AI Dividend interviews your organisation, thirty minutes, no prep, scores what comes back, and turns the strongest ideas into costed business cases in real approval. Board-ready roadmap in about six weeks. One enterprise engagement turned 200 ideas from 150 employees into six funded pilots, $6.2 million in projected first-year value.
One of three Otinga programmes, with AI Strategy and AI Hackathons, across twelve enterprise clients.
Your engineers know where the client journey breaks. That knowledge lives in a teams thread, not a system. 88% of organisations use AI somewhere, yet only 39% see EBIT impact, mostly under 5% (McKinsey, State of AI 2025). The gap: no route from knowledge to a funded number.
An idea reaches your CFO’s desk as bullet points and a hopeful adjective. No sizing, no payback period, so finance says no, rightly. Companies scrapping most AI initiatives pre-production rose 17% to 42% in a year (S&P Global, 2024).
Ask three executives who owns AI here, you get three answers, plus a pilot nobody mentioned. Only a third of organisations have begun scaling AI enterprise-wide; roughly 6% qualify as high performers (McKinsey, State of AI 2025). That visibility gap is what AI Dividend closes.
The ideas were never the constraint. The route from idea to funded work was.
AI-led interviews, one question: what slows you down on a Tuesday?
Scored on feasibility, value, strategic fit, complexity. Weak ideas fall away early.
Qualified ideas become business cases: sized, costed, return and risk, moving through real approval.
Coming, live, and parked work, one roadmap. Duplicate builds surface before double funding.
Promised value set against actual return, alongside governance on every AI system.
Not hypothetical
One Fortune 100 engagement: 150-plus employees, 200 ideas, 87 surfaced across 12 units, six funded pilots worth $6.2 million projected first-year value. A healthcare group built a $12 million projected pipeline in one quarter. Neither client can be named; both figures stand as given.
Agree units in scope, what we ask, who gets interviewed.
Interviews run in parallel across scoped units. No login or AI knowledge needed.
Everything captured is scored and ranked.
Fundable opportunities, written up, moved through approval.
Funded, shipped, and returned, against what was promised. Most programmes skip this.
Plenty of AI platforms are a slide deck and a promise. Here is where AI Dividend stands.
The AI-led discovery interview, the business case workflow with its full approval states, and your organisational maturity score.
Automated scoring at scale, executive dashboards, PII redaction in transcripts, and connectors for Slack, Teams, Jira and ServiceNow. Today, data comes out through a GraphQL export that your team can point at whatever they already use.
If a number or a screen matters to your decision, ask us where it came from. We’ll tell you plainly, including when the honest answer is that we can’t substantiate it yet. We’ll walk your architects through the built-versus-roadmap detail and a data-flow diagram before you commit to anything.
Both, delivered as one. Route through procurement as professional services.
Speed: a large firm interviews a sample over months for a deck; we interview everyone in weeks for costed cases in approval.
A thirty minute, no pitch conversation. If a fit, the next scopes units, interviewees, and board needs.
Today, via GraphQL export. Connectors (Slack, Teams, Jira, ServiceNow) are roadmap, not live.
We walk your architects through the data flow and access, security people in the room.
One unit is fine. Pick one visible enough that a result changes minds elsewhere.
