Michael Weiße × Monika Mlady
If you don’t just want to introduce AI, but truly embed it across your organisation, we have a proposal:
Two minds. One goal.
Strategy, transformation, delivery and a healthy dose of pragmatism – so AI doesn’t end in PowerPoint, but becomes part of everyday work.
01 · Reality check
A demo flow can be built quickly. AI only matters when it fits real processes, ownership, systems and day-to-day work.
Monika asks first: Which problem is actually worth solving? Where is the business value? What do people and processes need?
Michael asks: How do we turn that into a solid plan? Who owns what? Which dependencies, risks and quality gates need to be under control?
Two perspectives. One reality check.So AI doesn’t just impress. It works in the real world.
02 · Profiles
Same mission. Different focus.
AI Strategy · Enablement · Leadership
Monika connects business, technology and people. She leads a 35-person consulting and delivery unit, built a ten-person AI delivery capability and developed new offerings around agent assist, voice AI, AI strategy and assessments. Her first step is never choosing a tool. It is asking: Which problem is actually worth solving?
View profile →AI Delivery · Transformation · Governance
Michael brings structure to complex transformations. He translates strategic goals into clear work packages, manages dependencies and risks and stays close to execution from UAT and migration through go-live. His experience ranges from international rollouts across more than 40 countries to self-built AI workflows. His focus: turning a good idea into a reliable solution.
View profile →Different strengths. One strong outcome.
03 · Collaboration
Two perspectives. One continuous view from idea to operations. No relay race between strategy and delivery: Monika and Michael work through the problem together, challenge assumptions, evaluate options and consider execution from day one.
Does it create real business value? Does it survive in day-to-day business reality?
Less handover. Fewer blind spots. Better decisions.
04 · Operating model
Start with the problem, not the tool. Where does friction cost time, money or quality today? Where can AI make a measurable difference? And where is a simple workflow the better answer?
Evaluate use cases based on business value, feasibility, data readiness, risk and adoption. Weak ideas are stopped early. Strong ideas get a clear business case, an owner and measurable pilot goals.
No pilots without a path forward. Guardrails, ownership, delivery cadence and the operating model are designed from day one – so a proof of concept can become a reliable solution.
Usage, quality, cost and feedback drive the decision. What works gets scaled. What needs improvement gets adapted. What creates no value gets stopped.
Less tool sprawl. Fewer pilots going nowhere. More AI that gets used, can be operated and pays off.
05 · 90 days
Clear focus. Measurable impact.
A shared view of initiatives, stakeholders, dependencies, risks and open decisions. What is already running? What is duplicated? What is blocked? And where is TQG currently losing time, quality or margin?
Outcome: an honest AI landscape instead of another collection of ideas.
Value: less duplicated effort, visible blockers and a shared understanding of where action is truly worthwhile.
A prioritised portfolio with clear ownership, practical guardrails and an aligned mandate for piloting or scaling – assessed by business value, feasibility, data readiness, risk, adoption and total cost of ownership.
Outcome: a portfolio with owners, guardrails, success metrics and a clear delivery mandate.
Value: focus instead of tool sprawl. Decisions instead of endless evaluation.
One prioritised use case moves into a measurable pilot – or an existing initiative reaches its next meaningful decision gate.
Outcome: not another demo. Evidence.
The decision: Scale it. Fix it. Or stop it.
06 · Independence
We are applying together for two distinct roles at TQG – as a well-established team.
Because our work together has shown us that we can achieve more as a team: We challenge assumptions, uncover blind spots early, and bring Strategy, Enablement, Governance, and Delivery together as one coordinated effort.
That helps us move faster from a good idea to a decision that holds up in execution.
Two roles. One AI Transformation Engine.
