OpenAI’s AI-powered chatbot ChatGPT has taken the tech headlines by storm over the last year. It’s impacting everything from how people search for technical solutions to how people think about copyright law. The famous large language model chatbot has even ushered in a new domain of tech: prompt engineering.
Like many other hot tech trends, AI-based tools like ChatGPT are a mix of legitimate opportunities and some over-the-top hype when you drill into the details. The exciting question for MSPs looking to improve their bottom line is how can you use this tool to run a more profitable business?
To help you answer that question, in this article, we’ll take a closer look at ChatGPT and other generative AI platforms, their use cases, and how MSPs are already using them.
When ChatGPT makes sense for MSPs
Every tool you adopt should help you address a business problem. It probably isn’t worth your time and resources if it doesn’t. ChatGPT and generative AI tools are no different.
Of course, you often can’t know if a solution is the right fit for the job until you try it, and that’s where small experiments can have a significant impact. But, there are some rules of thumb you can use to help identify problems where generative AI tools might be a good fit. Let’s look at four indicators that a tool like ChatGPT might be a good solution to a business problem.
- You understand the domain. Under the hood, ChatGPT is powered by a large language model (LLM). LLMs can hallucinate and generate plausible responses that are entirely false. You can’t be an effective gate against false information if you don’t understand the domain. If you do, you can easily sanity check results.
- The impact of being occasionally wrong is low. ChatGPT is far from perfect, and you should expect some errors from time to time. If the impact of an error in a workflow is catastrophic, ChatGPT probably isn’t the right tool for the job.
- The workflow takes up a lot of human time. If humans are spending a lot of time on a workflow, automating it can save money. When you’re looking for tasks to offload to AI, find the tasks that will give you the most bang for your buck by freeing up humans to be more productive.
- You’re not handling sensitive data. Feeding sensitive data into a generative AI platform running on a public cloud could lead to data exposure. Frankly, there is a lot of nuance to this topic, and you can use different tools and settings to mitigate risk, but I wouldn’t recommend starting your AI journey with tests on sensitive data.
The risks of using ChatGPT as an MSP
ChatGPT’s output isn’t as deterministic as traditional MSP automations. Case in point: check out this chat I had using ChatGPT’s GPT-4 model:
An example of ChatGPT getting a math problem wrong.
That error is benign in context. But, in the context of an MSP’s role as a trusted advisor to their clients, mistakes can damage your reputation.
Additionally, with all you could do with AI, getting distracted from what you should do for your business can happen a bit too easily. Time is an MSP’s most valuable resource, so it’s important to remain focused and mindful about how much time and energy you allocate to this (or any) latest tech trend.
How are MSPs using ChatGPT to save money and increase efficiency?
Fortunately, you don’t have to start from scratch if you’re an MSP looking for ways to save money and improve operations with ChatGPT. Many others have experimented with generative AI since OpenAI’s chatbot burst onto the scene.
Below we’ll look at six real-world MSP use cases for ChatGPT.
Automating help desk responses
Help desk ticket handling is a textbook use case for chatbots. Rule-based chatbots were common support tools even before ChatGPT and other AI-powered tools surged in popularity. With ChatGPT, MSPs can automatically respond to help desk tickets in a more conversational manner.
Of course, this can be risky. If a chatbot frustrates your clients, you might lose them. In fact, the top response to this r/msp thread is an MSP claiming they have taken over three clients from an MSP that switched to using AI chatbots. If you’re looking to experiment with this method of saving money with ChatGPT, I recommend you start with helpdesk augmentation, not outright technician replacement.
Developing target personas
The beginning of a chat with ChatGPT on MSP customer personas. You can view the full text of the response here: https://chat.openai.com/share/388a7665-7e74-4976-a6fa-1e8d1bf98713
Marketing to and acquiring the wrong clients is expensive and comes with significant opportunity costs. Sometimes, it might even result in the need to fire a client. Developing your ideal customer personas (ICPs) can help you focus on acquiring and nurturing clients that are aligned with your business goals.
The tricky part is getting the ICPs right. It can be tough to generate ideas and refine them into something useful. ChatGPT can be an excellent assistant here. You can quickly iterate through ideas and have AI do much of the writing work based on your prompts. The conversational nature of ChatGPT makes it easy to flesh out ideas and pivot as you go.
Creating documentation
A chat with ChatGPT about creating an acceptable use policy.
Almost everyone who works in IT agrees documentation is important. Policies, procedures, and knowledge base articles can save time and money. But, writing and maintaining them is tedious. Luckily, ChatGPT can help you get you started with drafting a base document you can modify to meet your specific requirements. Essentially, you can tailor it to be a generic documentation template on steroids.
Translating code
If you have code that isn’t confidential, but you’re struggling to figure out what it does or why it isn’t working, ChatGPT can often quickly analyze and explain it. As a result, you can drastically reduce your troubleshooting and debugging time. You might even be able to add comments or documentation to supplement existing scripts.
Streamlining troubleshooting
Rubber duck problem solving is one of my favorite troubleshooting techniques. With ChatGPT, you can put a new spin on an old classic and problem solve step-by-step with an AI partner.The trick is to avoid letting the AI “lead” too much. If you keep your critical thinking hat on and focus on the problem, chatting with ChatGPT can be similar to having a patient colleague discuss it with you.
Creating marketing content
Many content creators are turning to AI tools to generate or augment their online content. In the proper context, AI tools like ChatGPT can streamline content creation. Be careful if you try this one. It’s popular, but it is a slippery slope. AI can quickly generate a lot of content, but it isn’t always quality content. Make sure whatever client-facing content you publish — AI-generated or otherwise — is worthy of representing your brand.
Final thoughts: Experiment, learn, repeat
Reinforcement learning isn’t just for AI. Feedback loops are a great way for us humans to learn how to lean into what works too. MSPs who want to determine if ChatGPT and other generative AI tools are right for them can use that idea to make a reasonable decision. The model is straightforward:
- Experiment with the tool as a solution to a business problem
- Check what works and what doesn’t
- Adapt based on what you learned
- Repeat
This empirical approach to AI can help you add some perspective to the hype and hone in on its value in your MSP business.
If you’re interested in exploring other topics related to how you can run a profitable MSP business, check out our MSP blog for more free resources!
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