True Digital Transformation depends on more than licences, deployments or vendor promises. It requires measurable business outcomes, disciplined cloud cost management, developer adoption and the right data foundations for AI. Oliver Niemandt, GM of Sales at Cloud on Demand, unpacks the findings of the 2025 Cloud on Demand CXO Priorities Survey and shares what South African organisations need to do to convert technology investment into strategic advantage.
Can you introduce the 2025 Cloud on Demand CXO Priorities Survey: Technology Adoption and Strategic Impact report and explain what the research aimed to achieve?
Our research set out to secure an honest, unfiltered view of how South African organisations are using Microsoft technologies in practice.
There is a substantial gap between what has been licensed and what is successfully deployed on the ground.
We wanted to understand not just what they are buying, but what they are actively implementing, the strategic drivers behind those choices and precisely where their teams are getting stuck.
The ultimate goal here is to provide CXOs with a realistic benchmark against their peers. By stripping away the usual vendor narrative, we are delivering the raw ground truth so leadership teams can make informed, data-driven decisions.
Many companies resist cloud or face strategic indecision. What is the single most detrimental consequence of this and what first step breaks this cycle?
The most detrimental consequence of inaction is the compounding of technical debt. Every month of delay further widens the gap, exponentially increasing eventual migration costs.
To break this vicious cycle, the critical first step is a time-boxed proof of value. My recommendation is straightforward: select a single workload, move it, and meticulously measure the results. This tangible outcome then forms the foundation of your internal business case. Ultimately, nothing breaks organisational indecision faster than a visible, proven result.
How can organisations make cloud spend more predictable and defensible?
The problem is not that the cloud is inherently expensive; it is that expenditure remains invisible until the invoice arrives. To counter this, a robust FinOps cadence must be established, built upon three core pillars.
First, tag every resource so that all spend has a clear owner. Second, configure proactive alerts to trigger well before budget thresholds are breached.
Finally, mandate a monthly review that puts both finance and technical teams in the same room. When these two distinct functions begin to speak the same language, cloud expenditure shifts from an unpredictable liability to a consistent, entirely defensible asset.
How critical is investment in DevOps and Developer Services for Azure’s momentum and talent retention, given users’ demand for better developer tools?
It is essential to understand that developer experience dictates platform success, and the data proves it with DevOps emerging as the top Azure deployment choice. This tells us unequivocally that developers are already voting with their feet.
In this industry, if the tooling is clunky, your most capable engineers will simply bypass the platform entirely and build workarounds.
Platform architectures must secure internal adoption or internal developer adoption share first; actual market share is merely a trailing indicator.
Given cost barriers, how does Cloud on Demand’s FinOps service ensure Azure spend is predictable using budgets, alerts and reusable deployment patterns?
We must treat FinOps as an ongoing discipline rather than a one-off audit. By implementing real-time budget guardrails and automated alerts, organisations can eliminate the ‘sticker shock’ that so often plagues cloud deployments.
This focus is particularly important given the findings of the 2025 Cloud on Demand CXO Priorities Survey: Technology Adoption and Strategic Impact report, which found that 25% of organisations cite cost as a barrier to technology adoption. The data reinforces the need for stronger financial governance and greater visibility into cloud expenditure.
Operating in a continuously moving environment requires leveraging real-time data insights to make agile, on-the-go decisions for maximum expediency.
When managed with this level of operational discipline, cloud spending becomes less reactive and more dependable for the finance team at the end of the month, transforming instead into a stable, manageable line item.
How does Cloud on Demand help clients move beyond simply deploying Teams and Power Platform to measuring the business impact of Modern Work through metrics such as time-to-onboard?
Deploying Microsoft Teams is arguably the easy part, but proving it has fundamentally changed how people work is where the real challenge lies.
Through our partner channel, we actively help customers shift away from superficial vanity metrics, such as mere licence assignments. Instead, we focus on quantifiable outcome metrics: accelerated onboarding times, measurable reductions in internal email volume and faster approval turnaround times.
The need for this shift is reflected in the findings of the 2025 Cloud on Demand CXO Priorities Survey: Technology Adoption and Strategic Impact report. The research found that 23% of organisations do not formally assess ROI, while just over one-fifth continue to rely primarily on cost savings or total cost of ownership (TCO) as their measure of success. This highlights a significant opportunity for organisations to adopt more mature, outcome-based approaches to measuring technology value.
When you frame technology adoption in financial terms that a CFO inherently recognises, you build the internal momentum required to integrate deeply into the Microsoft stack, rather than merely achieving only limited adoption.
Companies see Azure as a future AI platform. What data foundations should they put in place today to ensure they are ready for large-scale AI and IoT adoption tomorrow?
Organisations that win the AI race tomorrow are establishing strong data foundations today.
According to the findings, close to a quarter of organisations say IoT and Edge Computing use cases drive their choices for real-time data – reading from machines on the shop floor, sensors in the field and devices at the edge where speed matters most. It is therefore no surprise that Generative AI ranks second, followed by blended technology stacks that use AI to summarise signals, guide decisions and reduce manual effort in fast-moving workflows.
Achieving this readiness requires three crucial pillars. First, data must be consolidated into a governed, central repository. Second, organisations must establish rigorous data classification and lineage, ensuring total visibility over exactly what assets they possess. Lastly, it is vital to ensure that identity and access frameworks are resilient enough to handle IoT-scale operations.
Ultimately, your AI is only as good as the underlying data feeding it, and the reality is that most organisations are still two or three foundational steps away from being genuinely enterprise-ready.
For technology leaders, the message is clear: the organisations that will extract the greatest value from cloud and AI are not those that adopt the most tools, but those that build the operational, financial and data disciplines needed to turn technology into measurable business advantage.
