making-it-work DNA
Shifting into digitalization and AI, both drive transformation and enable new capabilities, while digitalization and AI remain distinct, with unique processes or challenges.
Digitalization + AI
Digitalization covers all forms of converting analog to digital, including basic technologies (cloud, SaaS, etc.), whereas AI specifically focuses on enabling cognitive functions like learning and reasoning that go beyond standard digitalization.
Transition Complexity
Digitalization can start with simple digitization tasks, while AI requires advanced data quality, complex algorithms, and specialized expertise for deployment and organizational change.
Advisory
No cheerleading, no frills – client focus
Decision Making
Digitalization often supports human decision-making by providing tools or access to relevant information, whereas AI can act autonomously, making or guiding decisions independent of direct human input.
Productivity
Both digitalization and AI reduce manual work through automated workflows, from basic task digitization to advanced intelligent automation.
Utilization
Digitalization enables the collection and storage of large data sets, which AI then analyzes to provide actionable insights and support decision-making.
Digitalization & AI.
Unlock value by systematically leveraging advanced technologies to enhance and transform existing business models or by developing entirely new ones.
Digitalization is accelerating at a rapid pace ...
… continuously reshaping how organizations operate and compete. Businesses must frequently reassess their structures, products, services, and investment strategies in response to this strict change and the growing demand for fast adaptation.
AI now serves as the critical engine for digital transformation, it converts „raw“ data into actionable insights, drives automation of complex business processes, and enables hyper-personalization at scale. Organizations leveraging AI can optimize operations, anticipate market shifts, and make better, faster decisions, transforming information into a competitive advantage.
Still practice is ...
… many good ideas fail to deliver impact as the momentum of digital transformation, and especially the power of AI, is not fully connected. When organizations overlook AI-driven automation and advanced analytics, potential improvements often remain unrealized across processes, administration, and products.
As a result, workflows often lack transparency, while reporting and control mechanisms tend to errors and lag behind real-time needs. Without integrated AI to extract actionable insights and automate repetitive tasks, the cost of management information remains unnecessarily high and valuable information resources stay largely underutilized instead of fueling continuous, data-driven optimization.
Digitalization and AI ...
… open up new dimensions for business development, driving innovation through advanced analytic and automation capabilities. Yet, many organizations still struggle with legacy silos and outdated processes that hinder effective implementation. This disconnect often results in incomplete access to essential information, while mounting complexity goes unnoticed and unmanaged.
Without the transparency and predictive power of AI-enabled data integration, standard reporting remains insufficient in highly analytical scenarios—leading to poor decisions and persistent inefficiencies. Frequent reorganizations only compound the challenge when they fail to prioritize seamless integration of data flows. As a result, management information remains expensive and fragmented, and valuable information resources are left idle instead of powering smarter, automated decision-making.