Today’s AI may be able to pass the Turing test, but I think we can all agree that doesn’t make it human. AI is a tool—a powerful one, but a tool nonetheless. And just like any tool, it can make our work easier, but it can’t do it for us. A sewing machine takes care of the task of stitching, but it can’t make a quilt without a human behind the wheel, guiding the machine and overseeing the larger process: choosing a design, acquiring fabric, placing the pieces where they’re meant to go in the pattern.
If AI isn’t part of a well-orchestrated process, it’s not going to deliver the benefits you’re hoping for. So what does it look like for AI and process to work together in harmony? Let’s dive into it.
The best way to describe the future of AI is with these two words: mixed autonomy. AI can handle some things independently, but humans need to stay involved to handle nuance, make decisions, and keep everything on track toward big picture goals. The work between the two will be a partnership: AI will write, and people will edit. AI will propose, and people will decide.
Picture AI as a co-pilot, capable of handling certain tasks but still reliant on human oversight. Think about how AI is not quite ready to drive your car without your vigilant supervision, but AI features are significantly improving vehicle safety. Like I said, it’s a partnership.
Some people worry that AI will replace human jobs. That just isn’t the case, and here are three reasons why.
So AI won’t replace human workers. But it will accelerate them in a way that will make anyone not using AI likely to fall behind.
So yes, it’s a partnership, the interactions between AI and humans. Not a competition. And the backbone of this partnership is process. Process, in this context, serves as the conduit that operationalizes AI, transforming insights into actionable outcomes. Without the scaffolding of process, the potential of AI remains largely untapped.
In any collaboration, work must be routed to and from the involved parties. This is true for when AI works with humans as well. Tasks and notifications bounce back and forth between people, AI, and other automation technologies, and if the communication process isn’t clear and effective, you’ll run into issues that can slow or even stall your progress.
Sorting, routing, prioritizing, evaluating—all these orchestration tasks have to happen to keep the AI-human workflow moving smoothly. The easiest and most effective way to do this is with an AI process platform.
The easiest way to make sure your AI is supported by strong processes is by having process orchestration built in to your AI tool. That’s what an AI process platform gives you. Here’s an example:
The Appian Platform comes with AI skills that can be trained by business users with low-code to take on tasks like classifying and summarizing documents and extracting data. These skills are particularly useful for organizations that handle a lot of documentation for things like invoice processing, employee or customer onboarding, insurance claims processing, patient intake, and more.
Since the AI skills are built in to the Appian Platform, once they’re trained they can be easily added to existing automated workflows by just dragging and dropping them into a visual process model. Ta-da! It couldn’t be easier to seamlessly incorporate AI into your organizational processes.
You may have heard it said that your AI is only as good as your data. And that’s true. But your processes are also only as good as your data. So if process is the backbone of good AI, data is the lifeblood.
AI models need to be trained on a very large volume of data. And in order to train on your data, the AI needs to be able to access it. So if your process for managing data involves lots of disjointed spreadsheets and emails, that’s going to be a problem.
Here’s where an AI process platform comes into play once again. A strong process platform will be equipped with a data fabric. A data fabric is a semantic layer that sits on top of all your data sources and connects them automatically into one unified virtual space. That way, your AI can access your data wherever it lives without you having to migrate, manually consolidate data sources, or invest in an expensive rip-and-replace solution for data management. With a data fabric, your data can stay where it is—you just get to access it much more easily.
And if data security is important to you, look for a vendor that takes a private AI approach. Private AI means your data stays yours and won’t be used to train the vendor’s models that other companies, potentially competitors, also use.
[Find out more about the benefits of a private AI approach with Implementing Private AI: A Practical Approach.]
The relationship between humans, AI, and process is one of symbiosis. As we navigate through the age of mixed autonomy, embracing the collaborative potential of humans and AI through robust processes is key to unlocking new frontiers of innovation and progress. Process is king—everything else is just working to serve its success.
[Keep up with the rapid pace of AI. Set your expectations for this year and learn how to stay competitive by reading 8 AI Experts on the Future of Enterprise AI.]