AI-Enabled Business Transformation

AI-based models become part of your everyday work – as sparring partner, analysis tool and assistant. You combine classic process, change and leadership thinking with data-based methods and gain time for what really matters.

• Understand the role and impact of AI in process optimization, change leadership and day-to-day leadership
• Use AI as a sparring partner, analysis tool and assistant
• Combine experience, process knowledge and intuition with data
• Redesign decision architectures for complex change questions
• Make your own working routines more efficient with AI tools
• Delegate tasks sensibly to AI – and stay present where presence is irreplaceable
• Consistently avoid misreading process and performance data
• Win back time for strategic change work

Data-based methods change how you handle process information, weigh options and take decisions. The quality, speed and consistency of your decisions improve measurably – without any loss of care.

• Integrate data-based systems into change and decision-making processes
• Use Predictive Analytics and scenarios to spot developments earlier
• Use simulations for capacity, throughput-time and risk decisions
• Separate relevant metrics from irrelevant – focus on what matters
• Prioritize change initiatives by effort, impact and risk
• Increase speed and accuracy in decision-making rounds
• Delegate to AI-based analysis tools sensibly and keep control
• Safeguard decision quality through structured reflection

Optimization starts with solid facts instead of assumptions. You make workflows visible end-to-end, identify bottlenecks – and assess what every change triggers in roles, costs and interfaces.

• Structure the process landscape and make it visible end to end
• Use Process Mining and process data for robust analyses
• Identify bottlenecks, system breaks, duplicated work and waste
• Improve lead times, error rates and process costs systematically
• Assess automation and AI potential realistically
• Make impact chains visible: from the process change to the business result
• Avoid local optimization at the expense of the wider system
• Evidence impact with suitable KPIs and before-and-after measurement

You combine strategic thinking with AI-supported methods. The focus: how AI supports future scenarios, investment decisions and business models – and where leadership remains irreplaceable.

• Develop future scenarios for strategies, structures and processes with AI
• Assess and validate strategic options on a data basis
• Underpin investment decisions with analyses and simulations
• Steer markets, customers, innovations and business models deliberately
• Identify productivity and efficiency potential automatically
• Build early-warning systems and strategic dashboards
• Understand digital platforms and AI ecosystems as growth levers
• Measure the impact of strategic AI initiatives with suitable KPIs

Change does not succeed by decree, but through participation, clarity and consistency. You set up change initiatives in such a way that they land in the organization and last.

• Give clear reasons for the need to change and develop a convincing target picture
• Set up change architecture, roles and responsibilities cleanly
• Turn those affected into participants and work through resistance constructively
• Balance pace, sequence and the resilience of the organization realistically
• Enable managers to act as multipliers in change
• Understand and shape culture as a success factor for transformation
• Establish cross-functional teams and hybrid decision models
• Shape Change Management successfully in an AI context

Effective change depends on clear communication. The module covers stakeholder communication, dialogue with those affected, crisis communication and alignment between executive management, the project and the line organization.

• Sharpen messages for different stakeholders and affected groups
• Use AI to make complex process and data relationships easy to grasp
• Present the logic behind decisions transparently and comprehensibly
• Strengthen trust, credibility and clarity in change communication
• Prepare and sharpen communication, texts and presentations with AI
• Prepare dialogue formats, town halls and feedback loops deliberately
• Communicate effectively in critical phases and after setbacks
• Balance AI-supported and personal communication sensibly

You analyze project trajectories, process metrics and market movements with modern methods – and translate weak signals into effective countermeasures, resilience and stability.

• Build early-warning systems for process deviations and project progress
• Recognize weak signals of overload, lost trust and change fatigue
• Expose spurious causality, policy resistance and typical thinking traps
• Detect market movements, trends and weak signals early
• Build resilience against disruption, price pressure and new business models
• Assess the risks of automation, system changes and migrations
• Professionalize risk management with AI-based models
• Find the balance between stability and agility

AI changes not only process and leadership decisions, but also responsibility, liability and trust.

In the seminar, AI is not treated as uncritical hype, but as a responsible leadership instrument for lasting impact and legitimate decisions.

• Develop governance structures for process ownership and AI-supported leadership
• Clearly define responsibility, liability and roles in the use of AI
• Take account of data protection, employee representation, compliance and regulatory requirements
• Establish ethical guardrails for automation and performance data
• Build acceptance among employees, the works council and stakeholders
• Address bias, misinterpretation and auditability systematically
• Communicate the impact of automation on jobs transparently
• Assess and communicate the limits of AI realistically

You identify the biggest levers in your own area of responsibility and develop your personal playbook for processes, decisions and change – ready to apply directly in your leadership practice.

• Reflect on your own process, decision-making and change practice in a structured way
• Identify strengths, gaps and untapped potential in your use of AI
• Derive concrete measures for your own area of responsibility
• Bundle fragmented initiatives and align them for shared impact
• Identify the biggest levers for impact, speed and acceptance
• Set implementation priorities for the next 100 days
• Prepare the transfer into your organization, your team and everyday change work