4 min to readDigital Workplace

Building a secure and intelligent Digital Workplace

Ty JohnsonSolution Architect - Digital Workplace, Software & Cloud

As someone deeply involved in the Microsoft 365 and Modern Workspace, I’ve seen the struggles organisations face when it comes to balancing security, compliance, and productivity. My role isn’t just about selling solutions—it’s about advising, guiding, and helping organisations make sense of complex challenges. Recently my focus has been on three key areas that I believe are critical to a strong digital workplace: Data Loss Prevention (DLP), Content Labelling, Data Lifecycle Management, and the foundational role these play in an organisation’s AI journey

The challenges of deploying sensitivity labelling and DLP

I’ve had countless conversations with IT teams who have been handed the responsibility of implementing sensitivity labelling and DLP with little input from the actual data owners. The reality is that this isn’t just an IT problem—it’s a business-wide responsibility. Yet, time and again, IT is left to define classifications, apply labels, and enforce policies without the necessary context from Compliance and Governance teams.

This needs to change. IT should be an enabler, not the sole owner of data security. The challenge isn’t just technical—it’s cultural. Organisations need to see data protection as a collective effort, with IT playing a key facilitation role rather than simply being tasked with implementation. Finding ways to bridge these gaps and bring the right stakeholders together will be a major focus for me throughout 2025.

Data Lifecycle Management (DLM): more than just retention policies

DLM often gets reduced to retention policies, but it’s so much more than that. Businesses generate data at an unprecedented rate, and without a proper lifecycle strategy, they end up drowning in redundant, obsolete, and trivial (ROT) data. Managing this effectively isn’t just about compliance—it’s about efficiency and cost savings.

The three key aspects I emphasise when working with organisations are:

Storage Optimisation: Storing the right data in the right place without unnecessary sprawl.
Retention Management: Keeping essential data while ensuring compliance with evolving regulations.
Eliminating ROT: Identifying and clearing out data that no longer holds value, reducing risk and improving performance.

I find that when businesses truly understand the importance of DLM, they begin to see it as a strategic function rather than just another IT task. It’s about enabling teams to work smarter, not harder; by ensuring they have access to the right information when they need it—without being bogged down by clutter.

How DLP, DLM, and Content Labelling lay the foundation for AI

One of the most exciting shifts in technology is the integration of AI into the workplace, but AI is only as good as the data it has access to. The strength of AI models depends on clean, well-governed, and properly classified data. Without a strong foundation in DLP and DLM, AI risks amplifying bad data, introducing compliance risks, and generating content that lacks context.

When I talk to organisations about AI, I break it down into three main pillars:

Productivity: AI-driven tools can streamline workflows, summarise content, and improve efficiency.
Content Generation: AI’s ability to generate and refine content is only as good as the data it has access to. Proper data classification and governance ensure that AI can surface relevant, high-value content rather than ROT.
Automation: AI-powered automation has the potential to transform processes, but only if built on a secure and structured data foundation.

This isn’t just about Microsoft Copilot or any one tool—it’s about a mindset shift. Businesses need to start thinking about AI readiness now by ensuring their data is properly governed, protected, and accessible in a way that adds real value.

Looking ahead: helping businesses bridge the gap

My role as an advisor is about more than just recommending tools—it’s about helping businesses navigate the complexities of modern work.

The organisations that will thrive with AI this year will:

Take a proactive approach to data governance by ensuring security, compliance, and accessibility are embedded in their processes.
Break down silos between IT, Compliance, and Business teams to make data protection a shared responsibility.
Strengthen Data Lifecycle Management by reducing ROT (Redundant, Obsolete, and Trivial data), improving storage efficiency, and ensuring compliance.
Adopt AI with a structured foundation by classifying and protecting data to drive intelligent automation and content generation.
Educate employees by fostering a culture of data awareness and security while training staff on classification, retention policies, and responsible AI usage.

The future of work is evolving rapidly, and those who act now will lead the way. I’m excited to help organisations take these steps and shape a smarter, AI-ready workplace—one step at a time

Contact us today

As you digest these insights and consider the strategic steps your organisation needs to take, I encourage you to explore further resources and opportunities with us to deepen your understanding and implementation of AI solutions. Continue your journey toward an AI-ready workplace with SoftwareOne.

Let’s talk

Contact us today

Author

Ty Johnson
Solution Architect - Digital Workplace, Software & Cloud

As a seasoned IT professional, my journey with SoftwareOne has reignited my passion for the IT industry. I thrive on navigating the complexities and overcoming the challenges of our digital world. My current role has provided me with the opportunity to delve into M365 and AI, leveraging my extensive experience across various industries.

With over a decade of experience in the M&A space, I have served as an enabler and facilitator for both buyers and sellers across various industries, including Construction and Medical.

As an avid snowboarder, I have travelled the world in search of fresh powder. In my spare time, I enjoy working on my collection of project cars, which range from nearly complete to those that have seen significant investment.

Building a secure and intelligent Digital Workplace

The challenges of deploying sensitivity labelling and DLP

Data Lifecycle Management (DLM): more than just retention policies

How DLP, DLM, and Content Labelling lay the foundation for AI

Looking ahead: helping businesses bridge the gap

Contact us today

Contact us today

Author

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