AI has taken the world by storm. It’s a big buzzword, but it’s also a real technology—and it’s doing some amazing things.
That’s great for companies that are already using AI. But what if you’re not sure how to make AI work at your organization? Before you compare solutions like Microsoft Copilot and ChatGPT, you must first understand the usefulness of AI as it applies to your business by uncovering real use cases.
The challenge: Where do we begin with AI for business?
Here at Corsica Technologies, we often talk to people who want to understand whether their organization needs AI. Once they figure out if they could benefit from AI, they need help building a valid business case. Given how new AI technology is, organizations lack the experience to envision it embedded in their operations.
And if you can’t envision AI in real life, then you really can’t select the right tool or make the business case for investing in it.
That’s unfortunate—because there are so many great use cases for AI. Companies leave tons of value on the table when they don’t explore their options. Ultimately, that leads to missed efficiency gains and less differentiation from their competitors.
The key, then, is to define the process for uncovering real usage scenarios at your company and where it will provide the most value.
Corsica’s AI Assessment Framework
In this article, I’ll outline a straightforward process to prove the value of AI to your organization without having to commit to a specific tool or investing in the wrong AI stack—all while getting buy in and building excitement for the impact AI can have on your teams and your work. This is the exact process we use when consulting with a client on Microsoft Copilot.
Here are the steps in the framework:
- Finding (and engaging) your organization’s AI evangelists
- Crowdsourcing real AI use cases with your team
- Refining your AI use cases
- Articulating your vision for AI
1. Finding (and engaging) your organization’s AI evangelists
If you want to succeed with AI, you’ll need to gather a team of passionate evangelists. You want to build broad consensus across the organization to ensure your adoption is a success—and to make sure you get the most out of AI.
What does this look like?
You’ll want to find a few individuals from different parts of the organization who are “early adopters.” We’re looking for people who are naturally passionate about new technologies and new ways of solving problems. These are the people who are ready to question the status quo and drive meaningful change.
Once you have found your early adopters, assemble these individuals into a task force to investigate AI and its use cases for your organization. This is the only way to get that comprehensive, cross-functional view. And you need that view—because AI has so many use cases. You want as many people on board as possible when you go to present the business case. The more AI can do for your organization, the easier it is to justify an investment—and the more impact AI can have on how you operate as a business.
2. Crowdsourcing real AI use cases with your team
It’s not enough to run through a PowerPoint about AI at your company. You need a hands-on workshop—and you need to uncover use cases through crowdsourcing.
The good news: This is easier than you might think.
Get those early adopters in a room and have them open up ChatGPT—or Microsoft Bing Chat, Microsoft Copilot, Google Gemini, or the generative AI tool that is most known by individuals on your team.
Note: If you’re using ChatGPT or a similar public AI tool, make sure your team knows not to enter any sensitive information into a prompt. Anything entered there can emerge in a ChatGPT output—for any user at any time. See our blog post on Microsoft Copilot vs. ChatGPT for more details.
Once people understand the ground rules and guard rails for safe exploration, you can ask them a pointed question: What are some of the most time consuming or mundane tasks that really slow down your day?
Invite them to be honest. Let them know there are no wrong answers.
Maybe they’re stuck writing routine emails to customers. Maybe they have to respond to online chats with users. Maybe they have to produce a written report on some aspect of the business that requires assembling content from many sources.
Whatever those tasks are, you’ll want to show your team how to enter prompts in the AI tool to generate artifacts that can help them with these tasks.
The ideas don’t have to be good. They can be half-baked—whatever pops into their heads. You’ll filter them later. At this stage, you just want people raising their hands and contributing anything that comes to mind.
Of course, you’ll want to make sure everyone understands their role in this exercise. This kind of session is fun, but it’s not just messing around. The exercise needs to produce a deliverable. That deliverable is a list of possible ways you could use AI at your organization to improve operational efficiency and drive value delivery.
3. Refining your AI use cases
Now you have a list of crowdsourced use cases for AI. What do you do with that list?
First off, you’ll want to refine it. Some items may be duplicates. Others may not be that relevant. Not every idea will be applicable at this stage. You want to trim the list and consolidate it so it’s an accurate representation of the real use cases at your company, or at least the ones you want to address first.
Once you have your consolidated list, go back to your early adopter task force and discuss the patterns and common use cases. Ask them to commit to testing these scenarios. For the next week or month, have them experiment and use AI in the situations from the list (within the guardrails outlined).
Ask them to log what they find. Does the tool really excel at certain tasks? Is it not such a good fit for others? You don’t want to lead the witness here. Rather, encourage them to keep a log of how they interact with the tool and what results they get. Encourage them to try different prompts to attempt the same desired outcome to see what phrasing or interaction provides the best results. Even slightly different prompts can provide very different results, so experiment and find what works best.
After that, you want to gather those findings and analyze them. The solid use cases will stand out because the real experience of your team supports them. The weaker scenarios won’t have that support, and you can let those ones go (at least for now). Again, the goal is to identify your top use cases that have real value and impact for your teams.
Once you have that “final” list of rock-solid use cases, it’s time to investigate solutions.
4. Articulating your vision for AI
You’re no longer asking an unfocused question like, “What do we do with AI?” You now have a solid understanding of what value AI can provide for your organization. Plus you have the data to back it up.
With this clarity, you can articulate an intelligent vision for AI within your organization—something like, “AI can do X, Y, and Z for our organization. This will create productivity gains of X work hours for Y individuals. It will create a better customer experience through XYZ.”
It is at this point that you can begin to evaluate AI solutions and find the one that best fits your discovered needs and desired outcomes. Our recommendation is to start by comparing Microsoft Copilot and ChatGPT.
The combination of real-world testing, real-world use cases, and identification of the right AI tooling will allow you to have meaningful conversations with senior leaders at your organization about AI and the impact it can have. As an added bonus, you have built a team of AI evangelists that already know the value of AI and can help drive adoption across your organization to maximize impact.
Have questions? Get Help!
As you can see, the process of building a business case for AI can be fairly involved. Maybe you have the bandwidth to engage that process in-house—or maybe you don’t. Starting your AI journey on the right foot is important for successful implementation of this technology. If you have questions, get help! Find an expert partner to come alongside you and facilitate that process (or help analyze your findings).
AI strategy consulting can deliver the focused process and expertise you need to uncover your use cases and connect them with real AI capabilities. From working with stakeholders to running workshops and producing recommendations, a good consultancy can take on the workload of AI transformation—leaving you free to pursue the essential tasks that already fill your day. It’s a great way to bring the power of AI to your organization.
Want to learn more about AI for business?
Reach out to schedule a consultation with our AI specialists.