Why your next competitive advantage won’t come from AI, but from how your teams work with it

Every company is buying AI, but very few are building collective intelligence. Billions are being spent on automation, models, and data infrastructure. Yet most organisations remain stuck in the same loops of inefficiency. Projects stall. Silos deepen. The gap between what technology can do and what people achieve keeps growing. The problem isn’t the algorithm. It’s how humans and intelligent systems work together.

Technology is not the competitive advantage. Collaboration is. 

The illusion of intelligence

Over the past few years, enterprises have rushed to embed AI into every corner of their operations. Marketing, finance, procurement, and HR are now powered by smart systems that predict, recommend, and optimise. But in many cases, the productivity gains have plateaued.

A 2024 MIT Sloan study found that nearly 70% of AI deployments fail to deliver measurable ROI. The issue is rarely technical. It is organisational. AI can process information faster than any human, but it cannot resolve conflicting priorities, interpret context, or persuade teams to act differently.

When humans and machines operate in parallel rather than in partnership, intelligence becomes fragmented. Insights are generated but not shared. Automation replaces steps but not judgment. The outcome is often more noise, not more clarity.

The shift from artificial to collaborative

True transformation happens when organisations stop seeing AI as an external tool and start treating it as a co-worker. That requires a shift from AI to collaborative intelligence—a model in which AI agents are not fully autonomous; instead, they act as trained assistants.

In this model, AI doesn’t dictate. It augments. It handles data-heavy, repetitive tasks while humans focus on strategy, empathy, and creativity. The human defines intent; the AI ensures execution.

A global survey by PwC found that firms integrating human expertise and AI systems in shared decision environments achieved up to 50% higher operational efficiency than those that automated tasks in isolation. Collaboration, not automation, drives the return on intelligence.

Culture before code

The next leap in productivity is cultural, not technical. Building collaborative intelligence requires organisations to rethink how teams collaborate and make decisions.

In most companies, decisions still follow hierarchical patterns. Managers approve. Analysts interpret. Systems execute. Collaborative intelligence flips this model. It distributes intelligence across the enterprise, enabling context-aware agents to assist humans in real time while feeding insights back into a shared knowledge layer.

This doesn’t just speed up processes. It changes how organisations learn. When every interaction between humans and AI contributes to collective understanding, enterprises start to develop what can be called organisational memory: a living system of shared intelligence that evolves continuously.

However, this shift requires more than new software. It demands new trust structures. People need to understand when to rely on AI, when to challenge it, and how to use its output to make better calls. Without that, even the most advanced technology becomes another silo.

The anatomy of collaborative intelligence

Building a system where humans and AI think together involves three key layers:

1. Shared data fabric: Breaking data silos so insights flow seamlessly across teams. Collaborative intelligence depends on context. A contract manager’s decision affects finance, compliance, and operations. When systems talk to each other, decisions align faster.

2. Human-in-the-loop design: Ensuring that humans remain embedded in every feedback loop. Intelligent agents may recommend, but humans review and refine. This balance ensures speed with accountability.

3. Trust and traceability: Every automated decision must be explainable. Transparency builds confidence and ensures compliance with privacy and regulatory frameworks like GDPR and India’s DPDP Act.

When these three layers operate together, organisations move from automation to orchestration. Workflows evolve into “thinking flows,” where insights, approvals, and execution happen collaboratively across people and machines.

From adoption to advantage

Companies that treat AI as a procurement line item rarely change how they work. Those who treat it as a collaborative capability transform their business model.

For instance, a leading financial services firm in Asia integrated collaborative intelligence into its contract and risk management systems. What once took days of manual review now takes hours, not because of automation alone, but because legal, compliance, and technology teams now work in a single intelligent workspace. The system surfaces risks, humans validate, and decisions are made collectively.

The result was a 60% reduction in approval time and a measurable increase in cross-functional trust. The firm didn’t just automate paperwork. It rewired how people worked together.

The future belongs to augmented organisations

As enterprises race toward AI maturity, the ones that will lead are not those with the most sophisticated models, but those that can turn intelligence into alignment. The future organisation will not be a collection of departments but a network of connected decisions, powered by shared intelligence.

Collaborative intelligence represents this next stage. It is not about replacing people with smarter systems. It is about amplifying human judgment through shared context and transparent automation. It is the difference between working with technology and working around it.

The advantage will belong to organisations that build cultures where intelligent agents and humans co-create outcomes, learn from each other, and trust the system as much as they trust themselves.

Because in the end, intelligence that isn’t shared is wasted. And in a world where everyone has access to AI, the only real differentiator is how you use it together.

The author is the founder and CEO of Melento (formerly SignDesk). Views are personal.