Once again, I awake today with thoughts of automation, well actually, desperation. When I take a step back and gaze upon the AI movement and specifically the Generative AI (GAI) movement, it looks like a zombie horde that just came upon a group of living brain tissue. Why are people chasing it with such zeal? In this particular case, I’m not even focusing the money chasing AI, they’re obvious in their goals and they chase the zombie hordes. Maybe a better analogy is they’re injury lawyers following a group of speeding vehicles on a snowy highway. I’m also not talking about the developers and product companies, because they too are merely attempting to be relevant in a shifting market. No, I’m talking about the direct consumers of the technology.

GAI is being embraced by workers across the enterprise in accounting, marketing, human resources, IT, and legal—I call these business-line workers—because GAI offers support where most companies cannot afford it, automating the mundane and unleashing creative productivity. It’s not a perfect tool and it quite often makes mistakes, and that’s okay. It’s ability to alleviate that pain of expression or time-consuming monotonous tasks far outweighs the fact it lacks exactness.

Hand it 5,000-line items and ask why it’s not reconciling. Ask for 10 ideas to write about in a particular topic area. Ask it to write a 300-word article on one of the topics it just recommended. Ask it to write code to handle something more complex; it not only will write it, but it will deploy and run it for you in the cloud as well. Ask it to create a visual to represent 300 words you just produced. Those who have spent a day staring at a blank Word document will tell you at the end of the day, GAI may still not put exactly what the author wants on that blank document, but it feels like forward progress has been made. It charges the neurons and generates the human intellect to act on the information provided.

But, back to my comment about desperation. Workers around the world spend thousands of hours and billions of dollars on dynamic requests. This is unplanned work that is required to address confusion and misunderstandings about data that was produced, and outputs of processes already run. It is soul-sucking work, but critical to the business. There are no IT resources that will jump in and build an automation to assist with this activity; especially if it’s a one-off. In the past, it’s been faster for the individual to just complete the task than spend time attempting to automate. But, with GAI and the ability to use natural language to express what they need done, it takes minimal effort to first try AI before just diving in and doing the work.

The best tool the industry has had prior to widespread availability of GAI was Robotic Process Automation (RPA) or low/no-code programming tools. In relation to GAI, let me describe RPA and no-code programming. If you’re in the jungle and you get a gash in your leg with your only hope for survival being to use a sewing kit you brought to stitch up yourself, that would be RPA/no-code for business-line workers. GAI is liquid stitches.

Now, for those that don’t know me, I cannot be accused of being a fanboi of silver-bullet solutions and emerging technologies in general. Part of the reputation I have developed is highlighting the pragmatic aspects of adopting any technology. And, while I believe there are significant issues with general availability of GAI, I am not Daryl from Walking Dead willing to stand with my bow and arrow in front of the oncoming zombie horde in this particular case.  It is a game changer in the field of automation.