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The partner asks the associates preparing a proposal to emphasize AI. They add an AI slide to the methodology and describe the approach as AI-powered. The client sponsor still needs to understand which workstream will change and what the case team will deliver.
At auxi, we sell AI software. We think a client should expect us to connect a technology claim to a specific task and a way to evaluate the result. Consultants should apply that standard to their own commercial proposals.
A strong AI consulting proposal names the analysis the case team will undertake, the client inputs it requires and the decision the work will support. It distinguishes a target the team intends to test from a result it can substantiate.
Write the workstream before writing the technology claim
Consider a fictional procurement diagnostic. The principal could describe an AI-powered approach to spend optimization and leave the methodology at that level. The client CFO would have little basis for estimating the effort required from the finance team or judging the eventual recommendation.
A more useful proposal would explain that the associates will test AI-assisted classification of a sample of accounts-payable transactions against an agreed spend taxonomy. The engagement manager will review ambiguous classifications with the client's category leads. The case team will compare the resulting spend cube with the existing classification before sizing opportunities.
The sponsor can assess that scope. The client may have a usable taxonomy and poor transaction descriptions, or good source data with no agreement on category ownership. The principal can address those conditions before promising an accelerated diagnostic.
Specify the output the client will receive. A classified spend file, a list of unresolved exceptions and an opportunity assessment serve different purposes. If the partner commits to all of them, include their preparation and review in the staffing estimate.
Separate the analytical finding from the financial result
An associate identifies a price difference between two suppliers. The case team should examine whether the products, service terms and volumes are comparable before describing the difference as an opportunity.
The partner should also distinguish an estimated opportunity from realized procurement savings. The client may need to renegotiate contracts, qualify an alternative supplier or change demand. A faster spend classification does not establish that those actions will succeed.
In the proposal, state whether the team will deliver a diagnostic, support negotiation or take responsibility for implementation. The client sponsor needs to know where the case team's commitment ends and which actions the client must own.
For a target such as reducing the diagnostic effort, describe how the engagement manager will evaluate it. Include the hours the associates spend resolving exceptions and the time client category leads spend validating the analysis. A fast first pass can require enough reconciliation to alter the business case.
Use AI language in proportion to the mandate
Consultants discussing proposals in a public forum described pressure to add AI language before agreeing on a use case. Those accounts are unverified, but the situation is useful to examine during a proposal review.
For a client commissioning an AI deployment, the principal needs to explain the technical approach, the operating responsibilities and the validation plan. For a client buying a commercial assessment, the sponsor may place greater weight on the fact base and the judgment behind the recommendation.
Describe the technology where it affects the client's choice. Explain data access and integration requirements that could change the workplan. Avoid making the sponsor read a model description to discover what the engagement will produce.
The relationship partner should also decide how to handle an unsuccessful pilot. If the proposed use fails the agreed quality threshold, state whether the team will complete the diagnostic through its existing approach, revise the scope or bring the decision back to the sponsor. Include the effort required for that path.
Review the claim during the partner page turn
Read the methodology without the broad AI labels. Ask the principal to identify the workstream, the acceptance standard and the client dependency behind each promised benefit.
If the team cites a prior engagement, check that the example supports the claim being made. A result achieved with clean transaction data and dedicated client support may be a poor estimate for a fragmented finance environment. Explain the difference before using the result to justify a fee or timeline.
Then restore the technology detail that helps the client assess execution. The partner should be able to explain both the analytical value of the approach and the conditions under which the case team expects it to work.
We encourage prospective auxi customers to evaluate us with the same discipline. Select a recurring case-team task, involve the engagement manager who reviews the pages and agree on what the team should improve. That comparison gives the partner a purchasing basis tied to the work consultants need to complete.