Is Your Managed Services Provider Actually AI-Ready?

Five things to ask a prospective partner before signing on the dotted line.

Your Salesforce investment is only as strong as the team behind it. A managed services partner can help you get more out of the platform over time — optimizing workflows, driving adoption, and keeping pace with Salesforce's continuous innovation. But not every partner is equipped to do that in an AI-driven environment.

Before you sign with a partner — or if you’re reevaluating your current one — asking the right questions can tell you a lot. Here are five to incorporate into your evaluation process.

1. Do they suggest AI use cases to you, or wait for you to bring them?

A managed services partner should not be an order-taker. One of the clearest signals of a high-performing partner is whether they show up with ideas, not just execution. That means proactively identifying where your organization can apply agentic AI, building proof of concepts alongside your team, and iterating based on what actually works in your environment.

If your partner is waiting for you to define the AI roadmap, you have the relationship backwards. The expertise you're paying for should be generating opportunities you didn't know to ask for.

2. Is their day-to-day methodology built around AI, or bolted on top of it?

There's a real difference between a team that merely uses AI tools and one that has completely restructured how it works to get the most out of AI capabilities. A team that uses AI tools can certainly get things done faster. But a team that has built its processes around AI can free its most experienced people for the work that actually moves the business.

An AI-first methodology means repetitive, predictable tasks are absorbed by automation, and senior capacity can be redirected toward complex problems. Before you sign, ask your prospective partner how AI is embedded in their daily execution, not just in their pitch deck.

3. How do they maintain quality throughout the Software Development Lifecycle (SDLC), not just at defined checkpoints?

Traditional quality control in services is checkpoint-based. You build, you review, you move on. The problem is that issues rarely announce themselves at checkpoints.

When AI is woven throughout the development process, quality control becomes continuous rather than episodic. Potential problems get flagged earlier, inconsistencies get caught before they compound, and your environment stays cleaner over time. For organizations managing complex Salesforce implementations, this distinction matters more than most people realize when they're evaluating vendors.

4. How do they incorporate humans in the loop to ensure the right outcome?

This one deserves a direct answer before you sign anything. AI should be enabling your partner's team to do better work, not driving task execution on its own. Every AI-generated output should be reviewed, refined, and owned by a skilled human being before it reaches your environment.

Partners who treat AI as a do-er rather than a helper produce fast, confident, wrong answers. The standard you should hold any managed services provider to is simple: AI should amplify expertise, not substitute for it.

5. How do they manage all the work that surrounds the work?

Requirements documentation. Meeting notes. Action items. Follow-ups. Status updates. In most managed services engagements, this coordination overhead lands in a gray zone between your team and your partner's team, and it quietly consumes time on both sides.

AI-enabled task management closes that gap. When your partner is running these workflows through AI-assisted tooling, you get faster turnaround, cleaner documentation, and more of your partner's attention on the actual work. It sounds like a small thing, but in a long-running engagement, it isn't.

The bottom line

A managed services contract is a significant commitment. The organizations that get the most from it go in knowing what to expect and what to require. These five questions are a useful filter, whether you're evaluating a new partner or reconsidering your current one.

At Thunder, our Amplify managed services practice is built around exactly these principles – AI embedded in how we work, human judgement driving every output, and a proactive approach to optimizing your Salesforce investment over time. If you’re evaluating your options, we’d welcome the conversation. Learn more about Amplify.

‍