Real-time collaboration between people and AI is emerging as a critical driver of faster, higher-quality business innovation.
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By any reasonable measure, artificial intelligence has crossed the threshold from experimental to essential. Yet the organizations seeing outsized returns from AI are not those treating it as a standalone technology initiative. They are the ones embedding AI into how people work together — continuously, transparently and in real time.
AI and collaboration are both incredible innovation resources on their own. When focused on value creation, AI can streamline prototyping, idea generation and many other key activities to enable faster and more efficient results. AI can not only replace tasks, but it can also catalyze the collective intelligence of teams in the moments that matter most.
And collaboration has long been key for every business, giving partners access to resources and knowledge that they might not have access to internally. Leveraging AI for real-time collaboration has become one of the most effective ways to innovate.
AI Is A Team Sport
Early enterprise AI efforts often failed for a simple reason: they were siloed. Data science teams built models disconnected from business users. IT deployed tools without understanding workflows. Executives expected transformation without changing how decisions were made.
AI can provide a powerful boost to existing human collaboration. Research by the Harvard Business School found that teams that used AI were three times as likely to produce innovative ideas ranking in the top 10% as individuals not using AI. AI-powered teams also produced significantly higher-quality ideas than non-AI-using teams. The teams not only saved time, but they were also able to develop ideas that successfully mixed technical and commercial elements.
Consider companies like Microsoft. The success of GitHub Copilot and Microsoft 365 Copilot is not just about model performance. It is about embedding AI directly into collaborative environments — code repositories, documents, meetings and chats — where work already happens. Developers pair with Copilot in real time. Knowledge workers brainstorm with AI inside Teams meetings. The innovation emerges from interaction, not automation alone.
Similarly, at Shopify, CEO Tobi Lütke has pushed AI adoption by encouraging teams to treat AI as a default collaborator. Teams are expected to explain why AI can not be used, rather than why it should be. That mindset shifts AI from a specialized capability to a shared productivity multiplier.
Driving Better Results With AI As A Collaborator
The Harvard Business School report found that individuals who collaborated with AI also saw major gains in time savings and quality. With AI as a real-time collaborator, individuals and businesses can get instant insights that help them pursue key goals that drive innovation.
For example, in a case study by GovSignals, federal government contractor Savvee was able to triple its proposal submission rate while saving over three hours on front-end prep and analysis for each proposal — all thanks to the use of AI agents that helped it surface more relevant contract opportunities and streamline the evaluation process.
Similarly, writing for the American Management Association of AI’s impact in the financial space, serial entrepreneur Joshua Summers notes, “Self-improving AI is pushing financial decision making to new heights, not by replacing risk analysts but by enhancing their speed, accuracy, and strategic insight. The ability to dynamically refine prompts, automate workflows, self-correct errors, and proactively surface risks marks a new era of lending intelligence.”
AI is a powerful collaborator that can level the playing field, especially for smaller businesses, giving them access to resources and information that might otherwise remain inaccessible. With AI as your real-time collaborative partner, you can leverage meaningful insights from data that help you scale your business and unlock new opportunities.
Collaborating To Build Better AI
Collaboration can also aid in the adoption and implementation of AI. The process of developing an in-house AI system can be difficult for companies without the right team or tech resources. But once again, collaboration can lead to the development of smarter, more efficient AI.
Consider this example from IBM: “A manufacturing company looking to optimize its supply chain might collaborate with a research institution focused on AI-driven logistics. By pooling resources and data, both parties can create a machine-learning model that predicts demand fluctuations more accurately. This type of collaboration accelerates the development process, allowing the manufacturer to implement AI solutions faster than it could alone.”
When partners work together with a focus on AI, they can develop more innovative and better tailored AI solutions, which in turn will help them unlock more innovations further down the line.
Action Steps To Capture Benefits
To win in this era, you cannot wait for a perfect system. Start building the muscle of collaborative innovation today.
For Individuals:
- Adopt an “Editor-in-Chief” Mindset: Stop trying to be the primary creator for everything. Practice using AI to generate the 60% baseline of your work so you can spend your real-time hours on the 40% that requires deep human empathy and strategic nuance.
- Master the Prompt, Master the Pivot: Learn to iterate with AI in live sessions. The skill of the future is real-time prompting, including excelling at steering an AI’s output during a live brainstorm.
For Teams:
- Implement AI-First Meetings: Use tools like Zoom AI Companion or Glean to automate summaries and action items. Free up your team members to actually look at each other and debate ideas instead of frantically taking notes.
- Audit Your Coordination Tax: Identify the recurring meetings that only exist to “update” people. Replace them with AI-powered dashboards that provide real-time status, and use that reclaimed time for a “Creative Jam.”
For Organizations:
- Modernize the Foundation: You cannot have real-time AI collaboration on legacy silos. Invest in a unified data layer where your CRM, project management and communication tools talk to the same AI models.
- Establish Ethical Guardrails Early: Transparency is critically important. Clearly define what data the AI sees and how it will be used. People will collaborate with AI when they know it is there to help them succeed rather than to spy on them.
The Bottom Line
Business innovation with AI is not simply about replacing people. It can be about connecting them faster, smarter and with greater shared understanding. Whether you’re using AI to support team-based collaboration, collaborating with AI on your own or working with a partner to enhance the power of your AI tools, these collaborations can deliver the rapid insights and innovations that will help you achieve your most important goals.
Real-time collaboration is the multiplier that turns AI from a promising technology into a strategic advantage. Those who invest now in skills, culture and collaborative infrastructure will both keep up with change and help define what comes next.
