AI Output

How to Improve AI Output with Help from Your Employees

By tapping into your employees’ experiences, you can improve AI outputs, create new job opportunities, and help your business reach new levels of success.

The businesses that stand out are not the ones using the most AI, but the ones that are using AI the smartest. And the secret weapon to using AI better than the competition?

Your employees.

Key Takeaways

  • AI output is best when employees provide business-specific context, customer insights, and operational knowledge.
  • Employee expertise helps transform generic AI outputs into accurate, unique, and actionable results.
  • Human oversight is essential for catching AI mistakes, inaccuracies, and misleading information.
  • Employees should never share sensitive information with AI tools without clear company guidelines.
  • AI can automate repetitive work while allowing employees to focus on higher-value responsibilities.
  • Businesses are 17.7 times more likely to use AI to assist employees instead of replacing them.

Prompts and Employee Context

AI alone doesn’t understand your business, your customers, or your processes. Your employees do.

When you marry your employees’ experience with AI outputs, you’re going to get more accurate, more useful, and more importantly, more unique results.

Here are some examples:

External Use: Marketing Campaigns

Imagine you want to use AI to create a marketing campaign for a new product.

If you prompt it to create a month-long campaign, it will likely produce something structured, polished, and usable. But there’s a good chance it’ll end up sounding generic.

You don’t want AI output that’s just “usable.” That’s not how you stand out.

Instead, sit a marketing professional down to provide your AI with much-needed context, and suddenly the AI output shifts drastically.

Unlike AI, a marketing employee will know:

  • What your customers respond to.
  • What messaging has worked before.
  • What tone fits your brand.
  • What hasn’t worked in the past.

By bringing their own experience to the table, your employees can turn generic AI outputs into unique and focused results that actually resonate with your customers.

Internal Use: Standard Operating Procedures (SOPs)

Now let’s look at an internal process: an SOP for handling a customer billing dispute.

If you ask AI to write it, again, you’ll get a generic template. Fast? Sure. But not necessarily anything unique to your business or your clients. Again, usable, but not great.

Now bring in a veteran who knows your company processes, and things change considerably.

They’ll know:

  • Which tools your company uses.
  • When escalation is required.
  • How to handle long-term customers vs new ones.
  • When to make exceptions.

With proper context, AI output swaps from generic production to customized workflows that represent your customers and how you do business.

Keep Sensitive Information Out of AI

While context is great, it’s critical that your employees don’t overshare sensitive information with AI. That includes:

  • Private customer information.
  • Financial information.
  • Passwords and login credentials.
  • Anything else you wouldn’t want getting out into the public.

Creating an AI usage policy can help provide a guideline on what your employees can and can’t share. That way, you avoid data exposure or violating any compliance frameworks.

AI Mistakes and Employee Oversight

AI can make mistakes. It can hallucinate facts, interpret data, and overlook crucial details. It takes someone with real-life experience to catch those issues.

An AI-generated financial summary might look fine to an untrained eye, but an accounting team can immediately realize the AI has completely miscalculated a column of numbers.

This can extend to any aspect of your business. AI is really great at making things look good, especially to those without proper experience or training. And that’s exactly why AI output can’t go unchecked.

Fast is great. Wrong is not.

Reskilling Experienced Employees

Just because you’ve implemented AI into your workflows doesn’t mean your employees have to lose their value. Instead, consider putting their expertise to better use in other parts of your business.

This is exactly what happened at IKEA after the rollout of their AI customer service agent “Billy,” which absorbed the workload of 8,500 call-center employees.

Instead of removing those employees, IKEA reskilled them, taking their years of deep product and customer knowledge and transforming them into 1-on-1 interior design consultants. This isn’t unique to IKEA either. A recent analysis of 1,048 AI deployments shows that businesses are 17.7x more likely to use AI to enhance employee productivity instead of outright replacing them.

While you may not have thousands of employees like IKEA, the principle is identical no matter the size of your business: your team has both context and experience that can improve AI outputs while creating opportunities for higher-value work.

And even if employees move into new roles, they can review AI outputs related to their previous responsibilities, helping catch mistakes. They’ll be able to spot issues before anyone else.

AI Isn’t (Always) an Easy Button

You might be thinking: Isn’t AI supposed to make things easier?

And while that is definitely true, it can be misleading. AI is a tool at the end of the day. A powerful one, yes, but still a tool. Think of it like a really complicated hammer. Sure, anyone can swing a hammer, but not everyone knows where to put the nails.

That’s why we challenge you to not just think of how AI can make things easier, but how it can make things better.

Before all that, however, you’ll need to actually get AI working inside your business. And that starts with getting your team on board. It’s critical that you explain to your team what you’re implementing AI for, how you want it to be used, and where your team plays a role. They’re the ones that are going to be using it after all.

Once you get your team ready, proper implementation can start – that’s where we come in.

At The 20 MSP, we help our clients adopt AI across their business, consulting them on what agents make sense, how to implement it, and where things can go wrong. We also help them secure their data and create concrete AI use policies, something not everyone fully understands.

For a monthly flat-rate fee, you get AI expertise, security, and 24/7/365 monitoring without any surprises.

If you’re looking to get AI working for your business, let’s talk.

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About The 20 MSP

As a leading provider of managed IT services, The 20 MSP serves thousands of businesses nationwide, including single and multi-location organizations, delivering white-glove service, secure and streamlined IT infrastructure, and 24/7/365 support. We believe in building lasting relationships with clients founded on trust, communication, and the delivery of high-value services for a fair and predictable price. Our clients’ success is our success, and we are committed to helping each and every organization we serve leverage technology to secure a competitive advantage and achieve new growth.

FAQ

How can my employees help improve AI output?

By using their own experience to provide context that AI doesn’t have. That could be customer preferences, company processes, brand voice, and tone. The more relevant the context, the better the results.

Why does AI need human oversight?

AI can generate inaccurate content or misleading information. Having a human in the process, especially one experienced in the task AI is assisting with, means having a better chance of catching those mistakes.

Can AI replace experienced employees?

AI is great at automating repetitive tasks, but it can’t fully replace your employees’ real-life experience and context. Instead, it can replace the time-consuming, low-value work, allowing your employees to focus on more important projects while guiding AI outputs.

How can I get more out of AI?

Stop looking at AI as an “easy button” or as strictly a cost-saving tool. Businesses that get the best results from AI use it to improve and support the processes they already have, instead of replacing them outright.