The notion of artificial intelligence began around ten years ago as an idea that was being explored in research labs.

Today the ability is a reality and can be used in corporate offices.  However, there are difficulties with its full adoption.  For one, the upfront costs for adoption of AI tools are high and not within the reach of smaller firms.  There is also currently a scarcity of people who can implement the processes at business locations, and more emergent IT expenses have widened the gap of who can achieve IT implementation.  As a result, a variety of players from large technology vendors to startups have begun coming up with tools that allow small businesses the ability to use the technology without the benefit of a data scientist on staff (ref. WSJ).  It can still take time, however, for even the largest of businesses to merge a new technology into standard business practices.  The operational efficiency of AI systems makes their utilization desirable, but, as yet, these are not deemed a high priority by many businesses.  Large agricultural operations have begun using the AI systems in earnest, using their advantages to sort harvests and make smarter on-the-land decisions.  But smaller farm operations, like a 30,000 acre operation in Idaho, say that they don’t have the time or the money to make AI a priority, instead using day laborers to sort out rotten potatoes in the same way that they have for decades.  The primary challenge centers around the complexity that is involved in implementing an AI system and, thereby, adjusting the final process to one that fits the company’s needs.  Those small firms that have begun to adopt AI processes have had to build everything from scratch, one analyst reports. And, even so, the firms working through the adoption process may lack the breadth of data to train and test the systems before they are put into use.  This is because the IT departments of many small companies are understaffed and their professionals are called into service to deal with technical issues considered more pressing, such as updating aging hardware or responding to growing tech requests from end users and the like.  It’s a situation much like the challenge of building strategy systems in companies – when clients tell us that they are too pressed with emerging issues to take the time to look at what needs to be planned for …. dealing with emerging issues.  Only 21% of small businesses are using AI; whereas, 65% of firms with 5,000 employees or more are doing so.  There are a large number of vendors that are attempting to get small businesses to buy into their AI programs, which makes it hard to cut through the noise of vendors touting their wares.  It’s suggested that small businesses make a point of asking what the vendors’ definition of AI is, and whether it matches the needs of the company, in order to avoid vendors selling for the sake of selling, without thought to the end result for a company.

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