In the last year, we’ve seen the explosion of AI in the enterprise, leaving organizations to consider the infrastructure and processes for AI to successfully—and securely—deploy across an organization. As we head into 2025, it’s clear that next year will be just as exciting as past years.
Here, Cloudera experts share their insights on what to expect in data and AI for the enterprise in 2025.
Bridging the Gap Between Business and IT
Bridging the gap between business and IT teams is not a new mission for enterprises. However, the onus has historically fallen on business leaders to adopt more technical skills and proficiency. Cloudera CEO Charles Sansbury predicts a reverse trend in 2025 and sees data scientists and IT teams stepping into a more business-conscious role to bridge this gap:
“Business leaders becoming more ‘savvy’ via the proliferation of user-friendly AI tools like assistants and copilots have made it possible for business professionals to leverage analytics to inform better decision-making. This trend is ongoing, and I expect it will continue into 2025. However, I also expect a new, reverse trend to take shape: IT teams and data scientists will start to glean even greater business acumen to plug into the broader needs of the enterprise.
For too long, IT and business teams have been siloed, with business users making requests of the IT team without understanding the scope of the technology needed, and IT teams requesting producing insights without knowing what business problem they’re being used to solve. In 2025, we will see that gap start to close with the most advanced enterprises arming themselves with an entire staff — from the marketing and finance departments to the IT and data scientists, all the way to the C-Suite — leveraging data, analytics, and AI to accelerate growth.”
The Shift to Private LLMs and the Ripple Effects
AI is only as powerful as the data behind it. As such, Remus Lim, Senior Vice President of APAC and Japan at Cloudera, believes enterprises will grow to favor private LLMs to spur their own AI innovation:
“With enterprise AI innovation taking center stage in the year ahead, businesses will eschew public large language models (LLMs) in favor of enterprise-grade or private LLMs that can deliver accurate insights informed by the organizational context.
“As more businesses deploy enterprise-grade LLMs, they will require the support of GPUs for faster performance over traditional CPUs, and robust data governance systems with improved security and privacy. In the same vein, businesses will also ramp up their use of retrieval-augmented generation (RAG) in a bid to transform generic LLMs into industry-specific or organization-specific data repositories that are more accurate and reliable for end users working in field support, HR, or supply chain.”
Hybrid Cloud Alone Will Be Insufficient for GenAI
2024 was the pilot year of GenAI, and 2025 will see businesses seeking to advance to full production and scale with GenAI deployments. As such, Lim believes hybrid cloud isn’t enough:
“With the growth in hybrid environments, companies’ data footprints span on-premises, mainframes, public cloud, at the edge. Businesses need the capability to bring GenAI models to wherever the data resides, and seamlessly move data and workloads across the business, to derive valuable insights and address organizational needs. With so much data being fed into AI model services, security and governance will also come to the fore.
As businesses turn to running AI models and applications privately, whether on premises or in public clouds, there will be a greater emphasis on hybrid data management platforms that integrate both on-premises and cloud data sources for greater flexibility and wider access to diverse datasets while maintaining control, security, and governance over model endpoints and operations.”
Agentic AI’s Big Step Forward
The training wheels are coming off with AI. Enterprises witnessed improved productivity and efficiency with AI-based solutions. But IT experts agree the technology has great potential for more, and Chris Royles, Field CTO of EMEA at Cloudera, foresees that coming to life through agentic AI in 2025:
“Currently, AI still falls short of replicating human-level decision-making, but next year that is set to change with Agentic AI.
Agentic AI is set to drive a wave of innovation, transforming real-time problem-solving and decision-making. Expect these AI agents to optimize tasks with ant-like efficiency, navigating challenges quickly and adapting in real time. This will see businesses building event-driven architectures that allow AI to react instantly to real-life events, revolutionizing industries like telecom and logistics.”
Research Will Fuel the Development of Legislation for AI Guardrails
Safeguarding for responsible, ethical AI use was a bubbling issue in 2024 as the technology advanced at a rapid pace. This will remain a priority, and Manasi Vartak, Chief AI Architect at Cloudera, foresees a larger focus on academic research for more informed GenAI policy in the coming year:
“While AI regulation is certainly necessary, it must be based on a deep understanding of how GenAI models and applications function. I also expect there to be an increase in funding for academic research into GenAI, including think tanks and labs to address what AI safety means and how it can be implemented, which will likely come from an increase in government partnerships with academic institutions.
Academic research plays a critical role in understanding AI and the necessary protocols, and government partnerships with academic institutions are essential to generate the knowledge and influence needed to establish effective safeguards and guide responsible regulation.”
Move Aside AI: Here Comes the Quantum Computing Revolution
The enterprise’s focus of late has been steadfastly on AI. Royles believes quantum computing will become the next “tech arms race” in 2025:
“Quantum computing is set to overshadow AI as the next major technological revolution. Rapid development is underway, with organizations investing heavily in next-generation data centers equipped to provide ultra-cold temperatures, specialized infrastructure, and massive power requirements needed to support quantum systems.
The potential value of quantum breakthroughs is immeasurable, from accelerating drug discovery and genetic reprogramming in healthcare to pushing energy closer to fusion, potentially rendering traditional power sources obsolete. As quantum emerges as a game-changer, this shift will trigger a race as companies rush to harness quantum’s capabilities, using it to enhance AI capabilities and gain a competitive edge.”
2025 is sure to be filled with exciting changes and developments. To dive deeper into these and other predictions, join us during our webinar on January 21.
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