What Questions to Ask Before Hiring an AI Development Partner

The AI development services market has exploded since 2022. Every web development firm, IT consultancy, and offshore staffing agency now claims AI expertise. Evaluating these claims is genuinely difficult for non-technical buyers — the vocabulary sounds right, the case studies are often not comparable to your situation, and the price range for the same project can span 300–400%.

The questions below are designed to surface meaningful differentiation between credible AI development partners and those who will underdeliver. They are organized by what they reveal.

Questions About Discovery and Scoping

"Walk me through your discovery process for a project like this."

A credible partner describes a structured discovery process: requirements sessions, stakeholder interviews, data assessment, architecture design, and a written specification before any development begins. An answer that immediately jumps to technology choices or timelines without describing how they learn what to build is a flag.

"Have you built something similar before? Can I speak with that client?"

Case studies on websites are marketing. Speaking directly to a reference client at a comparable scale — a Canadian SMB, not a $50M enterprise — tells you what you actually need to know: Did the project deliver what was scoped? Was the timeline and budget accurate? Was the partner responsive when problems arose? Would they hire them again?

"What is not included in your quote?"

Scoping gaps are where AI development projects most commonly exceed budget. Ask explicitly: Are data preparation and cleaning included? Is post-launch support included? Is third-party model API cost (OpenAI, Azure OpenAI) included or billed separately? Is user acceptance testing by the client team included in the timeline?

Questions About Data and Technical Practice

"Where will our data be processed, and can you provide a data processing agreement?"

Under PIPEDA, your organization remains accountable for personal data processed by third-party development partners and cloud AI services. A credible partner for Canadian SMBs should: know what a data processing agreement (DPA) is, be willing to sign one, and be able to specify which data centres process your data. An answer of "we use OpenAI" without further detail about data residency and the DPA is insufficient. (OPC PIPEDA Guidance)

"What LLM(s) do you plan to use, and why? What are the alternatives?"

A development partner with genuine AI expertise can explain their model selection rationale: why GPT-4o vs. Claude vs. an open-source model, how inference costs at expected volume compare, and what the tradeoffs are. A partner who responds "we use ChatGPT" without further detail may be using AI tools but does not have the architectural expertise to make principled model selection decisions.

"How do you handle model updates and version changes after launch?"

LLM providers regularly update their models. Prompts that work well on one model version may produce degraded outputs on the next. A credible partner has a plan for managing model updates: monitoring output quality, testing new model versions before switching, and maintaining application stability through provider changes.

Questions About Ownership and Contracts

"Who owns the code, the trained models, and the data after the project?"

You should own all of it. Some development agreements, particularly with offshore providers, assign IP to the developer by default. Confirm explicitly and ensure it is written into the contract.

"How are change requests handled, and what is the process for scope additions?"

Scope creep is the primary cause of budget overruns in custom development. A credible partner has a clear change order process: what triggers a change order, who approves it, and how cost and timeline are adjusted. Vague answers here suggest the partner either manages this ad hoc (which will cost you) or does not expect the scope to change (which is unrealistic).

"What does your standard post-launch support agreement include, and at what cost?"

Applications require ongoing maintenance. Confirm what is included: bug fixes, security patching, model updates, integration maintenance. Confirm the response time commitments and the cost structure. An application with no post-launch support agreement is a risk that becomes apparent the first time something breaks.

Questions About the Team

"Who specifically will be working on our project, and what is their AI experience?"

"Our team" is not an answer. You want to understand: who leads the project, who writes the AI layer, who handles infrastructure, and who manages client communication. Subcontracting arrangements — where the firm you hire passes the work to an offshore team you have never met — are a significant quality risk in this market.

Sources

• Office of the Privacy Commissioner of Canada. *PIPEDA Overview.* priv.gc.ca
• BDC. *Hiring Technology Consultants — What to Look For.* bdc.ca
• Statistics Canada. *Survey on Digital Technology and Internet Use, 2023.* statcan.gc.ca
• Innovation, Science and Economic Development Canada. *SME Research Statistics.* ised-isde.canada.ca

Cloud Forces is a Canadian AI development partner — we answer all of these questions directly and encourage reference calls with existing clients. Explore our Custom AI Applications service or book a discovery call to see what transparent AI development looks like in practice.