15 Questions to Ask Before Selecting an AI Implementation Partner

How to use this guide

A demo can show that a tool works in a controlled setting. It cannot, by itself, show that a solution fits your processes, systems, people, risks, or business objectives.

Use these questions to evaluate any prospective partner: a consultancy, systems integrator, vendor, internal team, or other provider. They are not a test designed to favor one firm. They are a way to make the work, responsibilities, and assumptions visible before you commit.

You don’t need to ask all fifteen in one meeting. Choose the ones that matter most to the work you’re considering. Ask for specifics, listen for how the partner handles uncertainty, and compare substance rather than presentation polish.

The perspective here draws on Julie Traxler’s more than two decades of personal experience in operations, M&A integration and carve-outs, ERP and operational change, and complex execution. It does not claim a track record of specific AI implementations or outcomes.

A. BUSINESS UNDERSTANDING

Q1. “How will you determine which business opportunities are worth pursuing with AI?”

Why it matters:
A business can have many ideas and still lack a clear basis for deciding what deserves time and investment. A partner should help distinguish a real opportunity from a technically interesting experiment.

A credible answer should address:
How the partner will understand the work and objectives; how it will compare possible value, feasibility, risk, and effort; what evidence or baseline it needs; how it will assess whether AI is appropriate; and how it will handle opportunities that should be deferred or declined.

Warning signs:
The conversation starts with a preferred tool or platform. Every idea is treated as a build opportunity. The partner cannot explain how it would compare use cases or what would lead it to recommend ‘not AI.’

Q2. “How will you learn how the work actually gets done, including the exceptions and workarounds?”

Why it matters:
Process documentation can be a useful starting point, but it may not show every handoff, exception, or workaround people rely on. A solution designed without understanding those realities may add work or miss important operating requirements.

A credible answer should address:
Who the partner would speak with, including people doing the work; how it will examine the process end to end; how it will identify exceptions, dependencies, and informal practices; what it will document; and how it will validate its understanding with your team.

Warning signs:
Discovery is limited to a workshop or review of existing documents. The partner proposes a solution before asking who uses the workflow, where it varies, or how exceptions are handled.

Q3. “How will you account for other changes underway that could affect this work?”

Why it matters:
AI implementation may overlap with an acquisition, system migration, carve-out, reorganization, or process redesign. Dependencies and timing can change whether a solution is suitable or sustainable.

A credible answer should address:
How the partner will identify related programs, systems, teams, and decision dependencies; how it will coordinate with owners of those changes; what assumptions may need to be revisited; and who decides whether to proceed, sequence, pause, or adjust the work.

Warning signs:
The partner treats the surrounding change as irrelevant or automatically out of scope. Its plan assumes the business and systems will remain stable without verifying that assumption.

B. IMPLEMENTATION CAPABILITY

Q4. “Who will design, build, configure, integrate, test, and deploy the solution—and what is required from our team?”

Why it matters:
‘Implementation’ can describe many different kinds of work. You need to know what the partner will actually do, who will do it, and what is expected of your own team.

A credible answer should address:
The roles involved; the tasks the partner will perform versus those your staff or another vendor will perform; how design decisions will be reviewed; how working progress will be demonstrated; and what the proposed solution requires before it can be deployed.

Warning signs:
The proposal lists capabilities but not responsibilities. The partner cannot identify who will do the work. Client participation is assumed to be passive (‘we’ll handle everything’). A polished demo is offered in place of an explanation of the build, integration, testing, and deployment steps.

Q5. “How will the solution fit with our existing systems, workflows, and handoffs?”

Why it matters:
Some AI solutions need to connect with existing systems, data, or processes; others may not. Where connections are needed, their scope, dependencies, and failure handling can affect whether the solution fits the work.

A credible answer should address:
Which connections the proposed solution needs and why; what information may need to move between systems; where approvals and human handoffs occur; which dependencies still need to be confirmed; and how the partner will coordinate with your IT and operations owners.

Warning signs:
Integration is called ‘straightforward’ before the environment is understood. The proposal describes the solution in isolation, skips client-side dependencies, or doesn’t say what happens when a connection is unavailable or information is incomplete.

Q6. “How will you test whether the solution is reliable enough for its intended use?”

Why it matters:
AI components can return incorrect, inconsistent, or unexpected results. A successful demonstration alone doesn’t show how a solution will perform across the conditions and inputs it is intended to handle.

A credible answer should address:
How test cases will reflect the intended use, including relevant edge cases; how results and limitations will be evaluated; how uncertain or incorrect outputs will be handled; who approves readiness; and what review or monitoring is appropriate after deployment.

Warning signs:
The demo is treated as sufficient evidence. The partner can’t explain how results will be evaluated or who accepts remaining limitations. There’s no plan to review issues that emerge in actual use.

C. GOVERNANCE, SECURITY, AND RISK

Q7. “Who will decide what the AI solution is allowed to do and when a person must review its output?”

Why it matters:
The solution’s authority should match the consequences of its use. Without clear decision responsibilities, people may not know when to rely on an output, intervene, or escalate a concern.

A credible answer should address:
Who approves the use case and data access; which tasks the system may perform; where a person reviews or approves work; who owns decisions and outcomes; and how the rules can be adjusted as the use or risk changes.

Warning signs:
Governance is left until after the build. No human responsibility is defined. The partner proposes the same controls for every use case without considering what the solution does and what happens if it fails.

Q8. “How will data handling, access, and vendor risks be reviewed before the solution is used?”

Why it matters:
Implementations may involve sensitive business information, customer data, intellectual property, or third-party services. The organization needs to understand where data goes, who can access it, and what agreements and controls apply.

A credible answer should address:
What information the solution will use; how access will be limited; where data is processed, stored, or shared; which vendors or subprocessors are involved; what security, legal, procurement, or compliance reviews are needed; and who is responsible for those decisions.

Warning signs:
Security review is postponed until the build is complete. The partner cannot explain the data path or third-party dependencies. Your existing requirements are dismissed as obstacles rather than incorporated into the work.

Q9. “If the solution produces a harmful, incorrect, or unexpected result, who is responsible and what happens next?”

Why it matters:
An organization shouldn’t assume an AI-enabled solution is error-free. It needs a way to notice issues, assign responsibility, respond, and decide whether the solution or its controls need to change.

A credible answer should address:
Who owns the solution and its business use; how people can report issues and how issues may be detected; who can pause or restrict use; what escalation and correction steps apply; and how the organization will decide whether changes are needed.

Warning signs:
The answer relies only on a general accuracy claim or defers responsibility to the model provider. There’s no named business owner, escalation route, or plan for investigating errors that aren’t immediately obvious.

D. ADOPTION AND BUSINESS VALUE

Q10. “How will you involve the people whose work will change, and what participation do you need from us?”

Why it matters:
A solution can be technically ready while the workflow, responsibilities, or expectations around it remain unclear. The people doing and managing the work can identify requirements that are easy to miss from outside.

A credible answer should address:
Which roles should help shape the solution; how their input will affect design and testing; what enablement or support they will need; how changes to responsibilities and handoffs will be communicated; and how feedback will be handled.

Warning signs:
Users are first involved at launch. Enablement means only a one-time presentation. The partner does not ask how the solution affects existing roles, workload, or accountability.

Q11. “How will we define and measure business value before the work begins?”

Why it matters:
Activity measures, such as number of users or outputs, do not by themselves show whether a business problem improved. A shared definition of value helps leaders make decisions about continuing, changing, or stopping the work.

A credible answer should address:
The business objective; the current baseline if available; which measures could reflect the intended improvement; who owns those measures; how and when they will be reviewed; and how the team will interpret results if the expected value does not materialize.

Warning signs:
The partner promises a result without understanding the baseline. Success is defined only as deployment or usage. No one is responsible for reviewing whether the solution made a meaningful difference.

Q12. “How will we understand and manage costs as usage and business needs change?”

Why it matters:
Costs can depend on usage, data volumes, vendors, integrations, and the design choices made. Leaders need visibility into those costs alongside the value and service requirements.

A credible answer should address:
The main cost drivers and assumptions; what usage levels were considered; which costs are variable; what monitoring and review are possible; who will own cost decisions; and how the organization can respond if costs or usage change.

Warning signs:
The partner discusses only the initial build price. Ongoing consumption or vendor costs are unknown. Cost is treated as a future issue, or the organization is told to expect savings without a measurement plan.

E. LONG-TERM OWNERSHIP AND SUSTAINABILITY

Q13. “What does ‘done’ mean, and how will we know the solution is ready to hand over?”

Why it matters:
Without an agreed finish line, deliverables can be mistaken for outcomes and the work can continue without a clear reason. A handoff should make ownership and remaining responsibilities explicit.

A credible answer should address:
The intended outcome; acceptance criteria; what is in and out of scope; what the client must provide; what documentation, access, and training will be transferred; and what must be true for the client to operate the solution.

Warning signs:
‘Done’ means only that the software was deployed. Scope boundaries are avoided. The partner cannot explain what the client receives or who is accountable after handoff.

Q14. “Who will own, maintain, and improve the solution after the implementation team leaves?”

Why it matters:
The business, its data, workflows, vendors, and requirements can change. Some changes may affect a solution’s behavior, cost, or suitability, so ownership and review responsibilities should be clear from the start.

A credible answer should address:
The client-side owner and their responsibilities; what maintenance or vendor support may be needed; how changes are reviewed and approved; what operating information and documentation will be retained; and how the organization will decide whether to improve, replace, pause, or retire the solution.

Warning signs:
No owner is named. The partner is assumed to remain responsible indefinitely. Documentation covers what was built but not how to operate or change it.

Q15. “Under what conditions would you advise us not to use AI, or to choose another partner?”

Why it matters:
A partner’s willingness to identify a poor fit can reveal whether it is evaluating the business need or simply selling a build. It also helps clarify the partner’s boundaries and the alternatives available.

A credible answer should address:
Conditions that might make AI unsuitable, such as unclear value, a process that needs attention first, unresolved data or ownership questions, or risks the organization can’t responsibly manage; alternatives worth considering; and work that would be better suited to another provider.

Warning signs:
The partner treats every problem as an AI opportunity, avoids discussing limits, or can’t explain when another approach or provider may be more appropriate. One answer alone doesn’t prove a partner’s judgment, but the specifics and willingness to discuss tradeoffs matter.

Using the answers

Compare how candidates explain responsibilities, assumptions, decision points, dependencies, failure handling, and handoff. Ask follow-up questions when an answer sounds polished but doesn’t tell you what the team will actually do.

A useful final check: can your own team explain what the partner will do first, what the client must contribute, and what will count as done? If those answers are still unclear, resolve that before committing.

This guide does not choose a partner for you. It helps make the decision and the work easier to see.

What Your Organization Needs to Bring to the Partnership

A partner can do good work and still be blocked if the organization can’t make decisions, provide access, or take ownership. Before work begins, identify who will:

• Sponsor the work: Set the business priority, provide decision authority, and resolve tradeoffs.

• Participate in the work: Make operational leaders and people who do the work available to explain processes, review designs, and test solutions.

• Make timely decisions: Name approvers and decision-makers, and agree how questions and approvals will be handled.

• Provide appropriate access: Arrange approved access to the systems, data, and people needed, with the right owners involved.

• Own the business outcome: Assign a business owner accountable for acceptance, ongoing operation, and escalation after implementation.

• Support adoption and follow-through: Make room for people to learn and use the changed workflow, gather feedback, and act on what the organization learns.

The partner should make these responsibilities, timing, and dependencies explicit. They shouldn’t be left as assumptions on either side.