AI is not just doing what you already did, faster.
I get your company to make the most of AI and turn it into new capability and competitiveness. I go function by function: I redesign the workflow from zero and install the operating model that makes the new way of working the default. Independent and platform-agnostic, whether you are filling a permanent AI leadership seat or not.
AI cuts across how decisions get made, how risk gets governed, how customers get served. Your organisation runs in vertical lanes, and closing that gap is an operating change before it is an org-chart change. That is the part most companies underestimate.
Where you already are decides how I help. If someone inside the firm already leads AI, I work alongside them to get the operating model, the metrics and the first use cases right, and add delivery capacity where it is thin. If no one owns it yet, I come in first on a time-boxed mandate, install the capability and ship the early wins, so the permanent leader you hire inherits a working function instead of a blank page. Either way the role is built to make itself unnecessary, and your team owns the capability at the end.
I have run this before. As Director of AI Transformation at a PE-backed software company, I rebuilt the go-to-market and back-office around AI under a P&L mandate, in production, and cut a core quote-to-cash process from days to hours, with full automated-test coverage behind it. I would have paid for someone to walk me through what works and what does not, instead of guessing and making every mistake in the book. That is what you get: the expertise a team usually earns over twelve to eighteen months of expensive mistakes, on the table from day one.
My focus is augmentation: AI that lets a hundred-person company perform like a thousand-person enterprise, where the same people take on work they used to turn away and the business grows.
The AI-maturity self-assessment. Six questions, five minutes, no call. You get a scored read of where your AI stands and the three fixes to make first. It is the honest place to start, and it costs nothing.
Take the free assessment →Most AI bets fail before they start. Wrong platform, wrong workflow, wrong success criteria. I map your real constraints and recommend a stack you can live with.
I sit with the people who run the function until I understand it properly, then rebuild the workflow from zero: the machine takes the repeatable steps, your people keep the calls that need judgment. That goes a lot further than wiring AI into the process you already have. I embed for 8 to 16 weeks and ship it to production alongside your engineers, ops people and domain experts, with security and governance baked in from day one.
Most AI dies quietly, and rarely because of the tool. It falls out of use because it asks people to rethink who they are at work. The last 20% is getting your best people to rebuild their role around judgment, so they pull the tool in instead of shelving it. I stay through that, measuring adoption and redesigning roles until the new way of working is the default.
Fines reach €35M or 7% of global turnover for prohibited uses. Prohibitions and the staff AI-literacy duty under Article 4 have applied since February 2025. The fines regime has been in force since 2 August 2025. Article 50 transparency duties and GPAI enforcement start on 2 August 2026. The high-risk obligations, recruitment and employment AI included, moved to 2 December 2027 under the adopted Digital Omnibus.
haven’t taken meaningful compliance steps
Vision Compliance, 2026
no complete inventory of AI systems in use
PwC, 2025
report AI literacy gaps across workforce
DataCamp / YouGov, 2026
From days to hours. I rebuilt a multi-team quote-to-cash cycle with full automated-test coverage, lifting win rate on the deals that turn on speed.
From weeks behind to live. Scoring with intervention triggers, replacing a manual review that lagged the real state of each account by weeks.
A week back, every cycle. Source systems pulled into a single management view on a schedule, replacing the hand-assembly.
Win rate nearly doubled. I built the global solutions-engineering function from the ground up and nearly doubled the win rate on complex enterprise deals, and led the analyst engagement behind the company’s leadership placement in a major analyst evaluation of its category.
I process EU personal data under signed Data Processing Agreements with every client and every infrastructure provider in the stack.
Every tool in the stack holds an independent SOC 2 Type II audit. I select for it before writing a single line of code.
Encryption at rest and in transit. Private networking between services. Tenant isolation per client.
Your team authenticates through your existing identity provider (Okta, Azure AD, Google Workspace) from day one. No separate credentials, no friction for IT.
I de-risk and accelerate AI value creation across your portfolio, fractional, with no full-time hire to fund per company. The cost-out play books a one-time saving before exit. The AI-native play removes the bottlenecks, so a company takes on work it could not before and grows revenue without adding headcount, and that compounds across the hold. I build the second. I take no vendor commissions, so the recommendation is the one that grows the asset.
For private equity →AI lands in a firm when the platform, the workflows, and the people all fit together, with privileged client data protected at every step. That is the work: the right platform, two or three workflows that give real hours back, a matter-by-matter privilege posture, and the whole thing defensible under EU law. Independent and platform-agnostic, so the recommendation is the one that fits your firm.
For law firms →A 30-minute working call. You leave with a read on where AI would pay back first in your business, whether or not we work together. I talk about your actual situation. If I can help, I’ll scope it. If I can’t, I’ll say so and point you at someone who can.
Or start with the free AI-maturity assessment →