AI Director · Interview Study Companion

Become AI-native for a media, events and iGaming powerhouse

Nadine is assessing three things: do you understand the business, can you think strategically, and can you explain complex systems simply. This page turns your prep into pictures so the model sticks. The one rule: every answer connects AI to revenue or relationships, never technology for its own sake.

Role: AI Director, exec team, reports to COO Setup: hands-on IC + budget for tools, contractors, headcount Location: fully remote (Malta HQ) Company: ~46 people, investor-backed, scaling
6,000delegates at NEXT Valletta (40% operators)
€175ktop headline sponsorship (of 58 products)
400+podcast episodes; in-house research team
$9bnprojected Brazil market by 2029 (they are scaling in)
01

How NEXT.io makes money: the flywheel

Memorise this. It is the deal-breaker question. Content builds a senior audience, the audience draws delegates, and access to that audience is what sponsors pay for. The revenue funds more content, and the wheel turns faster.

Drag to pan · Ctrl/Cmd + scroll to zoom · buttons top-right · expand to open full size

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The audience is the product. Everything builds a senior, trusted audience, and sponsorship and tickets monetise access to it.

Stream 1

Sponsorship

The biggest lever. 58 products per event, headline down to lanyards. Plus media: banners, editorial, podcast, Magazine.

Stream 2

Delegate tickets

Paid entry to summits and the NEXTPredict summit. Volume play (Valletta ~6,000).

Stream 3

Media advertising

Year-round monetisation of the daily news audience via ads and sponsored content.

Stream 4

Retreats + research

Invitation-only luxury retreats and paid market reports. High-margin, relationship-driven.

02

The iGaming value chain (close your domain gap)

You have no industry experience, so learn who the players are. NEXT.io sits above the whole ecosystem as the neutral meeting place: it serves operators, suppliers, affiliates and investors, and monetises their need to reach each other.

Solid arrows = money and players flow · dotted = who NEXT.io serves

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NEXT.io (the hub)
Operators (the buyers of games)
Revenue

Glossary to drop naturally

TermPlain meaning
OperatorThe betting or casino brand players use (B2C). bet365, Entain, Flutter/DraftKings, Betsson, Casumo.
Supplier / providerPlatform tech and game studios that power operators (B2B). Evolution, Pragmatic Play, Playtech. The big sponsors.
AffiliatePerformance marketer who sends players to operators for revenue-share or CPA.
GGR / NGRGross / net gaming revenue. The industry's core money metric.
CPA vs rev-shareTwo ways affiliates get paid: a fixed cost-per-acquisition, or a share of player revenue.
KYC / AMLKnow-your-customer and anti-money-laundering checks. Compliance backbone.
MGA / UKGCMalta Gaming Authority and UK Gambling Commission. Malta is the European hub (why NEXT is there).
Hot topic

UK tax

New ~40% tax regime and Gambling Act reform squeezing operators.

Hot topic

US expansion

State-by-state legalisation since 2018. Why NEXT New York exists.

Hot topic

Brazil

Regulated 2025, ~$6.5bn first-year GGR, election-year risk. NEXT scaling in.

Hot topic

Prediction markets

Kalshi, Polymarket, Sporttrade. Why they launched NEXTPredict.

03

The sponsorship price ladder

A EUR 175k headline sponsorship is a consultative, relationship-driven sale, not a transaction. Knowing the range shows you understand where the money is and why personalization matters at the top end.

Product (NEXT New York, sample)PriceRelative scale
Headline Sponsorship (exclusive)€175,000
Livestream€45,000
Registration Sponsorship€38,000
VIP Speaker Lounge (exclusive)€30,000
Lanyards Sponsorship€25,000
Exhibition Stand€19,000
Delegate Badge (exclusive)€16,000
Nico Jansen Run Club€7,000
The tell. There are 58 products per event, spanning from a EUR 175k headline down to lunches and lanyards. The top of the ladder is sold on trust and relationship. That is exactly why AI should help the salesperson personalize and time the pitch, not automate it away.
04

The human side (where they say most candidates fail)

They want someone who understands why the business works, not just the tech. Have crisp answers to all four of these.

Why deals close

Sponsorship

A big sponsorship is a consultative sale. Sponsors buy access to the right audience (40% operators), brand authority, and warm introductions. Trust and the salesperson's relationship close it.

Why they convert

Delegates

Because of who else is in the room. People come for networking and deal-making, exclusivity, and quality speakers. Valletta is a festival week (golf, padel, parties) precisely because "that is the reason deals get done."

Why not automate

Personalization

These are high-value, bespoke relationships. Generic automation would cheapen the brand and break trust. AI should make the human touch sharper and better-timed.

Why it matters

Content and timing

In a regulation-driven industry, timing is everything. A story or a pitch lands when the market moment is right. Relationships are the moat.

AI here should amplify human relationships and editorial judgement, not replace them. Automate the grunt work so people spend more time on the relationships and timing that close deals.

Respect editorial independence. Their research team states: "We do not commission white papers or sponsored content. What we publish reflects what we find." Any AI you propose for editorial must protect that independence, never dilute it.
05

Where AI meaningfully helps (mapped to revenue)

Never pitch AI for its own sake. For each area, tie it to money or the human side. Note the tools already circling their space, so you can speak to buy vs build.

AreaAI opportunityWhy it matters to them
Commercial
biggest lever
Sponsor prospecting from the news (a funded company = a target), sponsor-to-product matching, personalized proposals, HubSpot enrichment, renewal prediction.Grows the €175k-type deals. Supports Richard Crow's commercial layer.
EditorialResearch assistants, podcast and session transcription plus summaries, SEO, localization (Portuguese/Spanish), repurposing one event into articles, social and clips.Scales content output without losing the human voice or independence.
DelegatesConversion prediction, personalized outreach, on-site matchmaking (they already run "AI Match Sessions").More ticket sales and a better attendee experience.
ResearchTurn the proprietary news archive and reports into a queryable knowledge asset and monetizable product.Their content becomes a durable, compounding company asset.
OperationsSpeaker sourcing, event logistics, internal knowledge search, CRM hygiene.Frees a lean team to keep scaling into Brazil and the US.
Know this tool

Blask

AI-powered market intelligence for iGaming. Featured on their own podcast. Your "research asset" idea competes here.

Know this tool

FastTrack.ai

CRM and automation for operators. Shows AI is already normal in their audience's world.

Know this report

State of AI in iGaming

NEXT.io's own report (150+ execs). Reference it: "one of the world's most data-rich industries."

06

What I would build first: the company brain

Lead with the shared knowledge foundation, then prove it with one revenue-linked lighthouse. Same order you followed on Nova Res: build the trusted retrieval foundation first, then layer specialist agents. Agents are only as good as what they can read.

Foundation first (left), then agents (middle), always with a human at the gate (right)

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Step 1

Foundation

One trusted place where editorial archive, HubSpot and market data come together, with retrieval so any tool or agent can read and write safely.

Step 2

Lighthouse

An AI sponsor-intelligence assistant that spots buying signals in the news and drafts personalized (not automated) outreach a salesperson refines and sends.

Step 3

Standards + coaching

Light standards from day one (where things live, what is safe to automate vs keep human) so it scales into Brazil and the US.

07

The 5-day study plan

About 2 to 3 focused hours per day. Produce the written output each day: writing forces clarity and gives you notes for interview morning.

Day 1
Master the business and the money

The company 45m

Homepage, culture, summits, retreats. Positioning: "iGaming Event of the Year" 2023.

The money 45m

become-a-sponsor (58 products, price ladder) and the Valletta page (6,000 delegates, AI Match Sessions).

Research arm 30m

Two report series and the editorial-independence stance.

Output  the revenue flywheel in your own words + one line per product line.
Day 2
iGaming fundamentals

Value chain 60m

Operators, suppliers, affiliates. Glossary: GGR/NGR, CPA, KYC/AML, MGA, UKGC.

Regulation and geography 45m

8 to 10 news articles. UK tax, US expansion, Brazil, Gibraltar.

Prediction markets 30m

Kalshi, Polymarket, Sporttrade. Why NEXTPredict exists.

Output  a one-page iGaming cheat sheet (value chain, 12 terms, 4 hot topics).
Day 3
The human side, people and culture

How they think 60m

1 to 2 NEXT.io Podcast episodes (hosted by co-founder Pierre Lindh). Bonus: Blask and Kyborg.ai episodes.

Human side 45m

Write your four answers. Draft the "amplify not replace" north-star line.

People and culture 30m

LinkedIn: Nadine, Pierre Lindh, Richard Crow. The five values.

Output  your human-side answers + 3 facts about Nadine for rapport.
Day 4
Your AI strategy for NEXT.io

Map AI to revenue 60m

1 to 2 concrete opportunities per area, each tied to money or the human side.

First-build narrative 45m

Company brain, then the sponsor-intelligence lighthouse, then standards and coaching.

AI landscape 30m

State of AI in iGaming report; Blask, FastTrack.ai, Kyborg.ai for buy vs build.

Output  a one-pager: 6 AI opportunities + your 3-step first-90-days plan.
Day 5
Mock interview and polish

Three stories 45m

PRISM, Nova Res RAG, Turners ransomware. 90 seconds each, plain English.

Full mock 60m

Rehearse the Q&A drills below. Ask Copilot to play Nadine.

Questions and logistics 30m

Finalise 4 questions for Nadine. Confirm format and timing.

Output  a single revision sheet to read 30 minutes before the interview.
08

Q&A drills

Rehearse out loud. The blue block is the line to actually say.

What does NEXT.io do, and how do you make money?
Lead with the flywheel, then the four streams. "You are a content-driven media, events and publishing company for iGaming. The news, podcasts and research build a senior, trusted audience. That audience draws delegates to your summits and retreats, and that audience is what sponsors pay to reach, from headline deals near EUR 175k down to smaller placements, alongside tickets, media advertising, retreats and paid research. The audience is the product."
You have no media, events or iGaming experience. Why does that not matter?
Reframe around fast learning and pattern-mapping. "My value is architecting AI systems in complex, serious organisations and learning a domain fast. I have delivered in healthcare and automotive, both regulated and complex. The patterns here (a relationship-driven commercial engine, a content engine, a proprietary data asset) map cleanly to AI. I would spend my first weeks with your commercial and editorial teams learning why deals close and why delegates convert, because the systems must support those realities, not fight them."
What would you build first?
Foundation first, then a revenue-linked lighthouse. "The company brain first: one trusted place where your editorial archive, HubSpot data and market research come together, with a layer that lets any tool or AI read and write safely. Then one lighthouse: an AI sponsor-intelligence assistant that watches the news for buying signals, matches them to the right products, and drafts a personalized first-touch the salesperson refines and sends. Same order as my medical platform, foundation first, then agents."
How do you decide what to automate vs keep human?
A simple, brand-protective test. "I automate the grunt work: research, data hygiene, drafting, matching, summarising. I keep humans on what closes deals and protects the brand: relationships, timing, judgement, editorial independence. If automating a step would cheapen a relationship or risk trust, it stays human, and AI just makes that person faster and better-informed."
Do you know n8n?
Right tool for the job, not "I only code." "I have not run n8n in production, but I know it well: a node-based automation platform, more powerful and self-hostable than Zapier, now with AI and agent nodes. My default is code when I need tight control over reliability and complex logic. But I am a right-tool person. In a lean, fast-moving business like yours, n8n is great for quick integrations and for letting non-technical teams own simple automations. So I would use n8n for quick wins and reserve code for the core platform. I could pick it up in days."
Your three signature stories (90 seconds each)
  • PRISM. Built end to end, solo. Specialist AI agents drive work through planning, building, checking and review, with a human at each gate. Picks the best model per job, survives failures, resilient to a region outage. Proves: hands-on builder + architect.
  • Nova Res RAG. A medical platform where retrieval is the core: answers only from trusted sources, with citations, and a verifier checks every claim. You built the self-scaling ingestion pipeline. Proves: the exact "company brain" capability.
  • Turners ransomware. Led a war room, isolated the server, ran DR (lost ~1 hour of data), root-caused an open port, closed it, drafted the client response. Handled as a process fix, not blame. Proves: calm leadership under pressure.
Questions to ask Nadine (pick 3 to 4)
  • Where do you see AI's first big win: the commercial engine, the editorial engine, or the research asset?
  • As you scale into Brazil and the US, what breaks first without better systems?
  • How do the commercial and editorial teams share knowledge today, centralised or siloed?
  • What does "AI-native" look like to the exec team in 12 months, and what would make this hire a success?
  • How much appetite is there to build a proprietary system versus stitching together tools like Blask or FastTrack?
09

Red lines (repeat before you walk in)

Do not be tech-first

Always connect AI to revenue or relationships. If an answer is only about the technology, reframe it.

Do not replace their people

Amplify salespeople and journalists. Protect editorial independence. AI removes grunt work, not judgement.

Do not fake gambling passion

Sell passion for the systems problem and for helping a challenger out-execute bigger incumbents.

Do not sound rigid or big-bang

Pair "I build in code" with "here is where I would use n8n." Show phased, quick-win thinking.

Culture cues. Their values are collaboration, meritocracy (ideas over hierarchy), innovation, passion and transparency, and "action over promises." Bring shipped examples, admit what you do not know, and lead by teaching.