Frequently Asked Questions
What is AI strategy consulting?
An AI strategy consultant identifies which operational problems are worth solving with AI, defines those problems in terms a technical team can build from, and quantifies the expected return before any investment is made. The role provides independent guidance not tied to any vendor or platform — bridging the gap between what an engineering team can build and what a leadership team needs to justify.
AI strategy determines which problems are worth solving, in what order, and what return to expect — before any technology is selected or built. AI implementation is the technical execution that follows. Most AI investment failures are strategy failures: the wrong problem was chosen, the wrong tool was selected, or the expected return was never properly quantified.
The most common cause is not bad technology — it is a Logic Leak. The data exists. The decision exists. The logic connecting them is broken or missing. Most organisations invest in tools before finding this gap, which means they are automating a broken process rather than fixing it.
Manufacturing, FMCG, logistics, telecom, and retail — with engagements across the US, Europe, Asia-Pacific, Australia, New Zealand, and the Middle East. The diagnostic frameworks travel across sectors. The specific application is always built for the operational context.
About the Logic Leak
A Logic Leak is the specific point where data exists and a decision exists, but the logic connecting them is broken or missing. The data that could improve a decision is not reaching it — due to structural, architectural, or process gaps. Identifying and closing the Logic Leak is the central diagnostic task before any tool is recommended.
Most organisations assume AI initiatives fail because of data quality or volume. In practice, the more common issue is structural: the data exists, but it is not connected to the decision it should inform. A Logic Leak is an architectural problem, not a data collection problem. Adding more data to a broken architecture produces more noise, not better decisions.
80% of enterprise AI value comes from deterministic and probabilistic methods — forecasting, classification, churn prediction, safety stock calculations. The other 20% is GenAI and LLMs. Most companies build the 20% first and neglect the 80% that actually compounds the P&L. The 80/20 stack is the prioritisation framework used in every audit engagement.
About the engagements
Three engagements: the Logic Leak Audit starts at $2,400 (2-week diagnostic); the Fractional Chief AI Officer is a 3–12 month embedded retainer (custom-priced); the AI Profit OS cohort is $1,500 per seat. A Clarity Call is available first to assess which engagement fits.
The Logic Leak Audit runs 2 weeks. The Fractional Chief AI Officer runs 3–12 months, typically 1–2 days per week. The AI Profit OS cohort has quarterly intake. Timeline depends on the engagement type and the complexity of the system being audited.
A 2-week diagnostic that maps where the logic breaks between your data and your decisions. Delivers a data roadmap, tech audit, problem reframe, and AI roadmap for the next 4 quarters. Starting price is $2,400 — final scope depends on system complexity. No implementation work is required to run it.
A group programme teaching the Logic Leak diagnostic, 80/20 AI stack, and A.R.T. (Audit, Repair, Transfer) framework to operations leaders and their teams. $1,500 per seat. Intake is quarterly. Designed for COOs, CFOs, and VPs of Operations who want to apply the diagnostic methodology inside their own organisation.
An embedded part-time Chief AI Officer — typically 1–2 days per week — providing senior AI and business strategy judgment across a sequence of decisions over 3–12 months. For companies that need C-suite level AI leadership without a full-time hire. Covers vendor proposal review, implementation oversight, and translating technical progress into language the board can act on.
No. The Logic Leak Audit runs on whatever exists — including organisations with no AI systems yet. The diagnostic identifies where the highest-value gaps are and what the right first investment should be. Most engagements start precisely because nothing is in place and the leadership team does not know where to begin.
Working with Jitin
Yes. All engagements run entirely remotely — no site visits required. Clients are in Australia, New Zealand, the UK, Europe, the US, and the Middle East. Being based in India with global clients is a structural advantage: no timezone territory limitations, no travel markup on the engagement cost.
Big 4 firms over-staff mid-market engagements and charge accordingly — the economics only work for Fortune 500 budgets. Vendors define the problem to fit their tool, which is a structural conflict of interest. Jitin has no vendor relationships and no implementation arm. His only deliverable is a better decision. He built production AI systems before the term “AI strategy” existed — forecasting models, churn models, quality inspection pipelines — and brings that practitioner lens to every diagnostic.
Book a Clarity Call at cal.com/jitink-kriyalytics/strategy-consulting. 30 minutes. No sales deck. Jitin will tell you on the call whether an audit makes sense for your situation and which engagement fits.
The Weekly AI Decision Brief
What is the Weekly AI Decision Brief? A practitioner newsletter for operations leaders. One sharp insight per week on where AI connects — or fails to connect — to the P&L. Published every Wednesday. No vendor affiliation, no product promotion. Subscribe →