Last updated 2026-06-10
iAnalyst is not new to this. We have been the analysts behind growth programs for brands like Norwegian Cruise Line, PlayStation, and Benihana since 2009, which means fifteen years of being paid to answer one question honestly: is this working? AI consulting is that same question, asked before you spend instead of after.
The AI consulting market has a theater problem. Slide decks about disruption, maturity models, vision workshops. We do not sell those. An iAnalyst consulting engagement produces decisions: which workflows to augment, which tools to buy versus build, what your data can actually support, what the first ninety days look like, and which numbers will prove it worked.
Consulting is also where we decide together whether your situation calls for AI optimization of what you already run, or the deeper process redesign of AI transformation. Most businesses need the first. Some need the second. Nobody needs both at once on day one.
What the engagement includes
AI opportunity assessment
A structured review of your channels, workflows, and data, producing a ranked list of AI applications with expected gain and effort.
Data readiness review
What your systems can support today, what needs cleanup first, and where the quick wins hide in data you already have.
Build, buy, or skip decisions
Vendor evaluation grounded in your actual requirements, including the recommendation vendors never give: skip it.
90-day roadmap
The first quarter sequenced: pilots, owners, baselines, and the verdict dates when each bet gets judged.
Governance and guardrails
Practical policy for AI use in your business: what is automated, what needs review, what stays human.
Measurement plan
Every recommendation arrives with the number that will prove or disprove it. No unmeasurable advice.
What an AI consulting engagement answers
Where does AI pay off first in this specific business? That breaks into concrete questions. Which of your workflows are high-volume, rules-describable, and instrumented enough to augment safely? Which channels are leaving money on the table that AI-grade optimization would recover? What would each application cost to run, and what is the realistic gain?
And the questions most consultants skip: where will AI fail in your business? Which vendor claims do not survive contact with your data? What should you deliberately not automate because the human judgment in it is the product? An analyst firm earns its fee on the second list as much as the first.
Why a marketing-analytics firm consults well on AI
Because the failure mode of AI adoption is the failure mode we have spent fifteen years preventing in media: spend without measurement. Performance marketing trained us to baseline everything, distrust dashboards we did not verify, and kill underperforming bets quickly. Those instincts transfer directly.
We also operate what we recommend. The same firm that writes your roadmap can run the paid media, SEO, and content programs it proposes, which keeps our advice honest: we may have to live with it.
What it costs to find out
The first conversation is free and useful on its own. Book a call, and a senior analyst (not a salesperson) will spend thirty minutes on your business: your channels, your team's workload, your data, your competitors. You leave with a first-pass read on where AI pays off for you, whether or not we ever work together.
From there, engagements are scoped to the decision you need made. We do not publish rate cards or sell prepackaged tiers; the scope follows the question.