Artificial intelligence (AI) is rapidly becoming more readily available and beginning to change many processes. The progress has caused many managed service providers (MSPs) to explore how their teams could use the technology to improve workflows. If you’re considering that approach, this edition of Tip Tuesday will show you how following some best practices will increase your chances of success.
Set relevant goals and choose appropriate use cases
The first step is to decide how to use AI and what the technology will help you achieve. Some of the most common applications for MSPs are:
- Endpoint security
- Data analysis
- Support ticket resolution
- Customer engagement
Choose trackable metrics and create associated goals after identifying at least one relevant use case. You should ideally select targets that will show measurable progress over time. Then, if you don’t see the expected improvement, that’s a strong sign it might be time to tweak your applications or the goals.
Discussing your hopes with an AI vendor could also show whether they’re realistic. One commercially available solution has enabled some customers to close tickets eight times faster than without artificial intelligence. The same solution has also raised ticket closure rates by 400–500 percent, ensuring more consumers get the proper assistance faster than before.
Hearing about how other buyers have successfully used AI makes setting achievable but challenging goals easier. Consider asking vendors for detailed case studies or statistics to help you make confident judgments and discuss how other similarly sized companies or teams have applied AI to their work. You can then use the answers to shape how AI gets introduced to your employees.
Clarify capabilities and limitations
After selecting an AI solution and setting some goals, it’s time to lay out how your workers will and will not use the technology during a typical workday. Even with progressively more industries using artificial intelligence, some downsides exist.
For example, some responses from AI chatbots are virtually indistinguishable from those humans give. Issues also occur because of built-in biases. After all, people design and test AI tools — those individuals can unintentionally use skewed information or testing methods that make products occasionally unreliable.
Spend time demonstrating real-life examples of how AI works well and when it falls short. This stage of your implementation is also an excellent time to set some internal rules. An example of this would be that you may forbid workers from entering sensitive or confidential data into the interfaces of many popular AI chatbots.
Some developers use all inputted data for training future algorithms, sacrificing details users intended to keep internal. Create policies to protect data privacy while enabling AI usage. That may mean asking all MSP customers to accept that you use artificial intelligence in some internal processes or confirming what happens to data going into such tools.
Create a change management plan
Changes can be challenging for even the workers most eager to embrace them. Doing things differently can cause nervousness, especially for people who must substantially change their current processes. However, individuals typically respond best when their superiors implement new procedures gradually.
Determine a timeline for the progressive rollout of AI-related systems. Set estimated periods for installation, training, testing and other essential steps. Assume you’ll encounter a few setbacks and design your change management plan accordingly.
Another option is selecting a few employees to become early adopters of the technology. Once those workers get acquainted with AI, they’ll be in an excellent position to offer peer support to colleagues. Plus, once staff see people they know and trust who are already using artificial intelligence successfully, they’ll feel more upbeat about learning to do the same.
Show employees how AI can supplement their work
Many workers fear artificial intelligence will take over their jobs. Encouraging them to work with AI systems requires helping them have more balanced perspectives and giving them examples of others in the industry who are using the technology and getting great results.
One business in the MSP industry recently released a tool that works with ChatGPT — the popular generative AI chatbot tool. Representatives reported this decision shortens response times and enhances engagement.
Another AI product marketed to MSPs consolidates approximately eight tools into one platform. Such user-friendly options could streamline workers’ activities by saving them from logging into so many platforms to complete different tasks.
However, since individual experiences differ, you should remain open to feedback. Listen to concerns and meet with people individually to discuss potential methods for better results. Remind them that the best outcomes tend to happen over time.
Consider having periodic team meetings where everyone discusses the new and most effective ways they’ve experimented with AI at work. Those shared insights could urge others to adopt additional methods, too.
Understand AI is an evolving technology
A final thing to remember is AI platforms receive regular updates. Similarly, as more people use the technology at MSPs and elsewhere, they’ll collectively discover how to make the most of it. The frequent updates can make some AI tools temporarily show performance reductions or become slightly more difficult to use. Track how frequently such instances occur and consider reporting them to your tech vendor for guidance.
Staying open-minded about the different ways your MSP may use AI in the future will also prepare workers for potentially using it to improve their work in other ways. Fostering a forward-thinking culture in your workplace will set good examples for everyone to follow.
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