We get it – “process” doesn’t scream excitement.
But killer AI needs well-designed processes to maximize impact. These clear processes align AI initiatives to business goals, enable smooth integration, provide efficiency gains, and allow for responsible AI scaling.
With effective AI deployment, a business’s future is intelligent, adaptive, and driven by data. But with all this promise, there’s no guarantee that the AI Business Strategy will be successful unless you have a plan and framework to make the transition from the existing business’s paradigm seamless and tailored to unique organizational needs.
The macro plan can fall apart in the micro-operations. Or, as you may have heard, “The devil is in the details.”
In this lesson, you’ll learn our exact recipe for getting the nuts and bolts of an AI implementation right, all the way down to the individual workflows for the roles in the organization.
With the support of the AI Change Coalition, it will be easy to get your process efforts underway. The main contributors from the Coalition who will participate in the process phase are:
Once you have identified who will drive the process development, the fun part can begin – crafting AI-powered processes tailored to the AI Business Strategy and the company’s specific needs.
Many established companies simply don’t have documented processes in place. This is where “process mining” comes in. Process mining is analyzing data from existing systems to understand how work currently gets done to identify optimization opportunities.
Using the results from the Impact Assessment we performed on the individual roles in the new org chart, work with the Coalition to identify and prioritize which SOPs/workflows you should focus on.
The decision on which processes to focus on first should be based on the economic contribution of the process, the processes that are the most significant pain points for the company, and existing processes leading to the most constraints downstream from that process.
Once your list is established, it’s time to evaluate the individual processes on the list.
We do that by having the team leads work with the individuals responsible for executing the SOP/workflow. Here are some key questions they should ask workflow/process users to help discover the granular steps:
The goal is to uncover every step from the workflow user’s perspective, down to the micro-details, to fully map the as-is process before improving it. This granular insight allows you to identify optimization opportunities in the next step in the process.
Here are some of our best practices for documenting the process mining activities:
The goal is to capture the complete picture from multiple angles. Detailed notes supplemented by visual maps, actual usage recordings, and system artifacts will help ensure the process is fully documented.
Process mapping and workflow design is the art and science of translating strategy into actionable steps, and that’s the next step in our process.
Now that we have the answers to the questions from the process mining conversations, you’ll want to move into documenting those processes in a tutorial or instructional guide on executing the processes as they are currently defined.
Even though we will be optimizing the processes to include automation, human augmentation, or pure AI, we need to document the baseline workflow in case we need to revert to the original process if there’s an issue with the AI-powered process being developed at this phase.
Here are the steps you will follow to map the processes thoroughly:
1. Create an end-to-end process map visualizing all steps, systems, decision points, and pain points discovered. The visual of the process helps future workflow users understand all process steps. We use LucidChart, but there are many other tools you can use for creating the visual process map.
2. Include a list of the individuals or roles responsible, accountable, consulted, and informed at each step.
3. Catalog redundancies, bottlenecks, or unnecessary steps that you discovered in the Process Mining step.
4. In these process maps you’re building, link to recorded videos, screenshots, and other resources captured during Process Mining.
5. List out all inputs, outputs, and data flows for the process.
6. Identify the metrics you’ll want to monitor to know how the optimized process improved the workflow.
7. Catalog all requirements needed for the process, such as integrations, training, and system changes.
8. To go the extra mile, build a digital glossary of terms, acronyms, and systems referenced.
9. Once captured, store this detailed documentation in a collaborative hub like a wiki or shared folder. Set permissions that allow user comments on documentation to incorporate feedback directly into the wiki or shared folder.
Now that the existing processes have been documented, it’s time to work your magic and optimize them for greater efficiency, output, and results.
Using the analysis conducted during the Impact Assessment that was performed on the new org chart, it is time to start plugging in solutions.
If you recall, in the assessment, we looked for areas where we predicted automation, human augmentation, or pure AI could be applied to a role.
With the existing processes mapped and turned into visual representations, you will review each process step and identify the exact step(s) where you can apply AI.
Having the baseline process already documented makes this step simple for you to complete.
In the new, optimized process, you will replace steps in the baseline process that were exclusively human-powered and can now be supported by AI, listing the specific tools for the job.
Once you have the new steps defined, you’ll want to note where the tool configuration will be required from the tech team to make the tool ready for application into the documented workflow.
Once you have confirmed that the tools are ready for application, it will be time to train the workflow user to use that tool in the AI-powered process that replaces the baseline process. If no training exists, record the training you preset and include links to this training in the process map.
We haven’t discussed particular tools to use throughout this process, though many exist. And more “AI-driven” tools for process documentation are coming to market regularly.
We have included some of our favorite tools in the Additional Resources section of this lesson, so make sure you review those suggestions if you don’t have a favorite tool you already use.
In summary, well-designed processes are crucial for executing an AI strategy and integrating solutions into business workflows.
The key points covered are:
By following this systematic approach of first understanding current processes through discovery, then mapping and optimizing workflows, you can seamlessly incorporate AI at the granular level to align with the bigger strategic goals.
The key is documenting processes thoroughly, analyzing pain points, and being intentional about where and how AI can provide efficiency gains or automation.
With redesigned workflows powered by the right AI solutions, businesses can unlock productivity, scale intelligently, and deliver exceptional customer and employee experiences.
But remember, processes must evolve continually, so treat optimization as an ongoing journey.
With the proper framework, your AI-powered processes will drive growth, innovation, and competitive advantage.