An AI Workflow Design,
in full.
Not consultancy to redo every time, but a reusable playbook. This is the HR & People department example, open and free: what to really automate, with which tools, in which phases and — the most delicate point — with which controls when who you hire is on the line. The exact shape of what we graft into your business.
What to really automate
The pattern of what works: high-volume, rule-governed document and administrative work. AI doesn't decide who to hire and doesn't run the interview — it removes the repetitive triage and the routine questions around the decision, where the bottleneck is the hours, not the judgement. Screening stays the most-adopted use case, but it's also the one that carries the tightest regulatory oversight (see governance, below).
- Application screening and sourcing al posto di: Manual CV triage, keyword search
- Onboarding automation al posto di: Forms, calendars and role instructions by hand
- Self-service HR knowledge base (leave, payroll, benefits) al posto di: Tickets to the HR office for routine questions
- Engagement analysis and disengagement signals al posto di: Manual reading of pulse surveys, reactive exit interviews
- Performance review drafts al posto di: Manual synthesis of collected feedback
Screening is the most-adopted HR-AI function (about 58% of companies that use AI in recruitment), and automated screening + onboarding flows report admin-load reductions of up to 75%. But the available figures are self-reported aggregates from vendors and analysts, not independently verified: read them as direction, not a promise of results. The number that matters for an SME is a different one — HR-AI adoption sits at about 33% among small businesses versus 60% at large ones: the gap, not the chatbot, is the opportunity.
Two models, not a shopping list
The 2026 HR-AI market splits into two models useful to an SME. The right choice depends on where your people and data sit, not on the most-cited tool. The enterprise suites for people management (like Workday) remain a reference ceiling, not a starting point for an SME.
Vertical HRIS with built-in AI
A dedicated HR platform (like BambooHR or HiBob) that brings AI into the processes that really eat the hours — employee records, onboarding, staff requests — at a per-employee cost. It's the right cut for the SME tier: real automation on a single process, before any ambition on recruitment.
Horizontal copilot on the suite
An assistant (like Google Workspace with Gemini or Microsoft 365 Copilot) that speeds up drafts, the knowledge base and internal communication inside the tools you already use. If you're already on Workspace it's often the cheapest AI entry point; it stays a horizontal assistant, though, it doesn't handle high-volume HR flows on its own.
Our default choice for an SME is to start from the horizontal copilot if you're already inside that ecosystem — marginal cost and near-zero risk, because it doesn't touch recruitment — and move up to a vertical HRIS when the volume of people or onboarding justifies it. Automated screening is weighed last, never first: picking the exact vendor, the due diligence on its data-processing terms and its EU AI Act compliance documentation are part of the graft.
The phases of the graft
Every item in the playbook carries a phase, so halfway through you filter by "what comes next" instead of re-reading the pilots you've already closed. In HR the order isn't negotiable: you start from the low-risk case, recruitment arrives only with the controls already in place.
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1
Pilot
First 30 daysA single use case — usually the internal HR knowledge base (leave, payroll, benefits): high volume, low risk, no recruitment data. A named owner, the usage policy written and the metrics instrumented before you start. This is where the first hours are freed up at the HR office.
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2
Scale
First 90 daysThe workflow that worked extends to onboarding and — only with the compliance controls already standing — to application screening. It's the delicate step: any use in recruitment enters the high-risk perimeter of the EU AI Act, so it arrives with human oversight and documented bias tests, not before.
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3
Ongoing
Steady stateContinuous monitoring of adoption, data quality and — on recruitment — outcomes by group, with periodic review of vendors and risks. The playbook stays alive: it gets updated at every hiring cycle and as regulatory deadlines approach, not archived.
The compliance overlay, and who governs it
Recruitment is high-risk (EU AI Act, Annex III)
It's the most important rule in the whole catalogue, and in HR it counts double: the EU AI Act (Annex III) classifies as high-risk AI systems used for recruitment, promotion, termination and worker monitoring. A June 2026 European agreement pushed the full obligations to December 2027: it's a window to get ready, not an exemption. The bias is documented, not hypothetical — research on recruitment algorithms has found candidates screened out by group. With us no workflow that touches recruitment ships without human oversight, documented bias tests and a risk assessment: before ROI, you build the legal defensibility of the decision.
Compliance overlay
HR processes the most sensitive personal data in the company — applications, appraisals, performance: it raises the same GDPR questions as the rest of the playbook, but with the bar higher. An impact assessment (DPIA) almost always necessary, data minimisation, a legal basis for processing candidate data, transparency towards the data subject on automated processes. For high-risk cases (recruitment) come the technical documentation, logs and human oversight required by the EU AI Act: due diligence on the vendor and its processing terms is a non-negotiable part of the software choice.
The AI owner
No big-enterprise Center of Excellence: in an SME one or two people named as AI owner are enough. Five responsibilities stay with them — setting priorities, who approves what (recruitment use first of all), enabling the team, reusable standards and monitoring adoption, data quality and outcomes — without assuming a whole dedicated department. On high risk, it's the owner who keeps the record of who validated what.
The same pattern, other departments.
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Sales
Lead scoring, automated follow-ups, CRM hygiene.
See the full example -
Marketing
Campaign optimisation and copy with brand oversight.
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Operations
Process automation, reporting and anomaly detection.
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Finance & Administration
Accounts payable, month-end close and cash forecasting, with a human on the money.
See the full example -
Customer support
Ticket deflection, triage and agent-assist, with answers anchored to sources — no hallucinations.
See the full example
This is the example. We graft yours.
The other departments follow the same pattern. Start from the free assessment to find out where it makes sense to begin, or let's talk directly.
Example for guidance only: it does not constitute legal or tax advice or a compliance assessment.