Generative AI has rapidly moved from experimentation to the core of enterprise operations. Many organisations are now investing in large‑language‑model capabilities and agentic systems. Below are five trends that will define how businesses deploy generative AI over the coming year—and what each means for your company's roadmap.

1. Wide‑Scale Adoption Across the Enterprise

After two years of pilots and proofs of concept, generative AI is graduating to production. Enterprises are starting to embed generative models into mission‑critical applications, from customer support to knowledge management. For technology leaders, this shift means revisiting the entire stack—from development frameworks to data infrastructure—and revising talent strategies to ensure employees can work alongside AI effectively. It also signals that generative AI is no longer a niche experiment: in 2025 it will be integral to business operations.

2. The Rise of Agentic AI

The next evolution of generative AI is agentic AI: autonomous systems capable of reasoning and executing multi‑step tasks without constant human prompts. Enterprises will move beyond simple prompt engineering and retrieval‑augmented generation towards deploying independent agents that orchestrate processes such as document creation, data summarisation and even video generation. To capitalise on this trend, organisations must identify high‑impact use cases, design a multi‑cloud and multi‑LLM platform, and build strong governance for deploying agents. Business leaders should prepare for a future where software agents collaborate with employees, augmenting—not replacing—the workforce.

3. Governance and Responsible AI

As adoption grows, so does scrutiny. Regulators are catching up with the risks of generative AI, and enterprises operating in regulated industries must prioritise governance. This includes establishing clear policies for responsible AI, implementing monitoring to detect bias and drift, and ensuring explainability for AI‑generated decisions. Responsible AI is not optional; companies that proactively implement ethical guidelines and privacy safeguards will build customer trust and reduce compliance risks.

4. Generative AI for IT and Engineering

Generative AI isn't just for marketing content—it is transforming how IT and engineering teams work. By training models on internal codebases and databases, organisations can automate code generation, assist with SQL queries, streamline CI/CD pipelines and optimise infrastructure management. Early adopters report productivity gains of 10–25 percent. For CIOs, this trend means investing in toolchains that integrate generative models into development workflows and upskilling engineers to pair with AI effectively.

5. Enterprise Search and Knowledge Management

Knowledge workers spend a significant portion of their day searching for information. Generative AI offers a solution: systems that retrieve, synthesise and summarise information from internal documents through conversational interfaces. Over the next year, expect to see AI‑powered search and knowledge management platforms become widely available, making it easier for employees to access institutional knowledge and generate new insights. This shift will have profound implications for corporate culture and training as companies adapt to more intuitive ways of working.

What These Trends Mean for Your Business

Invest strategically: Generative AI is moving into production. Allocate budget for scaling infrastructure and retraining staff, not just for purchasing models.

Design with governance in mind: Incorporate responsible AI principles from day one to avoid regulatory and reputational pitfalls.

Embrace human‑AI collaboration: Focus on augmenting human expertise with AI rather than replacing it. Upskill teams to work alongside autonomous agents.

Prioritise use cases: Identify business processes with the greatest potential ROI, such as customer support, software development or knowledge management.