Monika Mlady · AI Enablement & Transformation Lead
I turn complex AI questions into clear decisions, sustainable structures and solutions that work in everyday business.
I never start with the latest tool. I start with the Business Problem, assess what people and processes actually need, and connect Strategy, Enablement, Governance and Delivery. Today, I lead a 35-person Consulting and Delivery unit, have built a ten-person AI Delivery Capability, and develop AI offerings and customer solutions from the first Use Case idea through production use.
01 · Leadership profile
My goal is not more AI.
My goal is people who use AI with purpose – and solutions that still work on Monday morning.
Technology matters to me when it solves a real problem. That is why I start with Business Value, people and processes – not with the latest AI tool.
Only then comes the technology decision: AI Agent, Workflow, RPA or traditional automation. The most advanced option does not win. The option that best fits the problem, risk and operating model does.
As a Managing Consultant and Team Lead, I connect People Leadership with portfolio development, technology selection and Governance. I create clarity, build capabilities and give teams the framework to make sound decisions themselves.
02 · Role fit
I turn “We should do something with AI” into a solid Use Case. I assess Business Value, User Experience, Data Readiness, risk and Total Cost of Ownership. Then the decision is clear: build it, solve it differently or stop it.
Adoption is not a communication package added shortly before rollout. I involve people early and connect new Use Cases with learning formats, coaching, hands-on experimentation and feedback. The result is not just usage, but real capability.
I define early what AI may handle, where a deterministic path is required and when a human needs to decide. In Conversational AI, I evaluated Use Cases, platforms, Human Handover and Knowledge Integration together with Business and technology stakeholders.
My experience in Product Ownership, transformation and ITIL-based Service Governance helps me not only introduce new solutions, but also transition them into reliable operations.
03 · Impact
I don’t just build solutions. I build the capabilities, structures and decisions that make them last.
04 · Cases
Service demand kept increasing. Available capacity did not. Longer waiting times, routing inefficiencies and declining customer satisfaction made one thing clear: simply adding more people was not a scalable answer.
The obvious question would have been: Which AI platform should we introduce? I asked a different one: Which customer interactions actually require a human?
As a Product Owner, I initiated the market analysis and technology evaluation for Conversational AI, translated emerging capabilities into concrete Business Use Cases and worked with Business teams, vendors and management on a realistic roadmap. We developed PoCs and pilots for selected Voice Use Cases, including Intent Recognition, Caller Authentication and knowledge-based Self-Service. Every solution included a clear Human Handover whenever automation reached its limits.
In parallel, I established an internal AI Community to connect knowledge across business units and move AI beyond an isolated technology initiative.
Outcome: not a rushed large-scale implementation, but a sound foundation for better decisions. The goal was never more AI. It was better decisions.
Voice, CRM and digital channels were owned separately. Processes, routing and reporting followed different logic. Service employees had to work across up to 14 applications at the same time. Every department optimized its own system. Nobody optimized the Customer Journey.
Instead of starting another technology project, I reframed the discussion: How should Customer Service work in the future — regardless of which tool is in place today?
I developed the strategic target vision for a shared Service Operating Model and brought together more than 50 stakeholders from Business, Service Operations and IT. Together, we restructured processes, ownership and requirements: one consistent Customer Context, cross-channel routing, shared Case processes, consistent reporting, and a solid foundation for Workflow Automation and Self-Service.
To secure Executive Sponsorship, I showed a real service workplace with 14 applications open at once instead of adding more architecture slides. The problem became visible immediately.
Outcome: an aligned strategic target vision and the organizational foundation for a connected Customer Journey and future AI-enabled services. First create clarity. Then choose the technology.
A business-critical Contact Center platform had reached the end of its life cycle. Around 1,500 Contact Center and 3,000 back-office users, 60 business units and four locations depended on it every day. Any major disruption would have directly affected customer service.
The challenge was bigger than a migration: Change the platform without putting operations at risk — while establishing new ways of working. I led the transformation end-to-end: from vendor negotiations, contracts and management reporting through IT Security, Data Protection and Works Council alignment to rollout, training and Hypercare.
No big bang. No blind rollout. Key Users tested early. Pilot groups validated processes. Change champions became trainers. Each rollout wave was stabilized before the next one began.
When a business-critical vendor feature failed to work as promised, I paused, gave the team space and looked for a different solution with a clear head. The next morning, we had a working path forward.
Outcome: the legacy platform was replaced, Business Continuity was maintained, and routing, softphones, supervisor tooling and integration with CRM and collaboration systems were modernized. Transformation works when people, process and technology move together.
05 · Enablement & Adoption
A tool is not adopted simply because access has been granted. It is adopted when people understand where it helps, trust its boundaries and can use it to do better work.
AI is part of my daily work — from Business Discovery and Architecture through Knowledge Engineering and prototyping to documentation, evaluation and Workflow Automation. I use different models and approaches according to their strengths. Not to add AI everywhere, but to reach better decisions and outcomes faster.
I built a ten-person AI Delivery Capability and developed traditional Contact Center roles through AI training, Vendor Enablement, coaching, hands-on experimentation and a weekly Lessons Learned format.
Adoption is more than login numbers. Depending on the Use Case, I assess usage and acceptance, Customer Experience, manual effort and handling time, process quality and automation rates, Knowledge Quality and Retrieval, cost and maintainability. This measurement logic determines what gets scaled, improved or stopped.
Enablement succeeds when AI stops being a special project and becomes a better way of working.
06 · Governance
For me, Governance does not start with a policy document. It starts with clear decisions: What may AI handle? Who remains accountable? How is quality evaluated? What happens when the system is uncertain? And when do we switch it off instead of continuing to optimize?
Not every problem needs an AI Agent. Sometimes a deterministic Workflow is more reliable. And sometimes the best process emerges from a combination of AI, Automation and Human Review.
That is why I do not assess solutions based on technical feasibility alone. Business Fit, User Experience, hallucination risk, integration capability, Governance, cost and long-term maintainability all belong together. Guardrails and Human Handover are not barriers to innovation. They are what make trust possible.
Good AI solutions need to survive both: the excitement of the first workshop and the reality of Monday morning.
07 · Leadership & Stakeholder
Setting priorities. Making decisions. Addressing conflict instead of postponing it. Defining standards. Developing people. And remaining accountable for the outcome.
Today, I lead 35 people with both functional and disciplinary responsibility. My scope includes portfolio, Presales, Delivery, capacity management, hiring, people development, Vendor Management and Alliance Management.
I give teams room to think, learn and experiment – but never without direction, clear expectations and a reliable decision framework. This balance is particularly important in AI: freedom without focus creates tool sprawl. Governance without trust creates paralysis.
Stakeholder Alignment does not mean keeping everyone equally happy. It means bringing Business, Tech, Security, vendors, leadership and Delivery to the same decision point. I make goals, conflicting interests, risks and dependencies visible. I translate complexity into understandable options, clear trade-offs and concrete next steps.
Clarity creates ownership. Ownership creates progress.
08 · Motivation
The role at TQG brings together exactly the areas I have been building my work around for years: translating Business Problems into scalable AI initiatives, enabling people, establishing clear Governance and embedding new solutions into everyday operations.
TQG is not looking for an isolated AI playground. AI needs to be structured, prioritized and made useful across Business, Tech and Security. That is where I add value: turning fragmented ideas into clear focus and building the capabilities that make transformation sustainable.
There is also a strong personal connection.
Sport shaped me long before AI became part of my profession. From the age of 10 to 35, I competed in elite cycling, competing at the German and Bavarian Championships, in the 1st German Cycling League, and as a regional squad athlete. It taught me that performance does not come from one major breakthrough. It comes from continuously learning, measuring and improving.
Nutrition, recovery and supplementation were never side topics. ESN and More Nutrition are still part of my everyday life — including ESN Creatine at my desk and More Zerup Barista Vanilla on top of my coffee machine.
Performance. Science. Technology. People.
At TQG, these areas come together. That is why this role does not feel like a move in a new direction. It feels like the logical continuation of what I have been building.
09 · Personal
I am a leader, an artist, a trained coach and, more recently, a runner.
After many years in competitive cycling, running means becoming a beginner again: learning from scratch, building patiently and not confusing progress with perfection.
In my own studio, I work with colors, shapes and ideas that do not always have an obvious answer. It sharpens my ability to see connections, perspectives and what lies beyond the most obvious solution.
My coaching education and curiosity for personal development help me understand how people learn, change and take ownership.
Curiosity. Growth. Creativity. And the willingness to keep becoming a beginner again.
monika@mlady.de
Based in Nuremberg · open to coordinated, purpose-driven on-site presence in Hamburg · notice period of three months to month-end.