EXECUTIVE SUMMARY:
- The generative AI surge has seen data centre commissioning shift its operating processes dramatically, with significant design and construction changes
- Three core challenges incurred from rapid genAI development – power, materials, and talent – are compounded by a lack of young talent in data centre commissioning
- Regulatory initiatives in tackling this challenge, from the UK government to the EU’s AI Continent Plan, may be threatened by power limitations and restrictive planning and approval processes
- Current pipelines to produce the next generation of data centre commissioning professionals are not producing the numbers of new hires the industry needs
A technological revolution is unfolding before our eyes, with Generative Artificial Intelligence (GenAI) redefining industries across the board; from software development and call centre productivity to copywriting. By boosting efficiency, GenAI is, according to some analysts, on track to raise the GDP of industrialised nations by 10–15% over the next decade. It truly resembles a digital gold rush.
AI is already having an immediate and widespread impact throughout the global economy. In the coming years, value will consolidate among companies that successfully innovate and respond to technological demands, while those that fail to adapt risk being disrupted.
The “arms race†to develop the next generation of AI tools is accelerating. Google’s new Veo 3 video generation tool, launched in early June, is already making headlines for allowing everyday users to create ultra-realistic videos; from kittens playing to depictions of election fraud and riots, for just $249 per month. It is a milestone moment, both for industrialised nations and for governments aiming to stimulate economic growth. However, GenAI alone is not inherently valuable. Its true power lies in applying models to data to innovate, analyse, and predict; the digital equivalent of refining crude oil into fuel.
Turbocharging Data Centre Demand
All of this computational power depends on data centres, which have become central to scaling GenAI’s productivity. The relentless race among developers to build, train, and operate ever more advanced models is pushing the limits of today’s digital infrastructure.
Goldman Sachs predicts that global power demand from data centres will rise by 50% by 2027 and by as much as 165% by 2030, largely due to GenAI adoption.
Professionals in the commissioning sector describe the surge as unlike anything seen before; bigger than the boldest pre-2023 forecasts. The scale of investment, the rapid expansion of infrastructure, and the explosive pace of demand have all exceeded expectations. By the end of 2025, nearly half of all data centre power consumption worldwide could be dedicated to AI systems. This has turned commissioning into a bottleneck that will either secure or derail AI deployment schedules.
Power, Materials, and Talent: the Pinch Points Holding back the AI Data Centre Boom
The commissioning space for data centres has shifted its current operating processes dramatically. Significant design and construction changes have gone underway, not only in how buildings are constructed but also in the very technology used within them, reshaping the ways data centres are commissioned.
There are three core challenges incurred from rapid GenAI development; those being power, materials, and talent.
GenAI has immense power demands, magnitudes greater than that of cloud computing workloads or traditional colocation. This requirement raises serious power availability concerns across Europe, and especially the UK. Developing data centres of this scale to capitalise on the GenAI boom is not feasible since there is just not enough power to sustain it.
The government is tackling this challenge head-on given its serious benefit to the nation’s GDP. For instance, the UK government has responded by creating “AI Growth Zones†to raise investments specifically for AI, enabling data centres by improving power access and providing planning support in some areas of the country. The European Union’s AI Continent Plan also includes plans to build large-scale AI data and computing infrastructures, including at least 13 operational “AI factories†by 2026 and up to five “gigafactories†at some point after that.
However, power limitations and restrictive planning and approval processes pose a threat to mitigating these efforts. Already, there are existing data centre markets facing pushback from local councils and communities against new infrastructure due to their effects on power grids and local water supplies.
Economic hubs such as Dublin and Amsterdam have already hindered development on new builds even before the AI frenzy push. This causes further risks down the line, as AI engines can be built anywhere. However, private data laws such as GDPR mean that data must be housed in-country. If Europe and the UK don’t move at pace with demand, large US AI firms with more resources will commit to building massive centres stateside and deploy this tech across the Atlantic later, setting back British economic stimulation.
Due to early-stage AI model development, significant processing power is required to train effectively. Once the model is fully trained, however, it can run on less demanding infrastructure. Yet the risk remains: if we continue to stifle the AI industry in Europe and the UK, and do not build faster and make more power available, we will lose out on much more than we can hope to gain.
Another huge restriction is the access to raw materials and components. Global supply chain challenges have spiked the cost of construction materials, and lead times for data-centre-specific components such as cooling equipment can take up to six months, further complicating the process of building new infrastructure.
An even greater problem, on top of the issues stated prior, is the talent needed to push the industry forward. Commissioning is essential for data centre design, construction, and approvals processes, and the sector is facing a generational talent crisis.
With not enough young talent coming into the sector, it needs the industry to change its approach across the board; not just in commissioning but also for project managers, consultants, everyone, everywhere.
Commissioning seems to have these issues all wrapped together, however, due to the sector’s niche pipeline and stringent requirements, it is hard to recruit to become an immediate commissioning engineer. The field requires a solid background in either electrical or mechanical engineering or through a trade. Right now, the current pipelines to produce the next generation of data centre commissioning professionals just aren’t producing the numbers of new hires the industry needs.
This is affecting all data centre commissioning, not just AI. Yet the scale of demand and speed at which the industry is moving means these risks will become a serious issue in the not-too-distant future. The demand for power is rapidly growing, and the race to build effective and reliable infrastructure has started. But it’s the AI push that’s necessary in ensuring both are met for the future of the digital ecosystem.
What’s next?
Looking at the next few years, there’s no blueprint to say exactly where we’re headed, but it’s clear that if Europe and the UK cannot secure access to reliable, affordable energy, as well as clear the way for data centre approvals to move quickly, issues such as the industry talent shortage and rising materials costs (not to mention lead times) threaten to leave the region behind in the race; missing out on untold societal benefits.
