While Microsoft recently made headlines with the announcement of GPT-5 in Copilot and its direct rollout, many organizations are still at the very beginning of their AI journey. Over the past two years, our Head of Modern Work Switzerland and Microsoft MVP for M365 Copilot & Copilot Extensibility, Pascal Bunner-Nikolla, has had the opportunity to guide numerous organizations through this transformation. One insight emerged time and again: everyone knows they need to take action, yet few have transitioned from awareness to concrete, strategic action. In this article, he shares his key observations and lessons learned.
Gerade zu Beginn kreisten viele Diskussionen bei der Einführung von KI stark um den Return on Investment (ROI). Das ist auf der einen Seite nachvollziehbar, schließlich müssen Entscheidungsträger:innen abwägen, wofür Budgets eingesetzt werden. Andererseits halte ich diese Sichtweise für wenig zielführend. Vor allem dort, wo KI alltagstauglich wird und unmittelbar auf die persönliche Produktivität einzahlt, greift die ROI-Logik zu kurz.
And this is where the true value lies: more can be achieved in the same amount of time. That’s why we talk about Business Value. In our Business Value Assessments (BVA), we make this value transparent – showing how it translates into measurable process improvements such as faster cycle times, fewer errors, higher customer satisfaction, or increased revenue per customer.
The Limits of Monetary ROI Thinking
At the beginning, discussions about AI adoption often revolved heavily around Return on Investment (ROI). On one hand, that’s understandable – decision-makers must justify how budgets are spent. On the other hand, I find this perspective not particularly helpful. Especially in areas where AI becomes part of everyday work and directly impacts personal productivity, ROI logic falls short.
Personal productivity is notoriously difficult to measure. In most organizations, there are no reliable benchmarks showing how much time specific tasks currently take. And even if such data exists, the immediate benefit rarely shows up right away. Time savings are often subjective and, while they can be converted into dollars or Swiss francs, they don’t translate into real cost reductions. Even when tasks are completed faster, the costs don’t disappear from the organization. Instead, the time gained is used for other, more valuable activities.
And this is where the true value lies: more can be achieved in the same amount of time. That’s why we talk about Business Value. In our Business Value Assessments (BVA), we make this value transparent – showing how it translates into measurable process improvements such as faster cycle times, fewer errors, higher customer satisfaction, or increased revenue per customer.
Everyday AI as the Starting Point
This is where “Everyday AI” comes into play. It makes the impact of AI tangible in daily work. Even though it can’t be expressed in traditional ROI metrics, it demonstrably makes people more productive, creative, and informed. From here, organizations can take the next decisive step up the AI maturity pyramid: moving from personal productivity to process optimization.
Von Everyday zu Leading AI. Der Weg zur markführenden Position beginnt mit dem Erlenen des Umgangs mit AI.
From my experience, certain processes can be directly “AI-infused” to achieve tangible results. At the same time, human involvement – the human-in-the-loop – is essential to identify opportunities and ensure sustainable value creation. That’s why establishing a robust Everyday AI setup is crucial. It relies on three key aspects:
- AI Ready Organization
An organization with clearly defined decision-making paths and responsibilities that embeds AI strategically. A Center of Excellence or similar structure ensures that experiences are shared and leveraged across the company. - AI Ready Tools
Technical readiness goes far beyond purchasing Copilot licenses. Security standards such as labeling and document classification must be implemented. The issue of oversharing – unconscious or overly generous information sharing – remains a major challenge. The good news: Copilot raises awareness and helps organizations systematically improve their maturity. - AI Ready People
People are the decisive success factor. Transformation starts with mindset. It’s not about training every function separately, but about enabling employees to ask themselves with every task: “How can Copilot support me here?”
The Goal: Real Business Value with AI
When evaluating the impact of AI, what truly matters are output and added value. This shift makes one thing clear: AI is no longer an experiment, it has become the new normal, just as Google once replaced the library. Copilot and AI should therefore not be seen as cost-saving projects but as strategic investments in organizational resilience and future readiness. Organizations that act now gain a head start over those still hesitating and remain competitive against those already evolving into AI-driven companies.
Enriching Business Processes with AI
On the path to becoming a leading AI organization, where innovation happens, the next step is to move from personal productivity to the systematic integration of AI into business processes. A multi-agent approach is becoming increasingly important: specialized agents autonomously handle defined subprocesses or tasks, are safeguarded through human-in-the-loop validation, and orchestrated by process owners. This creates a bridge between process optimization and a central AI platform.
What’s key is a platform that not only delivers isolated support but connects different AI use cases meaningfully.
That’s exactly what Microsoft Copilot provides. It’s not just another tool, it’s an AI platform. Combined with Copilot Studio Full Experience and Azure AI Foundry, all AI capabilities are available in one environment. This turns Copilot into the “User Interface for AI.” Just as Microsoft Teams once became the central hub for collaboration, M365 Copilot is now emerging as the control center for enterprise AI.
Not every use case can be implemented with Copilot alone. Still, it becomes the one-stop shop for employees. Through agents, Copilot integrates not only AI capabilities but also third-party systems such as SAP, ServiceNow, or Atlassian products, as well as custom models – from simple information queries to fully automated vacation requests.
This marks a shift from classic SaaS models toward an agentic AI approach. This transformation begins with Everyday AI, requires active human engagement, and rests on a solid technical foundation.
At Campana & Schott, we support our clients with insights from over 400 Copilot projects, helping them design this journey holistically and sustainably.
Would you like to start your Copilot journey or take your organization’s AI adoption to the next level? Get in touch with me for an initial conversation.
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