2024 enterprise trends: cloud meets AI

The digital transformation opportunity has never been greater, especially with cloud now being generally embraced as an enabler. The generative AI (gen AI) boom has further sharpened the focus on modernisation as enterprises assess how they can take advantage. They want a cloud environment that offers choice, flexibility and independence to more safely experiment with, and adopt, new technologies.

We set out to discover how organisations are approaching their cloud strategy into 2025, their appetite for AI, and the barriers to adoption of emerging innovations. A survey of 609 enterprise IT managers across France, Germany, Italy, Spain, the UAE and the UK showed that almost all respondents (99%) are investing in cloud as organisational priority, with preparations for AI adoption being a key driver. Yet numerous challenges persist including cloud sprawl, skills gaps, and compliance and data sovereignty.

Drivers of Cloud Strategy

The rapid evolution of enterprise technology is reshaping cloud strategies. According to our survey, the top drivers for cloud growth over the next 18 months include centralising cloud management (80%), security, compliance and sovereignty regulatory requirements (78%), and preparing for AI adoption (78%).

In parallel, organisations are prioritising innovation within their cloud programmes. Half of the respondents (50%) are planning for balanced growth, investing equally in new technologies like AI and optimising existing systems, while 26% will focus more heavily on innovation. Taking these two groups as a subset of respondents, 52% are planning on increasing investment in cloud technology by 21-50% by 2025.

Barriers to Cloud and AI Adoption

The survey also showed that the adoption of modern technologies is hindered by ongoing skills shortages. AI is the top reported skills gap, according to 71% of respondents. Respondents also flagged gaps in cybersecurity skills (66%) and cloud computing skills (61%). These shortages underscore the need for ongoing investment in workforce development and smart partnering beyond the organisation’s walls. 

Siloed teams continue to be a challenge for 96% of enterprises, impacting everything from security to cost management. More than half (52%) of organisations report encountering this challenge always or frequently. Of those impacted by silos, 54% reported inconsistent security and compliance across different cloud providers, while 47% noted increased costs as a result. Misalignment between teams not only hampers efficiency but also limits visibility and control over cloud resources (41%), further complicating cloud and AI adoption efforts.

Separately, the survey asked for the main obstacles preventing CTOs or equivalent decision makers from advancing generative AI initiatives. The top themes to emerge were concerns about data privacy and security (43%), energy consumption / sustainability concerns (39%), insufficient infrastructure or resources (32%) and lack of transparency in AI models (31%).

The Role of Enterprise Open Source

When looking at what factors determine trust in an enterprise model for gen AI, transparent, modifiable models with explainability of sources (89%) came top in our survey. Open source helps provide this transparency, and many organisations are finding ways to accelerate their AI and cloud ambitions through enterprise open source solutions. 45% of respondents identified accelerated innovation as a primary advantage of adopting enterprise open source for AI, with another 43% naming trust and transparency, and 39% citing cost efficiency.

Open source also complements upskilling efforts by enabling organisations to tap into a global community of contributors, getting access to the latest tools, frameworks and a support network that reduces the dependency on highly specialised talent. Tools like InstructLab can help bridge the AI skills gap by enabling people with business skills, not just data scientists, to contribute to AI models that have the potential to form the future of enterprise IT. 

Ready for the Future: Keeping your Options Open

As organisations look ahead, they need to build for hybrid flexibility while mitigating cloud complexity. They need to reduce environmental sprawl and connect clouds so that they can move workloads - notably AI - between edge, on-premise and multiple clouds to follow their data, with consistent performance and security features. The integration of AI with hybrid cloud demands an open and collaborative ecosystem where organisations work together, sharing best practices, data assets and training resources. With the ability to accelerate innovation, reduce costs, and promote trust and transparency, enterprise open source platforms offer an answer for businesses looking to harness the full potential of AI within their cloud environments. The path to AI and cloud success may be complex, but with the right foundations, leadership alignment, and willingness to adapt, the rewards are within reach.

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You can check out the survey data highlights for each country at the following links:

• France
• Germany
• Italy
• Spain
• UAE
• UK