By Candace Palangi
Strategic Advisor, Group-Q
Running a pilot program sounds straightforward enough, but we already know how difficult it can be to take the first steps for LSPs looking into AI solutions. Despite the potential upsides of adopting the right tool to improve jammed workflows, LSPs have legitimate concerns about adopting new tech. One way to overcome hesitation is to start with a small, focused pilot.
We have run these pilots from both sides of the table, both as an LSP evaluating the tools for our own internal workflows and as advisors helping technology companies structure their go-to-market initiatives in the language services space. Because of our experience, we’ve helped other LSPs structure their technology evaluation cycles to define and test the tools to meet their needs.
We’ve learned a lot about what works, what needs improvement, and the issues that need to be addressed. Whether you are an LSP looking into testing out a new AI solution or a technology provider fine-tuning your practices to ensure your clients and prospects have success, take note. Here are some do’s and don’ts I’ve personally learned that can make the difference between a pilot that produces meaningful results and one that flops, wasting everyone’s time.
Before the Pilot Begins
✅ Do: Determine who else should be part of the evaluation and get their input.
Identify any other key stakeholders within your organization and bring them into these early conversations. Who else could benefit from these changes, day to day or in the longer term? Bringing in the right people early can help ensure your feedback reflects real usage patterns and builds internal buy-in long before you have to make a buying decision.
✅ Do: Define what success looks like to every stakeholder.
Before you start, you and any other key stakeholders need to agree on the metrics for success. Quality scores, turnaround time, and ease of integration with existing systems are all important benchmarks that need to be identified and measured.
✅ Do: Ask the technology provider for a dedicated support contact.
Too often, we see vendors set up pilot programs and then disappear, assuming everything is running smoothly once their client/prospect logs in. Before you commit to a pilot, confirm that the vendor will assign a specific person to be there should you run into issues or have further questions. Not a help desk or a ticketing system, a real, committed individual who understands your use case and is available to walk through the specifics with you.
✅ Do: Request orientation materials in advance.
There have been a few times when we were speaking with a vendor, and their frontline salesperson wasn’t communicating clearly with the rest of their team, resulting in a trial that didn’t address our actual need. Once I began going through tutorials in advance, I started to catch these things much earlier. Even a short, two-minute walkthrough video can demonstrate the platform’s idiosyncrasies that may or may not be viable for your needs.
❌ Don’t: Accept a login without a plan in place.
Login credentials without context, onboarding, and a structured workflow to follow make for a very weak start to your pilot. Your vendor should spend some time with you and your team, making sure you are comfortable with the tool’s interface and have a solid, running start as things move forward.
❌ Don’t: Begin evaluating before the environment is set up.
I know how hard it is for LSPs to make time for AI pilot programs in the first place. It can be tempting to judge quickly, set it aside, and keep doing things the way you’ve always done things. But unconfigured dashboards, missing documents, and untested integrations cannot paint you a full picture. You’ve come this far. Give the pilot a chance to wow you.
While Your LSP is Running the AI Pilot Program
✅ Do: Test with actual documents, not sample content.
Vendor-provided demo content is (or should be!) optimized to perform well. The only way to know how a tool handles your workflows is to run your reality through it, be it messy, complex, full of outliers, or all of the above.
✅ Do: Document what is not working in real time.
Keep a running log of any friction points, platform errors, and workflow gaps as they occur. It will be worth the extra effort to do this in the moment when you’re summarizing your feedback weeks later. Detailed notes are also useful for the vendor. If they’re in touch with you throughout this process, they are in a good position to correct issues before they become total setbacks.
✅ Do: Speaking of the vendor, loop your contact in when you get stuck.
If you spend more than a few minutes trying to figure out how to complete a basic task in the tool, that’s too long. This could be an onboarding problem, or it could be a design flaw. Escalate it. A good vendor partner wants to know all the places where users lose traction.
❌ Don’t: Rely on one person to carry the entire pilot.
Not only is this unfair to the individual who shoulders the success or failure of the pilot alone, but if they’re out of office, on vacation, or pulled into another project, who is evaluating the program then? It’s always best to build in redundancy from the beginning.
❌ Don’t: Forget to share progress with your wider team and LSP leadership.
It’s useful to schedule periodic check-ins with the wider group of potential users as well as your leadership so that you all remain on the same page. Broader awareness does mean broader input, which can be good and bad. But I’ve found that sometimes the people outside the workflows, who participate in the process the least, are the ones who can spot the most important limitations.
As You Are Wrapping Up the AI Pilot Program
✅ Do: Compare outputs against your previously defined benchmarks.
Here is where you reap the benefits of all that work you did before the pilot began. Go back to the metrics you and the other stakeholders agreed to early on in this process. Did quality scores meet the threshold? Once it was fully configured, did the workflow save you time? Did the tool integrate cleanly with your existing stack? A structured evaluation is the final puzzle piece that brings everything into focus.
✅ Do: Give the vendor specific, documented feedback.
Even if you don’t proceed, a vendor can (and should) learn a lot from your clear, detailed, honest review. The better the vendor understands your needs the better their technologies can become at solving them. Maybe they will become a valuable partner in the future. And if you do move forward, your honest feedback will serve as the foundation for your implementation plan.
✅ Do: Share your findings across your organization.
Win, lose, or draw, running an AI pilot program is an accomplishment. You’ve learned a lot about this tool’s limitations and capabilities, and that’s extremely valuable knowledge for your LSP moving forward. Document it and share it.
❌ Don’t: Leave the feedback cycle on standby, waiting for the vendor to check in.
I’ve found that pilots often end with the best intentions, but no formal close. Carve out the time to complete the feedback cycle, both for your own record-keeping and for the vendor. If the decision to move forward is delayed (as it often is), documenting your experience with the pilot will be critical.
❌ Don’t: Make a decision based on an incomplete pilot.
Lots of things can go wrong during a pilot. Setup can take too long. Your contact at the vendor could go dark. You find out the documents you’re using to test a key feature weren’t truly representative of the work. If you didn’t have the full experience of the AI platform, or even if you suspect you didn’t, speak up. Ask for more time.
What the Pilot Tells You Beyond the Product
How a vendor engages during a pilot is the most reliable indicator of how they will conduct themselves as a long-term partner. Pay attention to how they foster their relationship with you. The vendors who invest in your success during the evaluation, sending orientation materials without prompting, checking in regularly, asking the right questions, chances are, they are in it for the long haul. The ones who hand over login credentials and wait for you to report back are not.
The technology landscape for LSPs is crowded and complex. Thoughtful, well-structured AI pilot programs for LSPs are how we will separate genuine potential from a polished sales pitch and inexperience. It’s worth investing the time to do them properly.
Group-Q assists LSP leaders in structuring and running technology pilots that deliver real answers to both your curiosity and your concerns. If you’re in the middle of an evaluation or trying to figure out where to begin, we’re here. Let’s talk.