Take a structured approach to developing essential AI literacy. Start by piloting AI in an existing workflow. Discover how to identify automation versus AI capabilities in your tech stack.
This post is for the small business owner and for the individual practitioner who wants to understand AI better so they can apply it in their role at work.
The structured approach described here is a way to conduct a pilot project based on one specific use case or process in your workflow. This can help not only orient you to some of AI’s capabilities but may also help you discover how you’ve been benefitting from AI without even knowing it.
Structured for Success
Adopting AI is crucial for staying competitive and driving business growth. Attempting to choose and implement AI tools, however, can quickly become overwhelming. Avoid the frustration of sorting through the options by taking a structured approach that is scaled down and relevant to your role.
AI Opportunities within Existing Workflows
Choose one use case from your existing workflows with the intention of using that use case to pilot AI. Your objective is to figure out where AI is built into your tech stack, whether or not you’re using those, and where you might augment your process with AI.
A good use case for the purpose of piloting AI is a workflow that is repetitive and involves data. It could be something like compiling a periodic report or producing a monthly newsletter, for example. One way to narrow your choices is to pilot AI with a task you don’t necessarily enjoy doing. AI excels at handling monotonous, tedious tasks, potentially freeing you up to do more meaningful work.
Map out the entire workflow, from start to finish. This can be as basic as a sequenced checklist of tasks you do each time you work on the project. Note the types of technology and software you use in your processes. For example, do you use Microsoft Office or apps from the Google suite? Do you run meetings on Zoom while collecting or delivering information? What CRM or project management program do you use during the course of the workflow? All of these solutions are tools that businesses use to operate more efficiently through the use of rules-based automation and intelligent automation. (See downloadable Use Case Model workbook.)
Rules-Based Automation, Intelligent Automation, and AI
The difference between automation and AI can be difficult to distinguish because these terms are often used interchangeably. Rules-based automation is driven by instructions provided by the user. For example, adding a meeting to your calendar and setting it to send you a notification 10 minutes before the meeting is an example of rules-based automation. If you didn’t provide instructions for what to do, when to do it, and how to do it, it wouldn’t be done.
On the other hand, the auto-fill feature of your email program is an example intelligent automation. Typing “What do I” might trigger auto-fill to suggest “have to do?” AI is predicting what you want to say. You didn’t ask it to. You didn’t program it to. It just did it. Intelligent automation is AI that you don’t have to take a course to learn. It’s built-in, ready to make you better at your job.
AI uses Machine Learning (ML) to make your software smarter and able to predict something that could happen next in a sequence. It still requires human intervention, but it moves the process along more efficiently . . . or at least that’s the idea.
An easy way to think about the relationship between automation and AI is to identify where in the sequence human intervention is required.
- Do you need to provide instructions before the action can occur automatically? That is rules-based automation.
- Is the action suggested to you by the AI, and then you decide the next step? That is intelligent automation.
- Do you query or prompt an AI for output? That is (generative) Artificial Intelligence.
Pilot AI on a Small Scale
With a use case in mind and a workflow mapped out that aligns tasks with technologies, you can start to recognize instances of automation and opportunities for using AI. Try to identify which of your technologies use rules-based automation, and which are infused with AI – either intelligent automation, or AI assistants.
Explore each technology in your tech stack for AI features you may not have discovered yet. Do an online search for, “What AI features does [your technology of choice] have?” Or, go to the website for that technology. If it is offering AI features, that news should be easy to find on its homepage or in recent blog posts.
Here are examples of recent searches:
- 14 Canva AI tools to improve your design workflow
- Trello native, AI-powered workdocs
- Supercharge Your Work With HubSpot AI
- AI for Google Calendar
- Zoom’s AI Companion: The Ultimate User’s Handbook
Don’t let this list distract you or send you away from your mission to pilot AI with your unique workflow. For a set period of time – 30, 60, or 90 days – use the workflow for your specific use case as a testing ground to intentionally decipher between automated tasks and AI-enhanced tasks. Explore your options and experiment with AI features in your current tech stack. It’s likely that you are using AI language models such as OpenAI’s ChatGPT or Google’s Gemini (previously, Bard). Note where those tools are used within your workflow, and if they are redundant or complementary to other tools in your tech stack.
AI Literacy is Essential
By now, you have heard concerns about AI replacing people in their jobs. Professionals in the space, however, have the opinion AI won’t replace humans; but humans who use AI will replace humans who don’t.
Whether you are a small business owner or you are waiting for your leadership team to provide guidance, you can and should develop your AI literacy. AI is not going away and will probably continue evolving at an unpredictable pace. A baseline comprehension of what AI is and the ability to recognize it when you encounter it will lead to competency and then mastery, which could put you on the path to maintaining relevance in your profession.