While AI dominated discussions at the edition of Technology Live! that recently took place in Munich, the real story wasn’t AI itself. Across presentations from Keepit, Scality, Solidigm, and Veeam, a common challenge emerged: how organisations can trust, govern, protect, and recover the rapidly growing volumes of data that increasingly power AI systems and autonomous agents.
For the past few years, the technology industry has focused on the race to deploy artificial intelligence. Organisations have invested heavily in infrastructure, cloud services, foundation models, and automation tools, all in pursuit of greater efficiency and competitive advantage.
Yet, beneath the enthusiasm, a more fundamental conversation is beginning to take shape. As enterprises accelerate AI adoption, they are discovering that success depends less on the models themselves and more on the quality, accessibility, resilience, and governance of the data feeding them. In other words, the challenge is shifting from building AI to building trust in AI. That theme surfaced repeatedly throughout the Munich event, albeit from different perspectives.
Data is becoming more valuable and more active
The starting point is the changing nature of enterprise data itself. Historically, organisations operated around a relatively simple hierarchy. Frequently accessed information sat on high-performance infrastructure, while older data was archived and rarely revisited. AI is changing that dynamic.
The implications are significant. AI systems thrive on context, historical knowledge, and access to large volumes of information. As a result, businesses are being forced to rethink long-established assumptions about what data should be retained, where it should reside, and how quickly it can be accessed.
Data has long since moved from simply something organisations store. It has become an operational asset that directly influences the effectiveness of AI systems.
Resilience is becoming a more critical business requirement
As data continues to grow in value, its protection becomes more critical. Cybersecurity has traditionally focused on preventing attacks. However, organisations are now recognising that breaches, outages, and operational disruptions are inevitable. The real differentiator is the ability to recover more quickly and confidently than before.
Keepit’s channel partner and customer Steffen Pohlenz, CEO of ARC at All4Cloud Group, stated that “digital resilience is not a luxury.”
That statement reflects a broader industry shift. Resilience is no longer viewed solely through the lens of disaster recovery or backup strategy. Instead, it is becoming a core business capability that determines whether organisations can maintain operations, meet regulatory obligations, and preserve customer trust during periods of disruption.
This challenge is particularly acute in cloud-first environments. As businesses distribute workloads across SaaS platforms, public clouds, and hybrid infrastructure, responsibility for data protection becomes steadily more fragmented. Recoverability, visibility, and governance can no longer be assumed.
In an AI-driven organisation, where automated systems may depend on thousands of interconnected data sources, resilience becomes even more important.
Sovereignty and control are rising up the agenda
Another recurring theme was the growing importance of sovereignty. While discussions around data sovereignty have often centred on compliance and regulation, speakers suggested the issue is evolving into something far more strategic.
Christoph Storzum, VP of Sales, Europe, at Scality observed that “there is no single AI workload”, highlighting the complexity organisations now face. Enterprises are simultaneously supporting AI training, inference, retrieval-augmented generation (RAG), analytics, archiving, and edge computing environments, often across multiple jurisdictions and cloud providers and the one size fits all model no longer works.
This complexity raises fundamental questions: who controls the data? Where is it stored? How is it governed? What happens if access is restricted, infrastructure changes, or geopolitical considerations alter the technology landscape? Rather than offering a single solution, the discussions pointed towards a broader shift in thinking. Trust increasingly depends on organisations maintaining visibility, governance, and recoverability across the entire data lifecycle, regardless of where data resides or how AI systems consume it.
Keepit’s Group Chief Information Security Officer, Kim Larsen, argued that global instability is increasing demand for greater data control, local access, migration capability, and data sovereignty. Rather than viewing resilience solely through the lens of disaster recovery, the presentation suggested organisations are increasingly treating control over their data as a strategic capability, particularly as geopolitical uncertainty, cyber threats, and regulatory pressures continue to reshape the technology landscape.
For many organisations, particularly in Europe, these questions are becoming inseparable from broader AI strategies. Trust in AI increasingly depends on trust in the infrastructure, policies, and governance frameworks that underpin it.
The missing layer in the AI stack
A recurring concern raised throughout the day was that organisations have accelerated investment in AI capabilities, yet the frameworks required to establish trust in the underlying data remain comparatively immature.
Veeam Senior Director of Product Strategy Michael Cade summarised this challenge succinctly, arguing that while AI infrastructure investment has accelerated dramatically, “infrastructure to trust in AI hasn’t kept up”. Framing this as the era of “Assume Drift”, he suggested organisations must prepare for AI systems and autonomous agents to evolve continuously, placing greater emphasis on data integrity, governance, and resilience rather than simply infrastructure performance.
Cade’s observation captures a growing tension within the industry. Analysts regularly argue that while investment in AI infrastructure, models, and applications has accelerated rapidly, governance, resilience, and trust frameworks have struggled to keep pace as organisations move from experimentation to enterprise-scale deployment.
The technology stack supporting AI is developing at extraordinary speed. Organisations have access to powerful models, sophisticated orchestration platforms, and unprecedented computing resources. Yet comparatively little attention has been given to establishing the mechanisms required to verify, govern, and recover the data on which those systems depend.
This is creating what many organisations now recognise as a trust gap. Trust requires more than cybersecurity controls; it requires visibility into data lineage, confidence in recoverability, strong governance, effective identity management, and clear accountability. It also requires organisations to understand how information moves between systems, users, and increasingly autonomous agents.
In many respects, trust is emerging as the next layer of enterprise infrastructure – one that sits between the data organisations hold and the AI systems acting upon it. As AI becomes more integrated into business processes, these capabilities will become essential rather than optional.
The next enterprise technology challenge
Lawrence Franklyn, CIO at Solidigm, stated that “AI isn’t a tool you deploy. It’s a change you make”, highlighting that successful AI adoption depends as much on organisational transformation as technology investment.
The most successful organisations over the next decade may not be those with the largest models or the fastest infrastructures. Instead, they are likely to be those that can demonstrate confidence in the integrity, governance, resilience, and recoverability of their data. As AI becomes embedded in critical business decisions, trust in the outcome will increasingly depend on trust in the underlying data.
For years, IT leaders were taught to assume systems would fail. Later, they learned to assume they would be breached. Today, the rise of AI introduces a new reality: organisations must assume continuous change.
In that environment, trust becomes more than a security objective or compliance requirement. It becomes a foundational business capability.
And judging by the conversations in Munich, it may well be the next major battleground in enterprise technology.
About Technology Live!
Established in 2015, Technology Live! is the number one European vendor-independent event where suppliers and IT influencers get together. The largest event of its kind, Technology Live! is a one-day deep-dive where up to four vendors present their technologies to the region’s leading journalists, bloggers, analysts, and other independent influencers. Technology Live! will next take place in London on 12th November.
