The onset of AI in the workplace raises key questions: How can we use artificial intelligence to help us constantly get better at our jobs, rather than just eliminating them? Provided AI will automate the mundane, can it also train staff to rise above those tasks as they disappear?
We don’t view artificial intelligence as a threat that replaces us, but as a multiplier on our personal skills. We realise that not all intelligence is artificial. Dispatchers or transport planners bring a complimentary problem solving approach, and different solution options. An activity as pervasive and diverse as trucking needs all this firepower. A synergy between software and staff offers a richer set of tools for value creation. The best use of AI in enterprise software is to guide workers toward doing their jobs more effectively while they’re doing it. It is a coaching resource, where they retain agency to make meaningful decisions.
By allowing meaningful choices for the users, TNX supports development of personal style, expertise, and ultimately better creative outcomes. As these are incorporated into the data TNX can learn from, everyone benefits.
To imagine how this will play out, logistics leaders should consider the appearance of AI in medicine. Logistics decisions have a similar mix of messy physicality, many data sources, and emphasis on experience. Now look at AI's inroads to x-ray reading, case-history assessing, and even diagnosis. Doctors are giving up tedious and exacting tasks to their AI assistants and emerging happier and more effective as a result. The role of the transport planner (like the doctor) is redefined, not abolished.