attacks on industrial targets. Supply chains are both a risk vector and a resilience opportunity.

Climate Disruption: extreme weather can combine with cyber incidents, stressing physical sites, power, and data recovery.

Bio-Digital Risk: emerging mainly for life sciences and precision manufacturing, regulators are tightening compliance around data and IP protection.

Expected impacts in 2026

• More ransomware-driven factory downtime
• Increased supplier-linked compromises
• Rising insurance costs and stricter controls
• Regulatory scrutiny under the new UK Cyber Governance Code
• Greater board accountability for operational resilience

12-month priority actions

Be incident-ready – update and test joint OT/IT response plans.

Secure the supply chain – assess top suppliers for cyber posture and backup arrangements.

Segment and protect – strengthen network boundaries and restrict remote access.

Close the basics – enforce MFA, remove legacy logins and train staff against phishing.

Verify backups – maintain immutable, offline copies of critical system data.

Plan for quantum – start your cryptographic inventory now.

Control AI use – govern employee and vendor use of AI tools to prevent data leakage.

Report upwards – deliver cyber KPIs to the board and align with the new governance code.

10 key metrics for 2026

1. Downtime hours due to cyber incidents: direct measure of operational impact and revenue risk.
2. Mean Time to Detect (MTTD) / Mean Time to Respond (MTTR): speed of detecting and mitigating attacks – critical for resilience.
3. % of production systems with verified offline backups: ensures the ability to restore SCADA/PLC, ERP, and critical data after an incident.
4. % of Tier 1 suppliers assessed for cyber risk: visibility into key supply chain dependencies and potential disruption points.
5. % of suppliers meeting minimum security controls (MFA, patching, backups): Ensures supplier resilience and reduces attack surface.
6. Phishing simulation success rate (% of users who click / report): tracks human vulnerability, the top vector for AI-amplified attacks.
7. % of systems protected by MFA: measures credential security coverage. Essential against automated attacks.
8. Number of OT/IT incident response exercises completed: shows operational readiness for combined cyber-physical events.
9. Residual cyber risk trend (High/Medium/Low): aggregated board-level risk indicator; supports governance and insurance alignment.
10. Backup restore success rate (%): confirms the effectiveness of business continuity and disaster recovery processes.

Learn more about the Getronics Manufacturing Solutions

More info

The post The 2026 Cyber Threat Outlook for UK Manufacturing appeared first on Getronics.

What are the Top 5 Benefits of Technology in Private Education? 

1. Improved Accessibility and Inclusion  

One benefit of technology in education is its ability to make learning more accessible. Digital learning platforms allow private schools to offer both remote and hybrid learning options. This means students can attend classes from home, in person, or a mix of both, depending on the situation. In case of pandemics or emergencies that can affect classroom learning, these platforms keep students on track in their studies. 

Moreover, technology solutions for private school environments can cater to students with disabilities or learning challenges through assistive tools. Screen readers, speech-to-text, custom interfaces, and other solutions help bridge the gap between physical and virtual classrooms, encouraging greater equity and inclusion. 

2. Personalised Learning Paths with Data-Driven Precision 

Traditional classrooms struggle with a one-size-fits-all approach. With the help of personalised learning systems and adaptive digital platforms, educators can tailor content and pacing to each student’s unique needs. These systems use data analytics to identify learning gaps and provide targeted interventions, ensuring no student is left behind. 

For example, if a student is consistently struggling with fractions in a maths programme, the platform can automatically assign visual tutorials focused on that topic. At the same time, it also ensures that other students who have mastered it move on to more advanced concepts. Besides, education technology solutions also help education leaders boost students’ exam success rates and promote better use of teacher resources. 

3. Enhanced Student Engagement Through Modern Tools 

Nowadays, students are constantly bombarded with digital stimuli – from social media scrolls to endless app notifications. This instant gratification has rewired the brain to crave speed and novelty, reducing the attention spans of young minds.  

With student engagement tools like gamification apps, interactive whiteboards, and AR/VR content, even passive learners can become active participants. By transforming abstract or challenging concepts into visual, tactile, and interactive experiences, these IT solutions for private education make lessons more accessible, engaging, and rewarding. 

4. Real-Time Feedback and Performance Monitoring 

Gone are the days of waiting for paper-graded tests. Digital learning platforms allow for instant assessments and analytics dashboards that track student performance in real time. Educators can now monitor progress and identify learning gaps to adjust instruction accordingly. 

For students, this translates into prompt, meaningful feedback that encourages continuous progress rather than waiting for delayed corrections. Whether it’s a short quiz, an interactive exercise, or a full project submission, these platforms deliver instant insights, helping learners reflect, adjust, and take active control of their development. 

5. Better Collaboration and Communication 

Learning today is no longer confined to the four walls of a classroom. With the rise of cloud-based platforms and smart communication tools, collaboration has gone virtual. Students can work together on assignments from anywhere, while teachers and parents stay connected through real-time dashboards that track progress, updates, and feedback. Together, these pave the way for a more unified learning experience. 

From Microsoft Teams to Google Classroom, IT solutions for education are streamlining communication like never before. This is especially vital in Singapore and Malaysia multilingual, multicultural school settings that value coordination among stakeholders. 

Conclusion 

As digital adoption accelerates across every industry, educational institutions cannot afford to fall behind. Many still struggle with fragmented systems or outdated infrastructure. By investing in robust education technology solutions, schools can align with technology goals, improve learning outcomes, and strengthen institutional resilience. 

At Getronics, we help institutions bridge these gaps through end-to-end technology solutions that align with academic goals, empower educators, and deliver richer student experiences. 

Contact us and let us help your institution lead accelerate digital transformation with confidence. 

Learn more about the Getronics IT Solutions for Higher Education

MORE INFO

The post 5 Benefits of Technology in Private Education  appeared first on Getronics.

The bus industry continues to face a challenging landscape. Outside of London, passenger numbers remain nine per cent below pre-COVID levels, with 15 per cent fewer bus miles operated since 2019. 

In an effort to get people back on board, both government and private operators are going full speed ahead on sustainability. Earlier this year, a further £37.8 million was allocated through the Zero Emission Bus Regional Areas (ZEBRA) scheme to help fund 319 new green buses across the UK.

But while greener fleets are essential, their impact will be limited if we don’t see more people choosing to travel by bus. The real opportunity lies not only in electrifying vehicles, but in transforming the passenger experience – making journeys simpler, safer and more reliable.

Buses have always been a vital part of Britain’s transport ecosystem. They connect towns and villages, support local economies and offer an essential service for millions who rely on public transport every day. Yet, despite their social and environmental importance, for many people, the bus has slipped down the list of preferred ways to travel. The Getronics Bus Trust Tracker explores why. 

Based on research conducted among 2,500 UK residents, it examines how people really feel about buses today – how often they ride, what stops them and what could get them back on board. Crucially, it looks at the role of technology in shaping that future and reveals that while sustainability matters, trust, information and passenger experience hold the key to getting the UK back on board. 

The state of the bus nation

The bus remains one of the most widely available modes of transportation, yet usage varies considerably, even among those with direct access to bus routes.

Our research shows that 54% of Brits take the bus less than once a week. Outside of Greater London, that figure rises to 59%, highlighting a divide between the capital’s extensive transport network and the rest of the UK. For more than a quarter of people, 28%, the bus is something they board just once every six months or less, and 17% of Brits say they never take the bus at all.

That is a lot of empty seats, and an even bigger opportunity.

Despite major investment in clean fleets and fare initiatives in some regions, usage has not fully recovered to pre-pandemic levels. Beneath these topline numbers, however, a more nuanced story emerges – one shaped by geography, perception and technology.

A country of contrasts

In Greater London, people use the bus an average of 142 times per year, around three times a week. By contrast, passengers in the South West and Wales take the bus 49 times per year, roughly once a week.

It is not simply about geography: local culture, ticket pricing and perceptions of reliability all shape behaviour. In London, a single capped fare and integrated travel system make bus journeys predictable and affordable. Elsewhere, the story is less straightforward.

In the West Midlands, 29%, East Midlands, 28%, and the South East, 27%, of people are likely to say that fares are too expensive. This is the single biggest deterrent to bus travel in these areas, outside of reliability concerns.

In London, people take the bus around 99 times per year (roughly twice a week) but in Bristol, that figure drops to just 48. It’s a reminder that even in major cities, where population density and travel demand are high, frequency of use isn’t guaranteed. Something beyond geography or affordability is shaping behaviour.

When asked how often they would use the bus if a convenient route met their regular travel needs, Londoners again topped the chart, saying they would travel by bus around three times a week or 172 times per year. In Wales, the average drops to 74 times per year, showing that even when the infrastructure exists, other barriers persist.

Average annual bus use by region, for those who have access to local routes

Regional nuances

In Scotland, there is a clear link between environmental awareness and openness to public transport. 63% of people in Edinburgh said they would be more likely to take the bus if the fleet were more eco-friendly, compared to just 37% in Cardiff.

Perceptions of safety also vary. In London, 63% of respondents said feeling safer would make them more likely to use the bus, while in Wales, only 28% agreed.

Trust and optimism are much higher in regions with major investment in transport integration. In Edinburgh, 58% of residents said they are likely to use the bus more often in the next 12 months, with 55% in London and 54% in Manchester saying the same. In Sheffield, that figure drops to 31%. Where joined-up transport exists, confidence follows.

The sustainability factor

People know that buses are a more environmentally friendly option, but this does not automatically translate into action. Only 20% of people said their current daily mode of transport is more sustainable than taking the bus; however, most are still choosing other modes of transport for their daily travel.

Half of those surveyed in Greater London (53%) the East Midlands (50%), the North West (50%) and the East of England (48%) agree that bus travel is more sustainable than their usual journey. Despite this, when asked about eco-friendly upgrades, only 51% of Brits said they would be more likely to use buses if the fleet were greener, such as using electric or hydrogen vehicles.

That is an encouraging signal for operators investing in low-emission technology. But it also shows that sustainability alone is not enough. The decision to travel by bus depends on a lot more than just reducing environmental impact. 

What’s stopping people?

When asked why they do not take the bus more often, respondents highlighted a number of barriers. The top ten are:

1. Buses are often delayed or not on time (30%) T
2. Journey time by bus is too long (30%) T
3. Buses are often overcrowded (24%) T
4. Bus fares are too expensive (22%)
5. Lack of reliable information about times or routes (15%) T
6. The physical experience of bus travel is uncomfortable (15%)
7. They are not easily able to access bus services where they live (12%)
8. Buses do not connect well with other transport (11%) T
9. They do not feel safe on buses (8%) T
10. Lack of onboard features such as Wi-Fi or USB charging (7%) T

70% of these issues can be directly improved through improved technology. This shows that where confidence lags, technology can lead.

NOTE: The factors featuring T are all things that can be overcome with tech.

The technology turning point

Brits are clear about what they want from bus companies, and much of it involves using technology to make journeys more transparent, predictable and pleasant.

69% of people told us that bus companies could make technological changes that would make them more likely to travel by bus or that would improve the experience. 

That is more than two-thirds of the UK who would be more likely to take the bus if technological measures were employed to improve passenger experience. This is a huge opportunity, not only for bus operators to fill seats, but for the UK to hit its net zero targets. 

Technology does not just improve convenience. It is the single biggest thing operators can do to get people back on board with bus travel. When passengers feel informed and in control, they are far more willing to choose the bus over other forms of travel.

Respondents told us the three most impactful changes would be:

This appetite for digital improvement also spans generations. Younger groups are the most enthusiastic, with 86% of 16 to 24-year-olds and 88% of 25 to 34-year-olds saying better tech would encourage them to use buses more; however, even among those aged 55 and over, 51% agreed.

Technology does not just improve convenience. It is the single biggest thing operators can do to get people back on board with bus travel. When passengers feel informed and in control, they are far more willing to choose the bus over other forms of travel.

Passenger trust

Trust in transport is not only about safety or data protection. It is about reliability. Passengers need to know the bus will arrive when expected, that fares are fair, and that information is accurate.

In our interviews, passengers often spoke about uncertainty. As one commuter put it: “When the bus works, it’s great. But so often it’s late and there’s no way to know when it will arrive or whether it will be massively overcrowded when it does. It’s not a risk I’m willing to take on my commute.”

Technology cannot solve everything, but it can deliver the accountability passengers are looking for. Real-time tracking, predictive maintenance, automated fleet coordination and accurate passenger apps can all help to rebuild confidence.

When passengers can trust the service to do what it says, that trust extends to the brand and the operator behind it.

What this means for bus operators

For operators, the implications of this research are both practical and strategic. 

• Invest in passenger-facing technology, not only back-end systems. Real-time information, predictive tools and clear service updates build day-to-day trust. 

• Integrate across modes. Passengers want to plan whole journeys, not just bus routes. Collaboration between bus, rail and local transport providers will drive long-term loyalty. 

• Communicate reliability. When delays happen, be transparent and ensure you have up-to-date live information. 

The opportunity is clear. The desire for technology-driven change exists across all age groups and regions. The next move belongs to the operators.

Conclusion: passenger experience is king

Buses are the quiet workhorses of the UK’s transport system. They keep towns, cities and communities connected and offer a unique opportunity to reduce the nation’s carbon footprint… if only more people chose to get on board.

The Bus Trust Tracker highlights a public frustrated by the outdated technology that underpins bus travel. People want to use buses more often, but improving the passenger experience must be the priority and technology is central to making that happen.

From accurate live information and simpler journey planning to better communication and more reliable services, tech-enabled improvements can make bus travel faster, safer and more predictable.

The destination is clear: a better passenger experience will mean fuller buses.

Methodology

Quantitative research was conducted by Censuswide among a sample of 2,500 UK residents in October 2025. Censuswide abides by and employs members of the Market Research Society and follows the MRS Code of Conduct and ESOMAR principles. It is also a member of the British Polling Council.

Qualitative research was undertaken by Getronics, including in-depth one-to-one interviews with five UK residents who regularly use or have access to local bus routes.

The post Getronics UK Bus Trust Tracker 2025 appeared first on Getronics.