Enterprise AI adoption
Use cases, ownership, data needs, build, buy or stop choices and a practical adoption roadmap.
Technology strategy
I translate complex technology into decisions people can act on.
AI adoption for enterprises. GTM, business model and investor readiness for startups. Board and public-sector advisory when the stakes are real.
Advisory
Enterprise teams need a path from pressure to adoption. Startup teams need a stronger business model, market story and investor logic. I help turn technical potential into decisions people can use.
Use cases, ownership, data needs, build, buy or stop choices and a practical adoption roadmap.
Business model, pricing, customer story, route to market and investor readiness.
Practical AI and emerging-tech judgment for boards, agencies and industry initiatives.
Founder evaluation, pitch judging, program design and conference work where the business case has to hold up.
Formats
Fixed-price calls for fast senior input. Enterprise AI work, startup strategy and board advisory stay scoped, practical and tied to a decision.
Independent advisory runs outside institutional commitments and depends on availability, mandate fit and conflict clearance. Compact formats are preferred; full-day work only by arrangement.
90 minutes on AI roadmap, use cases, ownership, build, buy or stop choices and the next implementation decision.
90 minutes on business model, GTM, pricing, market story, investor readiness and route to market.
Half-day, evening or split-session format for leadership teams that need a practical AI adoption path.
Limited monthly access for founders, executives or program leads who need senior sparring without a large consulting setup.
Advisory for boards, agencies and industry initiatives working on practical AI adoption.
Conference talks, pitch jury work, panels and investor-facing formats around AI, startups, GTM and technology adoption.
Fit
There should be an owner, a deadline and something meaningful at stake: adoption, GTM, funding, board judgment or public-sector work.
Outcomes
A workshop or advisory call is only useful if it changes what happens next: the adoption path, the build-or-buy call, the investor story or the board decision.
Prioritized use cases, owners, data needs, risks and the next implementation path.
A practical decision on what belongs inside the company, outside the company or nowhere at all.
Sharper customer, pricing, route-to-market and funding logic for technical founders and accelerator teams.
Clear language for boards and senior teams who need to understand what changes, what does not and what decision comes next.
Selected proof
A short selection of enterprise, accelerator, venture, media and technology work.
Titan Network
Work pattern
Across roles, the work stayed consistent: turn technical potential into adoption, revenue, funding and operating decisions.
AI-Rad Companion and AI-Pathway Companion work at Siemens Healthineers. Consultant for AI Acceleration & Growth at AI Factory Austria AI:AT, focused on Austrian industry enterprises.
UNDP SDG Accelerator, Cointelegraph Accelerator and 80+ AI and technology startups across pitch, GTM, pricing, investor readiness and partner strategy.
USD 4M+ in partnership revenue during Cointelegraph growth work, plus enterprise sales motion work for infrastructure and web-data products.
Advisory, investment and fundraising work across AI, SaaS, fintech, infrastructure and Web3, including USD 25M+ raised by supported Web3 startups.
Earlier operating experience across software, publishing, strategic marketing and field-sales SaaS work, including FieldProFlow.
Speaking
Talks, panels and jury work where teams have to explain who adopts the product, who pays and why now.
References
Selected excerpts from LinkedIn recommendations. The source, context and relationship stay visible on each card.
"His mastery of strategic conceptualization and actionable execution is second to none, parsing the signal from the noise."
Anthony FrancisCointelegraph context, LinkedIn recommendation, Nov 2025
"He has a rare ability to look at a project and quickly get to the core business risks and opportunities."
Chris ScibiorekCointelegraph Accelerator, LinkedIn recommendation, Nov 2025
"He gets the space, asks the right questions, and brings clarity when it's needed most."
Pawel LaskarzewskiNomad Fulcrum, LinkedIn recommendation, Jul 2025
"Paul brings a rare blend of strategic clarity and hands-on leadership in marketing, positioning, and reputation-building."
Anna ShakolaADI Foundation, LinkedIn recommendation, Jun 2025
"His remarkable ability to tackle complex challenges with innovative solutions makes him an invaluable asset to any team."
Oliver SchmittVenture value building, LinkedIn recommendation, Jun 2025
"Paul knows how to engage people in a conversation and challenge them to come up with ideas and opinions."
Roland LindnerDeloitte Digital Austria, direct manager, LinkedIn recommendation, Sep 2020
"Focused on outcomes that are highly creative while also being on point, not wasting efforts or budget."
Petra GruenSiemens Healthineers, LinkedIn recommendation, Jan 2019
"Thanks to him the global launch of the AI-Rad Companion was an outstanding success."
Ivo DriesserSiemens Healthineers, LinkedIn recommendation, Dec 2018
"Endlessly tenacious, unrivaled in curiosity, and exceptionally in tune with what others need and want."
Liz KraftSiemens Healthineers, LinkedIn recommendation, Oct 2017
Principles
Start with the business problem. Then decide whether AI, software or another technology belongs in the solution.
I do not replace the technical team. I make sure the right problem, owner and adoption path are in place before more budget goes in.
I am not an AI engineer. I am technical enough to pressure-test AI and software work, and hands-on enough to build with it, including FieldProFlow.
No owner, no value.
Adoption needs operating logic, not just use cases.
Build, buy or stop should be explicit.
Complex technology must fit how people buy, fund and implement.
Send the context: what decision is on the table, who owns it, what happens if it stalls and which advisory lane fits.
LinkedIn proof