In that survey, we also asked about how SMBs have implemented it, and the challenges they have experienced.
There is no one clearly dominant implementation practice – SMBs use a variety of strategies to adopt AI. Very small businesses (VSBs, or SMBs with fewer than 20 employees) and small businesses (SBs, with 20 to 99 employees) are both most likely to acquire an AI application from a third party and have it customized by a consultant. Midsized businesses (MBs, with 100 to 500 employees) are most likely to acquire it from a third party and use it off the shelf, followed closely by having it customized. A significant fraction of each size segment acquires an AI application and customizes it with in-house staff, and a roughly the same percent have a solution developed for them by a consultant or freelancer.
No matter how they implemented AI, SMBs face a number of challenges in getting the most from it:
- VSBs are most likely to lack a clear strategy for AI – for example, what exactly they want it to accomplish for their organization, and who will be responsible for it. They are also concerned about its expense – whether the initial fee or customization costs.
- SBs are concerned about the implementation time, and the amount of customization required – which are of course related.
- MBs are also concerned with the customization required; they are equally concerned with the status of their data – for example that it is isolated, siloed, inconsistent or poor quality. This is a very valid concern; AI is only as good as the data it is trained on.
In the coming weeks, we’ll explore more about the hurdles to AI adoption for non-adopters, the prevalence of AI usage policies, and how marketers can improve SMB adoption of and satisfaction with AI.
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