Leadership & management
For decision-makers who want to understand what generative AI means for their organization, which opportunities are realistic and which conditions become necessary.
04AI Transformation & Sparring
← Back to the offeringIntroduce AI sensibly, without getting lost in the hype.
Many organizations know that generative AI is relevant. But it isn't always clear where to start, which use cases really make sense, which risks need to be considered and how individual experiments turn into a sustainable way of working. In this format I support companies, teams and leaders in framing generative AI realistically, finding where it fits and developing concrete next steps. Not as a big off-the-shelf transformation program. But as a structured sparring process that fits the organization.
For organizations, leaders and teams that don't just want to try generative AI out, but bring it into their own work purposefully, responsibly and with a clear focus.
Positioning
Between waiting and rushing in, what's needed is orientation.
In many organizations, generative AI creates pressure and uncertainty at the same time. Some teams are already experimenting intensively. Others wait for clear rules, safe tools or strategic direction. This often leads to parallel movements: a lot of curiosity, many separate initiatives, but no shared understanding yet.
This is exactly where sparring helps. It creates room to sort out opportunities and risks, make concrete areas of application visible and plan the next steps so they fit the organization.
AI transformation doesn't mean changing everything at once. Often it starts much more pragmatically: with better questions, clearer use cases, suitable formats and a realistic view of what's already possible today.
Who it's for
For organizations that don't just want to try AI out, but make sense of it.
Departments & teams
For areas that already have first ideas or experiments and want to structure, prioritize and translate them into sensible next steps.
HR, communication & enablement
For people tasked with developing and guiding internal learning formats, guidelines, communication or skill-building around generative AI.
What happens in the sparring
Many loose ideas turn into a clearer picture.
Sparring isn't about collecting as many buzzwords as possible or writing an abstract AI strategy. It's about understanding your own starting point, recognizing relevant applications and deriving concrete, actionable steps from them.
Depending on the audience, the focus can lean more toward strategy, use cases, governance, enablement or practical implementation.
Understand the starting point
Where does the organization stand today? Which tools, rules, experiences, expectations and uncertainties already exist?
Identify use cases
Which tasks, processes or recurring activities could be noticeably supported by generative AI?
Prioritize
Not every use case is equally relevant. We distinguish between quick learning fields, productive applications and topics that need more preparation.
Clarify risks and conditions
Data protection, confidentiality, quality assurance, compliance and governance are considered from the start, not added only at the end.
Plan enablement
Which audiences need which knowledge? From this come suitable formats: sessions, workshops, guides, learning paths or internal exchange formats.
Define next steps
At the end there's no abstract sea of slides, but a realistic plan: what should happen next, who is involved and what is deliberately still open?
What can come out of it
No off-the-shelf strategy. But next steps that fit.
The result depends on the situation. Sometimes orientation is needed first. Sometimes a use-case map. Sometimes an enablement concept. Sometimes simply honest sparring before bigger decisions are made.
Formats
Possible formats
AI Transformation & Sparring can be run as a compact strategy workshop, ongoing sparring or a modular process. What's decisive is how much orientation, structure and guidance is needed. Many start with a single sparring session and then decide whether more guidance fits.
Sparring session
A compact format for leaders, project owners or teams who want to sort out a current question and derive next steps.
Suitable for
- first orientation
- decision preparation
- framing concrete questions
Use-case workshop
Identifying, structuring and prioritizing sensible AI application areas together, starting from real tasks in the team. With a view to benefit, feasibility, risks and organizational conditions.
Suitable for
- departments
- innovation teams
- internal AI working groups
Ongoing sparring
A flexible format across several sessions. Suitable when AI adoption, enablement or internal communication should be guided over a longer period rather than at a single point.
Suitable for
- AI adoption
- enablement programs
- pilot projects and roadmaps
How it works
From sorting things out to realistic next steps.
AI transformation rarely starts with the perfect master plan. Usually it starts with better questions: Where do we stand? What's relevant? What's allowed? What's feasible? And where should we begin?
Understand the starting point
We clarify where the organization stands: previous experience, existing tools, internal rules, audiences, expectations, uncertainties and possible friction points.
Sort use cases and questions
Together we make sensible areas of application, open questions and possible risks visible. Not every idea is equally important, equally feasible or equally suitable.
Set priorities
Use cases, enablement needs and next steps are sorted by benefit, feasibility, risk and organizational fit.
Derive next steps
At the end there's no abstract strategy paper, but a clearer basis for decisions: possible pilot projects, learning formats, guardrails or a sensible next appointment.
Example topics
Typical questions
Why with me
I combine AI practice with organizational reality.
I don't talk about generative AI from a distance. I work with it every day: for research, writing, analysis, product ideas, prototypes, automation and agentic working. That's how I see very concretely what's already productively possible today and where you should stay careful.
At the same time I've worked for many years where technology, digital products and organizations meet. For 15 years I ran an online marketing agency and, together with my team, delivered hundreds of digital projects. My role was often the interface between clients, departments and development: understanding requirements, translating technical possibilities and turning ideas into workable solutions.
For around ten years I've worked at Dolphin Technologies in product development and product management, mainly in the insurance sector. From that work and from projects with banks, I know heavily regulated business environments where data protection, governance, compliance, internal approvals and existing processes aren't side issues, but part of reality.
This combination is decisive for AI transformation. It's not about introducing as much AI as fast as possible. It's about finding the right next steps: understandable, compatible and realistic enough to hold up in everyday work.
Gerald Aichholzer
Advisor, trainer & speaker on generative AI
Outcome
What's clearer afterward
Relevant use cases
The organization sees more clearly where generative AI can create concrete benefit and which ideas are less suitable.
Realistic priorities
Not everything has to happen at once. The next steps are sorted by benefit, feasibility and risk, before budget and tools are committed.
Suitable enablement formats
It becomes clearer which audiences need which knowledge and how learning can be organized in practice.
More decision confidence
Leaders and teams can better judge which actions make sense, which guardrails are needed and which questions deliberately stay open for now.
Frequent questions
What often gets clarified beforehand.
Is this classic AI strategy consulting?
Not in the classic sense. It's not about a big off-the-shelf strategy paper, but about orientation, prioritization and realistic next steps that fit the organization.
Can you start with a single session?
Yes. Many questions can be sorted out well in a compact sparring session. Afterward it's usually clearer whether a workshop, a pilot project, an enablement format or further guidance makes sense.
What's the result in the end?
Depending on the format: a sorted use-case list, first priorities, a roadmap for next steps, an enablement concept, sparring results for leaders or a better basis for decisions on internal AI initiatives.
Who should take part internally?
That depends on the topic. Usually it makes sense to involve people from departments, leadership, IT, data protection, communication, HR or operations. What matters is that need, feasibility and conditions are all represented.
How concrete does the sparring get?
As concrete as possible. The starting point is real questions, tasks, processes and decisions. The goal isn't to discuss AI in the abstract, but to find out what makes sense as the next step for the respective organization.
Before and after
Sparring is often the frame for the other formats.
01
Talks & keynotes
For events and leaders where AI should first be framed clearly, before a team starts working with it hands-on.
02AI Workshops & Training
For teams that don't just want to understand generative AI, but apply it practically to their own tasks.
03Coding for Non-Coders
For people without a programming background who want to build small tools, prototypes and automations with AI.
Inquiry
Let's sort out what makes sense for your organization.
Whether a single sparring session, a use-case workshop or an ongoing process: I develop the format to fit the starting point, audience and decision needs. The goal isn't a ready-made AI master plan, but a clearer view of realistic next steps. A short inquiry is enough; we clarify the right setup beforehand, with no obligation.