Use Artificial Intelligence strategically – your path to the Agentic Company

Efficient, scalable and future-proof: We support companies in using Artificial Intelligence strategically, automating processes and accelerating data-driven decision-making – for greater productivity, competitiveness and sustainable growth.

Artificial Intelligence (AI) is now a key driver of efficiency, productivity and competitiveness. Companies face increasing pressure to digitalize processes, use data more intelligently and make decisions faster and with greater confidence.

According to McKinsey (2025), 88% of companies already use AI in at least one function, a clear sign of its maturity and strategic importance. Industries with high AI adoption also achieve nearly four times the productivity growth – from 7% to 27% within just a few years.

For companies, this means: Those who introduce AI strategically, scale it and integrate it into processes not only increase efficiency – they secure the future viability of their business. AI is not a standalone technology but a strategic way of working: It shapes how companies make decisions, design processes and evolve their organizations. The prerequisite is a clear and structured approach. Instead of getting stuck in pilot projects, companies must translate AI into scalable, business-relevant use cases that create measurable value for the organization.

AI delivers value when it is applied to real business challenges. In particular, companies can benefit from the following opportunities:

Strategic benefits

• Increasing operational efficiency by automating repetitive tasks
• Faster, data-driven decision-making through intelligent analytics and predictive models
• Optimized processes through end-to-end digitalization
• Robust governance through the automated detection of anomalies, risks and compliance issues
• Scalability through the systematic support of growing data volumes and processes

Typical application areas

• Finance: Automated forecasts, risk detection, booking automation
• Human Resources: Skills analysis, onboarding automation, workforce planning
• Production & Supply Chain: Predictive maintenance, quality control, supply chain optimization
• Sales & Service: Lead scoring, next-best-action, automated customer interaction
• IT: Incident categorization, ticket routing, self-service agents

These examples demonstrate: AI not only supports operational activities but actively strengthens value creation.

We do not think about Artificial Intelligence (AI) in silos, but end-to-end across all relevant platforms. As a holistic transformation partner, ORBIS combines the AI ecosystems of Microsoft, SAP, Celonis and Databricks into an integrated architecture. This provides companies with a consistent data and process foundation, enabling AI capabilities to scale across systems and technologies – without dependencies or media discontinuities.

Our expertise covers every layer of modern AI landscapes: from the data foundation and integrated AI capabilities through to autonomous AI agents that execute and automate complete business processes in production environments.

Microsoft provides an integrated platform that makes AI available across the entire workplace.

Copilot supports employees directly in Word, Excel, PowerPoint, Teams, Outlook and Dynamics 365. It creates content, analyzes data, structures meetings and prepares customer conversations – based on existing company data. This enables companies to increase efficiency and quality in their day-to-day work.

With Copilot Studio, autonomous AI agents can be developed to independently manage end-to-end processes. They respond to business data, make decisions and orchestrate workflows – ideal for IT automation, HR processes, customer service and sales.

SAP integrates AI deeply into operational core processes, enabling decision support where it delivers the greatest business impact.

SAP Business AI

AI capabilities are already natively integrated into every modern SAP cloud solution, such as S/4HANA, Customer Experience and SuccessFactors, and can be activated easily. They provide contextual recommendations, automate recurring steps in end-to-end processes and continuously improve data quality.

SAP Joule, SAP’s generative AI assistant, supports users through chat-based analysis, research and real-time decision-making. Joule is complemented by specialized SAP agents that independently execute complex tasks and automate function-specific processes.

A successful AI transformation follows universal principles – regardless of whether companies operate within the Microsoft, SAP, Celonis or Databricks ecosystem. AI delivers its greatest value when data, processes, technology and people are connected to create a holistic transformation journey.

The ORBIS 7-step model translates technological possibilities into a structured approach – from AI strategy and data foundations to scaling AI use cases and establishing responsible AI governance. This enables companies to evolve step by step into an Agentic Company that uses AI as a scalable operating system for value creation.

1. Strategy: Develop a Clear AI Vision

The journey begins with strategic alignment: Together, we define the business value AI should deliver and how AI initiatives can contribute measurably to business objectives.

2. Data Foundation: Build a Stable Data Foundation

A reliable data foundation is a prerequisite for every AI application. This requires the consistent establishment of data governance and data quality, as well as the targeted optimization of data platforms and integration processes.

3. Culture: Empower Employees and Embed AI Competencies

For AI to create value in everyday work, acceptance and know-how are essential. We promote AI literacy, establish training programs and guidelines, and ensure that employees can work with AI confidently and effectively in their daily activities.

4. Technology: Provide a Scalable AI Infrastructure

Depending on your starting point, we establish the technological foundation – from scalable cloud platforms to modern AI and ML environments – ensuring that pilot projects do not stall but can be scaled into productive operations.

5. Execution: From Pilot Projects to a Use Case Factory

We begin with clearly defined pilot projects, measure their business value and transform them into a systematic use case factory that delivers rapid results and continuously generates scalable business value.

6. Governance: Use AI Responsibly and Securely

A clearly defined governance framework ensures that AI is deployed transparently, responsibly and in compliance with applicable regulations – including risk management, compliance requirements and ethical principles.

7. Innovation: Embed AI Permanently into the Value Chain

Through continuous enhancement, regular technology assessments and iterative improvements, AI becomes an integral part of business processes and a driver of new business models, products and efficiency gains.

Companies that introduce AI strategically and scale it consistently strengthen their efficiency, innovative capacity and competitiveness over the long term. The key is a holistic approach that gives equal consideration to data, technology, people and governance. Organizations that embark on this journey early position themselves as pioneers and gain the agility and resilience required for the digital future.

We do not view AI as a one-time project, but as an ongoing transformation. Companies that consistently follow this path evolve step by step from data-driven organizations into true AI leaders.