AI Consulting
AI strategy your leadership can act on, not just nod along to.
We work directly with management to cut through the noise — what AI can do for your business, what it can't, and what to do first. No jargon, no vendor pitch.
Why strategy first
Adopting AI is easy. Getting value from it isn't.
McKinsey found that 88% of organizations now use AI in at least one function — but only about 6% report a material impact on earnings. The gap is rarely the technology; it's choosing the right problems and sequencing them. Gartner expects roughly 30% of generative-AI projects to be abandoned after proof of concept by the end of 2025, most often for unclear business value.
That's what consulting is for: deciding what's worth doing, what to skip, and what to do first — before you commit budget or headcount.
Who it's for
Executives and leadership teams who need a clear-eyed view of AI before they commit budget or headcount — CEOs, CTOs, COOs, and functional leads deciding where AI fits.
What we cover
Concrete, scoped conversations — not a generic AI-101 deck.
- AI strategy — where AI can move the needle in your business, and where it can't.
- Readiness assessment — data, systems, and team maturity for AI adoption.
- Build-vs-buy — when to use existing tools versus build custom.
- Roadmap — a sequenced plan with owners and milestones, not a wish list.
How engagements work
Three shapes, depending on what you need.
Advisory session
A single working session to unblock a specific decision — a tool choice, a vendor evaluation, a go/no-go call.
Assessment
A structured review of your data, systems, and team readiness, with written findings and recommendations.
Ongoing advisory
A standing arrangement — regular sessions as you execute your AI roadmap, adjusting as priorities shift.
When the roadmap points at something worth building, the practice builds it — see how projects run.
Delivered in Hebrew or English.
Questions
Before you book, the usual questions.
What does a consulting engagement actually produce?
A decision you can act on, and usually something written to back it — a readiness assessment, a build-vs-buy recommendation, or a sequenced roadmap with owners and milestones. Not a generic AI-101 deck, and not a pile of slides you'll never open again.
How is this different from a generic "AI 101" briefing?
Every conversation is scoped to your business — your data, your systems, the decisions in front of your leadership. We cover what AI can and can't do for you specifically, then what to do first. General "state of AI" talks are what workshops and lectures are for.
Do we need clean data or infrastructure before you can help?
No. A readiness assessment — an honest read on your data, systems, and team — is often the first thing we do, precisely so you invest where it will pay off. Poor data quality is one of the top reasons Gartner expects 30% of generative-AI projects to be abandoned after proof of concept.
How do you approach build-vs-buy?
Case by case, against your actual constraints — cost, timeline, data sensitivity, and how core the capability is to your business. Sometimes an existing tool is the right call; sometimes a scoped build is. The point is to decide deliberately, not default to whichever is louder in the market.
Who from our side needs to be in the room?
The people who own the decision — usually a CEO, CTO, COO, or the functional lead whose area AI would touch. Engagements are sized from a single decision-maker to a full leadership team. If you're weighing where AI fits before committing budget, that's the right group to start with.
Ready to talk through your AI decisions?
Book an intro call and we'll figure out which engagement shape fits.
Book an intro call