By Ronnie Hamilton, Pre-Sales Director, Climb 

The industry’s answer to AI failure is to move faster. From where I sit, that’s the cause, not the cure. 

The channel has spent the past few years getting good at one half of the AI problem: working out which vendors are worth selling. Distributors are overwhelmed by the number of vendors available to them: sorting the contenders from the pretenders, assembling curated portfolios. That work is real, and we do it too. But it is the easy half. It establishes that a vendor is a real company with a channel programme behind it. It does not answer the question the customer cares about: whether the product will work for them. 

This answer tends to come later, in the proof of concept, where a vendor’s demo meets the customer’s own data and where pre-sales either earns the recommendation or finds the reason not to make it. The gap between what a product demonstrates and what it deploys has always existed; AI has widened it sharply. The industry’s answer is to move faster, certain the window is closing. That answer is the problem. 

The pressure 

The channel is working to a deadline. When cloud arrived, partners had three to five years to retrain, hire and rebuild how they sold around it. Futurum reckons AI allows for 12 to 18 months, because we’ve reached a change where the technology is changing by the week.  

Customers are applying their own version of the same pressure: in research we ran across 600 enterprise decision-makers in the UK, Ireland and Germany, 32% expect a return on AI within one to six months, rising to 40% in Ireland. And the channel is strangely absent while all this is going on: 47% of those organisations are not engaging resellers or vendors on AI at all, even as 55% plan to expand their use of it. 

The effect on a partner is obvious. There is pressure to have an AI answer and pressure to have it now. The backdrop is a market in which every vendor’s deck leads with AI and every demo is impressive. The path of least resistance is to pick quickly and recommend quickly. This is a trap. 

The trap 

AI is uniquely unsuited to judgement by demo. A demo runs on clean, curated data in conditions the vendor controls. A customer’s environment is none of those things because their data is fragmented, access is governed, and edge cases are real. The danger is that the product still installs perfectly well in this environment. The licence goes live, the pilot is written up as a success, and the failure is invisible at the point of sale. It only announces itself months later, when the customer asks what they actually got. 

The scale of this mistake is already reflected in the data. Over half (53.5%) of the organisations we surveyed place themselves in what we called the AI Gap: with tools in use but no value coming back. The confidence problem sits right alongside it: 61% of organisations describe AI as well understood and implemented in their organisation, while just 49.2% have trained fewer than half their staff to use it. The belief that AI is working is running well ahead of the evidence that it is. When that happens, the customer’s disappointment is naturally going to be directed at the partner who recommended the product rather than the vendor who built it.  

The discipline 

The answer, then, is not to move faster. It is to validate before recommending – and validation is not the same discipline as vetting. Vetting asks whether a vendor is sound. Validation asks whether this product does what it claims on this customer’s data, against this customer’s constraints, for the use case the customer actually has. That work happens in the proof of concept, it takes the time it takes, and it is the one stage that cannot be compressed. 

It is also the stage a self-serve marketplace cannot perform, and it’s the question a vendor, in the moment of a deal, is not placed to answer. It needs someone sitting between the two who has run the same product through enough real environments to know where it tends to break: someone who will tell a partner a product is not right for their customer even when a quick yes would be easier. This is the part of distribution that has nothing to do with moving stock. It is the judgement about whether a product fits, whether the use case holds, and whether the risk is worth carrying – made for the long-term success of the deployment rather than the speed of the sale. 

And it is not at odds with what the vendor wants. No vendor is served by a sale that fails in production: a deployment that stalls is a renewal lost and a reputation dented in a market that talks. The distributor that thinks past the transaction, and grounds what it carries in knowing where it works and where it does not, is looking after the partner, the customer and the vendor at the same time. A partner is better served by pre-sales that tests a product honestly and sometimes comes back with no than by a fast yes that unravels in deployment. 

None of this argues against the 12-to-18-month window. The window is real, and so is the demand behind it. The argument is about what the channel does inside it. The vendors will always move faster than distribution, and the marketplaces faster still; speed was never going to be the channel’s advantage, and neither was the size of the catalogue. What the channel can still offer, when AI products demo better than they deploy and customers are in no position to tell the difference, is proof.  

The partners who build their AI practice on that principle will be the ones whose customers are still listening three years from now. 

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If you want to remove the risk from your AI recommendations, let’s talk.

I work with partners to validate AI solutions before they go to market, making sure what demos well also delivers in the real world.

👉 Start a conversation with me and build your AI practice on proof, not assumption. Drop me an email on RHamilton@climbcs.ie or connect with me directly on LinkedIn.