10 Trends Shaping AI in 2025, According to 34,000+ Business Leaders
Michael Lawrence- May 9
- 2 min read
The AI revolution is accelerating, and 2025 is shaping up to be the year that organisations realise value. For leaders aiming to stay ahead, understanding the trends shaping this revolution is essential. Our latest report, A Business Leader's Guide to the AI Revolution, explains the ten key AI trends in 2025, offering a structured framework based on survey responses from 34,173 business leaders.
Here’s a high-level look at what’s driving the AI revolution this year.
The Three Frontiers of AI Trends in 2025:
AI is developing across three critical frontiers – Software, Safety, and Scale – each with unique challenges and opportunities:
Software – The Boundaries of AI Capabilities
AI software is rapidly evolving, moving beyond chatbots and single-function models to more complex, enterprise-ready solutions. Key trends include:
Retrieval-Augmented Generation (RAG) – Enterprises are leveraging RAG architectures to harness internal data while minimising bias and hallucination risks.
Ensemble Models – Organisations are combining multiple models to enhance performance and reliability.
Custom Models – Tailored solutions are gaining traction, offering greater control and specialisation for specific tasks.
Agents – Autonomous agents are becoming central to AI strategies, with references to this technology surging 17x in the past year.
Semantic Layers – Ontology-driven frameworks that reveal hidden insights in complex data sets.
Safety – Managing AI Risks at Scale
As AI systems become more powerful, the risks associated with their deployment grow. Key focus areas include:
Defining Risk – Establishing clear frameworks for understanding and categorising AI risks.
Measuring Risk – Automating the evaluation of AI performance to ensure reliability and compliance.
Addressing Risk – Implementing robust governance and tooling to mitigate emerging AI threats.
Scale – Powering AI Growth Through Data Centers
Scaling AI requires significant investment in physical infrastructure and energy. Key developments include:
Data Centers – Global demand for AI processing power is skyrocketing, requiring rapid expansion of data center capacity.
Energy Demands – The power required for advanced AI is increasing exponentially, driving innovation in energy-efficient systems.
Download the Full Report
For a complete breakdown of these trends, including detailed frameworks and hundreds of statistics on AI adoption, impact and risk, download the full report here.
