A quote for an AI system is sitting on your desk. Maybe it says NIS 80,000, maybe half a million, and you have no way of knowing whether either number is fair, because no serious player in Israel publishes a price list. You asked a colleague and he got a completely different number for a similar job. That is not sloppiness. Opacity is the business model in this market. So here are the real numbers, from the global benchmarks down to what actually happens here.
The Global Numbers: What Each Stage Costs
In the American market, where the data is far more visible, clear anchors have formed for every stage of an AI project:
Proof of concept (PoC): $15,000 to $40,000. A small build that proves the idea works on your data, without full integration.
Pilot: $50,000 to $250,000, usually over 8 to 16 weeks. This is where the system meets real users and a real process.
Going to production: 2.5 to 4 times the cost of the pilot. This is the number you most need up front, because most quotes price the pilot alone and the rest of the bill lands afterwards.
Assessment and strategy: An organizational readiness assessment runs $25,000 to $75,000, and in organizations of a thousand employees or more it reaches $90,000 to $200,000.
Ongoing retainer: $2,000 to $15,000 a month for standard advisory work, and up to $50,000 a month in a deep partnership.
If you have ever wondered what sits behind a quote from one of the big consulting firms: US government procurement data (GSA) prices an hour of a senior partner at a leading global firm at $1,100 to $1,200. One hour.
One more anchor worth knowing is the fractional CAIO, an outsourced chief AI officer who works with the organization part-time on a fixed basis. Globally the model is priced at $5,000 to $30,000 a month, against $400,000 to $1.2 million a year to hire that executive as a full-time employee. The standard American structure is a 90-day opening sprint (roadmap, governance, work plan) followed by a monthly retainer, with a discount of 15 to 20 percent customary on an annual commitment.
And in Israel? Two Markets With a Chasm in Between
In Israel the only prices in the open belong to the small-business end of the market: an AI workshop at NIS 3,000 to NIS 12,000, an advisory retainer at NIS 3,500 to NIS 8,500 a month. Those numbers sit 5 to 15 times below their American equivalents, and they serve an entirely different market.
At the other end are the big firms, with projects running from hundreds of thousands of shekels into the millions and no public price list of any kind. Between the two ends a hole opens up: one well-defined project taken all the way to production, with measurement, in the range of NIS 100,000 to NIS 300,000. And the absence of a published Israeli benchmark has one practical consequence for you as a buyer: the first quote placed on your desk sets the anchor for the entire negotiation. Compare it against the global numbers above before you answer it.
Then there is the figure that should turn on a red light. According to the State Comptroller report of June 2026, 68% of AI projects in Israeli organizations are stuck at the pilot stage, and only 32% were actually deployed. An MIT study found the same picture globally: 95% of pilots produce no measurable impact on the bottom line. Put plainly, most of the money paid for AI today buys presentations and pilots, not working systems.
How to Read a Quote Without Getting Caught
Four questions worth real money to you:
- What happens after the pilot? Insist on seeing the cost of going to production in writing, up front. If it is not there, multiply the quote by 3 in your head.
- What is the metric, and who signs off on it? Success has to be a business number (time to handle an inquiry, cost of processing an invoice, share of inquiries closed automatically), fixed before the work starts, not after.
- Who owns the code and the data? If the answer comes back mumbled, you are buying dependency, not an asset.
- How many people are actually working on this? Much of the spread between quotes is head-office overhead, not work on your system.
One more principle from the global research: 73% of buyers prefer outcome-based pricing to hourly billing. A vendor willing to tie his fee to the result believes in what he is building.
Where I Know These Numbers From
I came to this field from an unusual direction: more than 20 years as a CEO and in senior management, and over my career I have personally built systems that are running in production today, with AI as the working partner - full web platforms, voice bots, reporting automations and payment flows. I know how many working hours every stage takes.
Have a quote you are unsure about? Send it over. I will take it apart with you against the benchmarks, no strings attached. And if you want to see what a system that actually runs in production looks like, ask me for a demo.
