playing with a model train set
PHOTO: Georg Eiermann | unsplash

As businesses strive to stay competitive in a global market, they are looking for ways to optimize their operations. One way to do this is by using artificial intelligence (AI) to model the workplace. By understanding how work is done and how teams interact with customers and data, businesses can create new ways of doing things that can have a big impact.

When I say "model the workplace" with AI, there can be connotations of using AI algorithms for hiring, or populating the office with smart devices. And while that all can be done (although I'd encourage you to avoid some of that), where I recommend companies to start is to use AI to understand how their business actually operates.

Using AI and Automation to Discover What You Do All Day

If you ask someone what they do all day, they'll generally give you a high-level overview of their job. But if you ask an AI system to observe them, it will notice and record everything they do. This data can be used to understand how work actually gets done in an organization.

For example, let's say you have a customer service team. You might think they spend most of their time talking to customers on the phone, but an AI system would notice that they also spend a lot of time checking email, looking up information, and entering data into CRM systems.

Systems like Microsoft Power Automate Process Advisor and UiPath Process / Task Miner (disclosure: my firm, Mind Over Machines, is a partner of both), allow you to record, analyze and extract the tasks from someone's work. This data can be used to help optimize the team's work. For example, if the AI system notices that the team spends a lot of time copying data from Excel to System A, you might consider investing in a tool that can automate some of that work. Or if the AI system notices that the team spends a lot of time looking up information, you might consider investing in a chatbot search tool that can help them find information more quickly.

The goal of this activity, having AI analyze the work being done, is to find areas for optimization. This optimization can be in the form of automating tasks, changing processes, or even rethinking how work is being done. Note: Always start any AI/automation task with a deep analysis of the process. There is no sense adding intelligence to a bad process, as you will just end up doing the bad process faster.

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AI for New Ways to Interact With Your Business

Often when AI is discussed with business chatbots comes up as a solution. While chatbots can be a great way to automate customer interactions, they are just one way that AI can be used to interact with your business.

For example, I've seen numerous businesses drown in helpdesk tickets for report customization. To manage this, those businesses need to constantly churn through ever-changing reporting requirements. But, using AI to build natural language query into your reporting platform, I've seen a dramatic drop in custom reporting requests.

Many modern business intelligence platforms, like Microsoft's PowerBI and Tableau, allow you to ask questions of your data using a natural language query, so that employees can explore and discover new information. These queries often come with visualizations of data and filtering capabilities so they can further explore the data based on their question.

This example is a very tangible impact for business. You can measure the impact of using the Q&A capabilities with the reduction in reporting related tickets. Often the impact of AI is seen in time savings, but don't forget other metrics like speed to resolution, and overall reduction in service requests.

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How Do You Start Modeling Your Work?

Do not try to do a big bang change. Instead, I encourage companies to start small. Choose a problem or an opportunity that you want to understand better and form a small team to work on it.

This team should be made up of people from different parts of the organization who are excited about using AI to improve the way work is done. There are many low-code / no-code solutions to help this team quickly try new things. By embracing these low-code solutions, the team can iterate over a solution quickly.

One tool I strongly encourage teams to implement is a "Lessons Learned" list. This is a list where you keep your lessons learned and reference it for future team members. Tracking your lessons learned will help the team remember the lessons they have learned along the way. This list can be as simple as an Excel spreadsheet or an Evernote Notebook.

Using the process recording and task mining tools, have the team members record their work. They should do this for a week or two so that they can get a good understanding of their work. The team should then meet and discuss what they noticed in the recordings. It is critical that you show the team members what the system has discovered. Do not hide anything. Transparency with AI builds trust.

Along with tools and process mining, make sure your team is getting the space and time to brainstorm solutions. A challenge I often see teams face is juggling the competing priorities of innovation and their "day job." Team members are selected for this cross-functional team, but their day job is not changed and so there is no time for experimentation and learning. Make sure to prioritize learning and exploration for these team members. That might be carving out an hour or two a day or Friday afternoons or whatever works best for your team. Make time.

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Time + Space + Problems + Artificial Intelligence

Modeling work with AI is not about trying to replace all the humans. It is about understanding how work is done so that you can optimize it. For example, if you discover a very manual task, maybe there is an opportunity to automate it. If you find a process with too many steps, maybe there are ways to streamline or eliminate some of those steps.

All too often I see businesses get stuck in the "we've always done it this way" mode. Modeling work with AI can help break down those barriers by providing new ways of looking at the data and processes.

If you are a business leader, director or VP-level person wondering how to use artificial intelligence in your business for impact today, start small. Choose a problem or an opportunity that you want to understand better and form a small team. Try different tools and techniques and track your lessons learned. Be transparent with what you are doing and make sure the team has time to experiment. You will be amazed at the impact AI can have on your business.