Ford Motor Company recently made headlines when it announced that it had trained over 1,000 employees on its artificial intelligence platforms. The large number is undoubtedly impressive, but more interesting is the fact that these 1,000 employees were vehicle engineers, supply chain managers, designers and other employees outside of the company’s IT department.
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Ford will still have teams of data scientists and technicians working on complex AI problems like self-driving vehicles, with the 1,000+ AI-trained individuals tackling issues within their areas of expertise. According to Ford, these individuals will be doing everything from optimizing supply chains that remain unstable to creating quieter air ducts for vehicle heating and cooling systems.
Programs like this seem intuitive and somewhat obvious yet are surprisingly lacking in most IT shops. Traditionally, IT fields a team of business analysts to understand a business process, design a system to support or modify that process, and then communicate with the technicians who build the system. While familiar, this approach makes an interesting and often invalid assumption: it’s easier for a technical individual to learn business content than it is for a businessperson to learn technical content.
This approach also requires significant, high-value resources from IT. Even the best and most capable technicians can only support a limited number of projects, and in the current job market, talent has become a significant constraint.
Contrast this approach with providing technical knowledge to those outside IT, a movement often referred to as democratizing technology. A significant investment is required to provide the skills and training to those non-IT individuals, which appears as a stumbling block to many organizations. Yet consider for a moment that you’re already paying to “train” your IT staff in various business processes. This task reduces the productivity of the non-IT people doing the training that’s usually disguised as a discovery or analysis process. Furthermore, it’s often throwaway knowledge after your analyst completes a project and moves on to the next one.
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Once adequately trained, any incremental costs are usually the easiest to scale and come in the form of more technology licenses. It’s hard to address a shortage in data scientists, but it’s barely an afternoon’s work to acquire more licenses for your pool of “citizen technicians” outside IT.
Depending on the application, these individuals may be better equipped to deploy your shop’s technology than IT resources. They have years or even decades of experience in the content and are also close enough to the problem that they will naturally determine which scope and functionality are most important, avoiding the usual infighting between IT and business units competing for resources.
You can also use this shift to clear IT’s project backlog. Once the investments in training and tools have been made, it’s easy to imagine your citizen technicians tackling many of their departments’ projects before they wind up as yet another competing priority in your backlog. Unlike an analyst’s disposable knowledge, the citizen technician now has a durable skill that increases in value over time.
Don’t fear the shadow (IT)
The biggest objection to creating citizen technicians is often that this will create an explosion of shadow IT, systems and technologies that are outside the purview of corporate IT. The obvious fear is that when these unsanctioned systems fail, IT will be called to the rescue and ultimately have more work to clean up the shadow technology than if IT had built it in the first place.
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This is not an unreasonable concern, yet most of the risk of shadow IT comes from the fact that it gets created without guidance or consultation with IT, often as a result of frustrations with the speed or flexibility of internal IT. If you act thoughtfully and in partnership with other business units in creating your cadre of citizen technologists, you can set appropriate policies and guardrails on what’s acceptable and where to go with questions.
Most companies have some experience with creating citizen technologists by equipping business users with reporting and analytics tools. Look for examples that already exist within your organization, and identify how to improve the training, management and support of what were likely ad-hoc exercises and successes hidden in plain sight.
Start small when creating citizen technologists
As with all new efforts, there’s no shame in starting small. A company like Ford employs almost 200,000 people worldwide, so while 1,000 AI-trained individuals sounds impressive, it’s less than 1% of the entire workforce. There’s no shame in creating a pilot program with a handful of people, and you likely already have a business unit that’s requested a new tool or technology. Rather than having IT lead the charge in acquiring training and deploying analysts, consider experimenting with creating citizen technologists in that division.
Determine what kind of problems they’ll solve with the new technology, and if they’re relatively confined to that business unit, it’s likely a great candidate for an experiment. Train your new non-IT technicians and provide a point of contact within IT who has or is willing to acquire experience with the technology. Assess how these non-IT techs perform and whether this new mode of working creates a stronger impression of your IT shop. You may be surprised that for less effort and ongoing involvement from IT, you’re able to create better and faster results that have the added benefit of making IT look like superheroes fighting for freedom and empowerment, at least when it comes to technology!