In ‘The Data & AI Readiness Playbook’ we explain how you can unlock the value of your business data. Quality data is crucial to the effectiveness of AI. Here we look in more detail at the importance of data culture and the practical steps you can take to build a great data culture.    

Data is perhaps the single greatest asset of the modern business and the bedrock of successful AI initiatives. But the quality of that data is critical to success.  

The ROI of investing in data quality

Already convinced of the importance of quality data? Then skip ahead to ‘Developing a great data culture’, otherwise read on.  

When we refer to quality data, we mean that it is accurate, complete, consistent, timely, valid, unique, and reliable. Armed with that, both human and artificial intelligence can arrive at the decisions that deliver real value.

Matthew Ebo is Assistant Strategic Insights Manager at Lloyds Banking Group and a contributor to ‘The Data & AI Readiness Playbook’. Matthew explains, “The cost of AI is an investment, but one that pays off in saved time, better decision-making, and automation of repetitive tasks”.  

Developing a great data culture is an investment. An investment in the raw materials for transforming how an organisation operates, competes, and grows. For the business, this can drive value in many ways: 

• Better, evidence-based decisions enabling more effective strategies, faster responses to market changes, and improved stakeholder buy-in for new initiatives. 

• Increased innovation and agility as the organisation becomes better at identifying new opportunities, anticipating trends, and proactively adapting to changes.  

• Improved operational efficiencies as data insights help identify inefficiencies and optimise processes and resource allocation.  

• Greater competitive advantage gained from better anticipation of customer needs, reaction to industry shifts, and speedier innovation.  

• Enhanced customer experience through superior analysis of customer data, to tailor products, services, and communications to better meet customer needs.  

• Boosted employee engagement as staff become more engaged, and invested in the success of the business, by using data in their roles. 

• Trustworthiness – data driven cultures tend to be open about business decisions improving trust amongst employees.

A great data culture enables smarter decisions, drives innovation, enhances customer and employee experiences, and provides a competitive edge. 

So how do you get one?  

Developing a great data culture

We know that AI initiatives are only as good as the data they access, so data quality is key – and great data follows a great data culture. 

Data quality isn’t solely the responsibility of IT: it’s everyone’s responsibility. But it is IT’s responsibility to encourage a culture in which everyone cares about data quality“, explains Dan Knott, Data & AI Practice Lead, Cloud Direct.

A great data culture is one where data is valued by an organisation and its people, becoming a key part of daily operations. Here are eight key aspects of a great data culture.  

1. Leadership commitment and example
As with most aspects of culture, data culture needs to be led from the very top. Senior management need to be actively involved in communicating the importance of data to organisational success. This needs to be supported with investment in the resources, training, and technology to support data initiatives.

2. Data-driven decision making
It needs to become the norm that decisions, at all levels, are based on data and analysis and not just intuition or hierarchy. Leadership and example are an important part of this. It also means establishing processes that make data analysis a standard part of planning, operational, and problem-solving activities.

3. Data access and democratisation
For IT this means ensuring that employees have easy, secure access to data and analytics tools. Employees should be able to freely share data internally, within appropriate privacy and security parameters, to enable collaboration.

4. Data literacy and training
Key to all this is an ongoing investment in employee’s data awareness and skills, ideally with training tailored to different roles and data personas. This should equip staff with the skills to interpret analytics, know when to use data, and to ask the right questions about data quality.

We’re looking at AI in the same way as other tools which become part of the workforce’s toolbelt, so we have to provide the same level of training for it. It’s not only imperative that the right skills are gained, but that they are regained as time goes on“, explains Mike Downing, Chief Technology Officer at insurance nonprofit WPA

5. Continuous learning and improvement
Alongside formal training initiatives, organisation’s need to develop a mindset of ongoing learning, experimentation, and adaptation – constantly utilising data to refine strategies and processes.

6. Trust in data quality
Underpinning this, there needs to be organisation-wide confidence in data accuracy and consistency. People know where data comes from and how reliable it is. This requires robust data governance, clear data lineage, and transparent processes for data validation and error correction.

7. Collaboration and communication
Success will be evidenced through open communication and collaboration around data, with teams working together to solve problems and share insights. This should be openly encouraged. It is important that this is also supported by establishing a common ‘data language’, so everyone communicates effectively.

8. Accountability and measurement
The final aspect of great data culture is one of transparency and it is an extension of point two. Clear goals and metrics are set for data initiatives, with progress tracked and results linked to business outcomes. With performance KPIs relating to data usage built into everyone’s evaluations.

Together, these elements can help you to build a great data culture that will deliver demonstrable value to your organisation and support effective use of AI.  

Next Steps

Download a copy of The Data & AI Readiness Playbook to learn more. You’ll discover how others are preparing for and using AI, and a seven-step process to unlock the value of your business data.  

It’s 2026, and efficiency is the name of the game. For a number of years now, IT teams have been under constant pressure to do more with less, all while enabling innovation and protecting their security posture.

 Getting to this point has seen the proliferation of “best in breed” solutions, which has led many businesses to manage sprawling estates of disparate platforms, vendors, and integration points. But now, a growing movement towards vendor consolidation is shifting the paradigm. More organisations are choosing to streamline their supplier lists and partner with a single Managed Service Provider (MSP) for their Microsoft estate.

What makes vendor consolidation so compelling? There are a number of commercial, operational, and strategic benefits to rationalising your technology stack and supplier ecosystem.

The Commercial Case: Cost savings and predictable spend

Managing multiple vendors can quickly lead to spiralling costs, both directly and indirectly. Each additional supplier brings its own set of contracts, licensing models, support fees, and renewal cycles. Over time, this complexity drives up administrative expenses, increases the risk of duplicated licensing, and makes it difficult to negotiate favourable commercial terms.

By consolidating your vendor list – particularly around a single MSP for your Microsoft environment – you gain significant negotiating leverage. A unified contract covering M365, Azure, and associated services enables bulk purchasing, volume discounts, and streamlined renewals. Instead of juggling myriad line items and invoices, your finance team deals with a single, predictable bill. This clarity reduces the risk of budget overruns and enables more accurate forecasting.

Additionally, a trusted MSP can help you right-size your licensing and cloud consumption, identifying opportunities to eliminate shelfware and optimise usage. With fewer vendors and clear visibility of entitlements, organisations spend less time reconciling and more time innovating.

The Operational Case: Reducing administrative overheads

Vendor management is resource-intensive. Every supplier relationship demands due diligence, onboarding, security reviews, compliance assessments, ongoing performance monitoring, and periodic contract renegotiations… the list goes on. Multiply this by dozens of vendors, and your IT and procurement teams can become overwhelmed by administrative tasks that add little strategic value.

Consolidation is the answer. Engaging a single MSP to manage your Microsoft estate means one point of contact for all your support, renewals, and service escalations. There’s no longer a need to track which vendor is responsible for which component, or to referee disputes between overlapping providers. Support requests are simplified – whether it’s a technical issue, a billing question, or a feature enablement, you know exactly whom to contact.

What’s more, a single MSP can offer holistic reporting, monitoring, and service management. With a unified dashboard and agreed service levels, you gain a clear view of your environment’s health and performance, enabling proactive management rather than reactive firefighting while jumping from one conversation to another.

Simplified Support and Accelerated Resolution

When incidents occur, speed is of the essence. In a fragmented environment, support requests can pinball between vendors, with each pointing fingers or requiring separate troubleshooting before a root cause is found. This slows down resolution, increases downtime, and frustrates users.

With a consolidated approach (especially when working with an MSP that oversees your entire Microsoft estate) the accountability is clear. Your MSP understands the full stack, from identity and access management to endpoint security and collaboration tools. Their cross-domain expertise means they can triage, escalate, and resolve issues without the friction of inter-vendor boundaries.

The result? Reduced Mean Time To Resolution and higher end-user satisfaction.

The Strategic Case: Enterprise-grade integration with Microsoft

Microsoft’s cloud suite, which encompasses M365, Azure, Defender, and Power Platform, offers enterprise-quality solutions spanning productivity, security, compliance, analytics, and automation. By standardising on Microsoft, organisations benefit from deep integration, a unified identity model, and common policy controls.

A tightly integrated platform reduces the need for custom connectors, fragile APIs, and manual workflows. Security and compliance are easier to enforce, as audit trails, access controls, and data loss prevention policies can be set once and applied universally. Feature releases and updates are synchronised, ensuring compatibility and reducing technical debt.

In contrast, managing a patchwork of “best in breed” tools may deliver niche capabilities at the cost of complexity. Each application may have its own authentication standards, update cycles, and support models, which increases the risk of security gaps, configuration drift, and costly integration efforts. Moreover, keeping skills current across multiple platforms pulls IT resources in many directions.

Innovation at Scale

Vendor consolidation unlocks agility. With a unified Microsoft stack managed by an expert MSP, your organisation can deploy new features, scale services, and adapt to regulatory changes in a speedier fashion. A consistent platform accelerates cloud adoption, enables seamless collaboration, and empowers business units without the friction of platform sprawl.

Your MSP can focus on continuous improvement, suggesting best practice architectures, automation opportunities, and proactive security measures. Freed from vendor wrangling, your team can devote energy to transformation and user adoption.

Less is more

Consolidating your vendor list and standardising on a trusted MSP for your Microsoft estate isn’t just about administrative convenience. It enables cost control, risk reduction, and innovation, and by choosing a comprehensive, enterprise-grade platform and a single expert partner, you position yourself for greater success in the age of AI. Less really is more.

Introduction 

End users are now the last line of defence for protecting your IT infrastructure.  

Are you confident they have the tools and knowledge to successfully keep attackers out?

Identity attacks have continued to rise using tactics such as password spray to gain unauthorised access. With over 99% of unauthorised access attempts being blocked by Multi-Factor Authentication. It is crucial employees are equipped with the right tools to protect your organisation.

Increasing hybrid and remote employees makes the need for robust, intuitive security solutions more critical than ever. Microsoft Defender, supports organisations by offering layered protection, integrated intelligence, and a user-focused approach to security. Defender empowers organisations to protect against major attack vectors and enables employees to work flexibly and securely. 

End-User Protection Against Attacks Vectors

From phishing emails to fileless malware, users encounter a wide spectrum of attack vectors daily. Microsoft Defender shields users from malicious links and attachments by scanning emails, documents, and tools in real-time. Taking away much of the burden, and equipping employees with knowledge of potential threats. Defender’s robust endpoint protection leverages AI-powered threat detection to block suspicious activities before they can cause harm. This can reduce the risk of breaches from drive-by downloads, rogue applications, or credential theft. 

End-users gain peace of mind as automated protections work seamlessly in the background, so they can focus on their work without worrying about clicking a link and accidentally setting off a cyber breach. Defender’s user-friendly guidance and actionable steps also help demystify security, encouraging a culture of shared responsibility.   

Beyond Defender: The Power of Integrated Security Ecosystem 

While Microsoft Defender is a powerful foundation, its effectiveness multiplies when integrated with complementary tools within the Microsoft security ecosystem. Conditional Access, for example, extends user protection by enforcing policies that evaluate both the context and risk level of access requests. If a user attempts to log in from an unfamiliar device or location, Conditional Access can prompt for additional authentication or block access altogether. This mitigates the risk of compromised credentials. 

Furthermore, Microsoft’s Extended Detection and Response (XDR) capabilities, consolidates security telemetry from across your environment. These tools ensure your security teams gain a centralised view of the entire digital estate. For end users, this consolidation means faster detection and remediation of threats. Further good news, even if a phishing attempt slips through email defences, XDR can correlate signals to quarantine the threat and guide users through recovery steps. 

Cost Benefits within M365 Licensing 

For many organisations, cost is a significant consideration in security strategy. Microsoft Defender’s inclusion within Microsoft 365 licensing delivers exceptional value:  

• Advanced protection features are available without the need for costly third-party solutions or complex integrations.  

• Users benefit from consistent experiences across devices and platforms. 

• IT teams can deploy, manage, and monitor security policies from a unified console. 

This consolidation not only reduces operational overhead but ensures that security is not sacrificed for the sake of budget constraints. 

Facilitating Secure Flexible Work 

An increasing number of the workforce are looking for flexible working options, including hybrid and remote models, however, with this security perimeters need to be considered. 

Microsoft Defender’s cloud-native architecture and integration with Azure Active Directory enable employees to work securely from anywhere. Real-time threat intelligence ensures that whether in the office or on the move, users remain protected against emerging threats. 

Conditional Access policies further empower organisations. An ability to dynamically assess risk and adapting controls based on user behaviour and context. For employees, this translates into frictionless access to resources with confidence that their security is not impacted. 

AI-Driven Security: Respecting Configurations and Amplifying Protection 

AI is at the heart of Microsoft’s security stack, enabling smarter defences and more adaptive protections. Solutions like Microsoft 365 Copilot and Security Copilot, ensure that user data remains governed by the existing security configurations.  

Microsoft 365 Copilot operates within the boundaries of user permissions, never exposing information to which a user does not have access. This means that the efficiency of AI-powered assistance never come at the expense of data security or privacy. This trust is vital for users to leverage AI tools confidently in their day-to-day work. 

Security Copilot, meanwhile, is poised to transform the incident response lifecycle. Security Copilot can automate Endpoint Detection and Response (EDR) workflows, rapidly triaging alerts, correlating events, and even suggesting or executing remediation actions. This means that incidents are resolved faster, with minimal disruption and less risk of human error. 

Conclusion 

In an era where cyber threats are ever-present and working patterns are more dynamic than ever, an integrated security suite offers organisations a compelling advantage. From defending against major attack vectors to enabling secure, flexible work, Defender empowers users to navigate the digital world with confidence. When complemented by tools like Conditional Access, XDR, and AI-powered solutions, the benefits extend far beyond basic protection.  

Ultimately, the best security is the kind users barely notice: always present, always vigilant, and always enabling them to do their best work. 

Ready to discuss how you can make better use of Microsoft Defender and improve your security posture? Speak to one of our experts by filling in the form below.

Every IT decision maker understands the importance of a clear cloud strategy. It is not just about where you host your apps. Your strategy must actively support the overall mission of your company. The challenge is that Azure evolves at lightning speed. New features, services, and security standards appear constantly, making it hard for teams to keep up. 

This is where many organisations fall into the trap of reactive cloud management. They spend all their time fixing problems and responding to immediate demands. Whereas proactive management requires something different. It needs dedicated expertise that can look years ahead and guide your architecture toward future success. 

Reactive vs Proactive Cloud Management 

Reactive management focuses on solving today’s issues. Proactive management anticipates tomorrow’s challenges and positions your business to take advantage of new opportunities. Without expert guidance, your cloud strategy risks falling behind. This is what we call ‘strategy drift’. 

The Risks of Strategy Drift 

When your cloud configuration moves away from best practices, you face three major risks: 

• Unnecessary Costs: You miss new cost saving features or fail to adapt to licensing changes. 

• Missed Innovation: You do not adopt AI or data services that could give your business a competitive edge. 

• Security Gaps: Your architecture fails to keep up with the latest security standards, leaving vulnerabilities unaddressed. 

A dedicated expert resource such as a specialist Azure Solution Architect can help to prevent these risks. However, hiring a full time Azure Solution Architect is expensive and for most businesses their expertise is only needed for major projects or complex upgrades. So how do you access that high level insight when you need it most? 

Five Expert Tips for IT Decision Makers 

To future proof your Azure strategy, here are five essential tips: 

1. Prioritise Proactive FinOps: Do not wait for the bill to arrive before thinking about costs. Implement automated rules and architectural best practices to ensure continuous cost optimisation. 

2. Plan for AI Adoption: Azure is rapidly integrating AI features. Your cloud strategy should include a roadmap for leveraging services like Copilot and advanced Data and AI platforms, such as Microsoft Fabric, to drive business growth. 

3. Strengthen Security Posture: Regularly review your architecture against the latest security standards. Proactive security checks prevent vulnerabilities before they become incidents. 

4. Align with Sustainability Goals: Track CO₂ emissions in your Azure usage and integrate sustainability targets into your cloud roadmap. 

5. Leverage Azure Expert Advisory: The best way to ensure your strategy is sound is by partnering with a Microsoft Azure Expert MSP. Selecting the right partner will bring certified expertise and proven experience to help you deliver business value. 

CSP+ Delivers Azure Expert Advisory 

Our Cloud Direct CSP+ programme is designed to help you close the expertise gap. CSP+ is a tiered model so that you can pick the level of support that your business needs. From the essentials tier where you’ll gain an initial onboarding health check and business hours support. To the enterprise tier for 24×7 support, monthly optimisation reports and access to a dedicated Azure Solution Architect to deliver strategic advisory sessions.  

These experts provide ongoing architectural reviews to keep your Azure strategy aligned with your business goals. This includes: 

• Strategic Feature Adoption: Guidance on deploying new Azure features safely and effectively. 

• Long Term Architecture: Support in designing scalable, resilient, and secure environments. 

• Risk Mitigation: Reviewing your environment to eliminate potential security and performance issues before they become incidents. 

Expert insight through CSP+ means your internal team is never alone. You have the full weight of a certified Azure Expert MSP behind you, ensuring your cloud platform is architecturally optimised and ready for innovation. 

Ready to Strengthen Your Azure Strategy 

Stop reacting and start planning for the future. Try our CSP+ calculator to find the right plan for your business. Plus, save on costs instantly.

It’s becoming increasingly apparent that artificial intelligence will be integral to how organisations operate effectively and remain competitive. But responsibility is a topic that regularly rears its head, and the question of how you use AI responsibly isn’t one purely for IT but for your organisation’s executive leadership. Here we consider how to benefit from AI, while remaining true to your organisation’s values, obligations and stakeholders.  

Much is written and spoken of AI’s power to drive business transformation, efficiency and innovation. But as the saying goes, ‘with great power comes great responsibility’.

Using AI responsibly isn’t just about regulatory compliance. It’s about trust, safeguarding reputation, and ensuring that AI strengthens rather than undermines the organisation’s values and purpose. There are three important topics to consider – People, Planet, and Policy.

People

Let’s start by confronting the really big question: jobs. We’ve all seen and heard carefully worded references to AI’s labour-saving capabilities. It does less work, it means fewer workers, but does that also mean redundancies? This question needs considering, carefully, at a very senior level, and very early on.

They’ll need to know the expected time savings and whether these affect fractions of roles or entire roles. You should also consider timeframes in each area, and how these compare to natural attrition, retirement and contract expiration timescales. They’ll also need to know recruitment pipelines, so hiring can be slowed or redirected rather than abruptly frozen, as well as redeployment opportunities and the skills required for new or expanded roles such as AI oversight, data literacy, and creative problem-solving.

This will impact much of what follows.      

Enablement, not displacement

Responsible AI should augment human judgement and not replace it – freeing people from repetitive work. But to achieve this, it needs to be accompanied byreskilling and digital literacy programmes that enable employees to work effectively with AI systems. Success should be measured in terms of human productivity and satisfaction, and not headcount reduction.

Transparent and ethical

Everyone involved with AI, from developers to decision-makers, must understand what AI can and cannot do. Build a culture of AI literacy and ethical awareness supported by specific training on responsible data use, bias awareness, and explainability. Employees using AI outputs should be able to interpret and justify its decisions, especially in regulated sectors. Staff must appreciate that humans remain accountable for AI-assisted outcomes and feel confident challenging algorithmic decisions without recrimination.

Inclusion and fairness

Similarly, fairness and inclusion must be embedded in your use of AI. These systems will typically maintain or increase any biases in training data, so utilise diverse teams in AI design and validation. Train models with diverse data sets and monitor for bias, especially in HR, credit, or customer-facing use cases.Treat governance of AI fairness with the importance of a workplace equality and diversity issue, rather than a technical issue.

Planet

AI’s benefits should also be considered in the context of its environmental impact and sustainability. During training AI models can consume significant energy, and operationally AI infrastructure has a significant carbon footprint. But with the right actions, this can be mitigated.

Opt for energy-efficient architectures

Data centres powered by renewable energy, with liquid cooling, and using energy-optimised GPUs (Graphic Processing Units) and ASICs (Application-Specific Integrated Circuits) are more energy efficient. Also consider scheduling AI workloads to optimise power use.

Actively manage your technology lifecycle

Using cloud and hybrid models can allow you to dynamically scale, without having an over-provisioned on-premises infrastructure. Apply sustainability principles to AI hardware: responsibly sourcing, refurbishing and/or reusing, and recycling at end-of-life.

Use AI for sustainability

‘Planet’ doesn’t just mean mitigating AI’s environment impact. AI can also make a positive contribution towards meeting corporate sustainability goals through data-driven energy optimisation, intelligent logistics routing that lowers emissions, predictive maintenance to reduce waste, and carbon accounting.

Policy

A responsible use of AI also depends on robust governance that ensures transparency, accountability, and compliance. A key consideration for the board is who will be accountable for AI ethics and compliance, and how governance can be shown to be effective?

A best practice approach combines collective ownership with clear executive accountability. It is likely to blend existing structures with some new, specialised capabilities. This might take the form of a Chief Information Officer or Chief Digital/Technology Officer with primary accountability, working with a cross-functional AI Governance Board. This would include Technology, Data, HR/People, Legal, Compliance, Risk, Operations, your ESG (Environmental, Social, and Governance) team, and business unit leaders.

This will provide the basis for effectively actioning the following. 

Establish an AI governance framework

Determine the principles which will guide your use of AI. These need to be consistent with your organisation’s values and risk appetite and will typically encompass fairness, transparency, accountability, privacy, and sustainability. Bear in mind that different contexts may require different ethical considerations – what’s appropriate in one area may not be in another. AI ethics will touch IT, legal, HR and compliance so ensure that there is clear ownership within and across these areas.

Control and oversight

Integrate AI risk management into existing risk frameworks, with a focus on model validation, auditability, explainability, and version control. Track who built which model, with what data, and how it is performing. Require human-in-the-loop oversight for all critical decision and systems.

Regulatory alignment

There will be external interest in your AI use from regulators, customers, investors and other stakeholders, so aim to stay ahead of expectation. There is an EU AI Act, with most provisions applying from August 2026, and a UK AI Assurance Framework. The Information Commissioner’s Office has provided AI guidance, with sector-specific guidance expected in several areas (like from the FCA in financial services). Maintain audit trails for AI models, data lineage, and decision logic to satisfy auditors and regulators.

But, above all, be transparent about how AI is used, governed, and improved.

A final thought

Using AI responsibly requires deliberate, pre-emptive leadership. It means ensuring that AI use aligns with organisational purpose, is trusted by employees and other stakeholders, and contributes to sustainable growth. Many will do this badly, but those that do it well can successfully position their organisations as trustworthy and responsible innovators.

Cloud Direct can help you successfully benefit from AI in a real and responsible way. Request a call with a subject matter experts through the form below.