In 2025, enterprise AI is moving into a new phase. For the past few years, much of the focus has been on agentic AI—autonomous systems that can perform tasks, follow instructions, and even make decisions independently. From customer support bots to workflow automation tools, AI agents have become essential for driving speed and scale in business processes.
But as AI adoption matures, organisations are realising that autonomy alone isn’t enough. The next era of enterprise AI is about coordination, orchestration, and integration. In short, the focus is shifting from what an AI agent can do individually to how a network of AI systems, data infrastructure, and human expertise can work together. It’s a major leap from agentic intelligence to enterprise-wide intelligence.
From AI Agents to Integrated Intelligence
Agentic AI, tools that can act independently with limited human input, was a significant breakthrough. It gave businesses the ability to automate repetitive tasks, assist with content creation, triage support tickets, and even analyse data in real time. But the limitations are becoming more obvious. AI agents tend to operate in silos, struggle with context transfer, and often require ongoing customised rules or prompts to remain useful over time.
What we’re seeing now is the rise of composable and orchestrated AI, sometimes referred to as Orchestrated Distributed Intelligence (ODI). This involves the deployment of multiple AI systems that interact, share data, and learn from each other. These systems are tightly integrated with an organisation’s existing workflows, CRM platforms, cloud infrastructure, and its people.
For example, instead of a single customer service bot answering emails, a modern AI setup might involve:
- An LLM trained on product manuals generating responses.
- An intent classifier routing requests to the right team.
- A Salesforce integration fetching account histories.
- A human agent reviewing and finalising priority interactions.
Each component has a role. The intelligence isn’t just in the agent, it’s also in the carefully designed architecture.
What This Shift Means for Organisations
1. Human-AI Collaboration Is Now a Strategic Asset
The future of enterprise AI is collaborative. AI systems now work best when they support, augment, and extend the capabilities of human workers. In creative teams, AI drafts first versions. In operations, it flags anomalies. In sales, it helps prioritise leads. This is a shift from replacing tasks to enhancing outcomes.
2. Decision-Making Becomes More Data-Driven and Context-Aware
Unlike standalone agents, integrated AI systems can draw on a broader range of signals: CRM data, customer sentiment, business rules, and historical patterns. That means recommendations are no longer just fast, they’re contextually relevant, traceable, and aligned with business strategy.
3. AI Governance and Infrastructure Are Now Board-Level Concerns
As AI becomes more embedded across departments, questions of data quality, model accountability, and interoperability become mission-critical. Businesses must invest in infrastructure (like secure data lakes and low-latency APIs) and governance frameworks that allow AI systems to operate transparently and ethically.
Why the Shift Matters: Avoiding the Trap of Jagged Intelligence
As discussed in our previous blog on Salesforce’s research into jagged intelligence, AI systems can be impressive in one area and unexpectedly weak in another. The solution to this isn’t building a “perfect agent”, it’s building an ecosystem of specialised, interoperable tools that complement each other’s strengths. This is what forward-thinking organisations are doing now: moving from tool-based thinking to system-level design.
Preparing for What’s Next
Here’s how CloudSmiths recommends organisations prepare for the next wave of AI transformation:
1. Map out where AI can assist, not replace, your teams.
Identify pain points and tasks that could benefit from augmentation, not automation.
2. Invest in integration not just innovation.
A brilliant tool that doesn’t connect to your CRM, support platform, or data warehouse is just another silo.
3. Create internal AI champions.
Encourage leaders in each department to explore AI use cases and share insights with others.
4. Prioritise trust, traceability, and transparency.
Use systems with clear audit trails and governance policies to ensure your AI aligns with your values.
The Role of CloudSmiths
At CloudSmiths, we help organisations move from standalone AI adoption to intelligent, integrated systems. Whether you’re running Salesforce, Google Workspace, or Microsoft Azure, our team works with you to design intelligent AI architectures and implement secure, scalable infrastructure to support it.
We don’t just deploy AI, we help build the systems that make AI trustworthy and valuable at scale.
