Finding the Real Budget: Give AI a Budget. Give That Budget a Purpose.
From everyday AI tools to Snowflake: shared answers, useful guardrails, and investment your business can support.
By Dithanon Khrutmuang | Power Ladder
Have you ever subscribed to several AI tools, only to find that some go barely used while your team needs more of another?
We might start with ChatGPT, Claude or Grok for thinking and writing, then add specialist tools for voice or video. The management question is familiar: who uses what, for which work, and what value does that spending create? Unused capacity does not automatically mean poor value. High usage does not automatically mean waste.
It reminds me of my resort business. We invested in a large outdoor meeting area that guests used infrequently. Meanwhile, staff had insufficient space for some of their work nearby. That experience taught me to think about investment and allocation together.
Resources become useful when they match the work people actually need to do.
From personal prompts to shared business decisions
When the question changes from “Help me draft this message” to “How much should we stock next month?” or “Which customers might stop buying?”, the answer needs company data: sales, inventory, costs and customer behaviour, with definitions people agree on.
Snowflake is one option for bringing that data and AI together. Cortex Analyst can translate natural-language questions into SQL over prepared data. Forecasting stock or predicting churn still requires suitable business logic or models, with validation. [1]
Once multiple teams depend on the answers, we need to design access, workflows and costs together. AI services and data processing can contribute separate charges; a single subscription-plan analogy will not describe every system. [2]
FIG. 01 The move to shared business data introduces shared definitions, access and cost responsibilities.
This is where I apply Finding the Real Budget Business Play: consider the opportunity alongside financial readiness, decide which work deserves investment, and design how people will use it.
Find the money the business can actually commit
Finding the Real Budget uses AI-assisted forecasts of cash flow, the balance sheet and margins to support investment choices. A simple starting point for the cash side is:
PRELIMINARY CASH HEADROOM B = max(0, opening cash + expected receipts − existing payments − reserve)
Use the same time period for every input. Existing payments exclude the proposed new project. B is an initial view of available funds, not the full Business Play model: check payment timing, liabilities and margins before committing.
FIG. 02 A hypothetical cash plan. Available headroom still competes with other business priorities.
If THB 200,000 of expected receipts slips beyond the three-month period, headroom falls to zero. Even a positive closing balance can hide a cash shortage earlier in the period.
Calculate recurring answers. Let people use them together.
I suggest starting with questions people repeatedly use to make decisions. Calculate the answers on an appropriate schedule and share them through a dashboard: products to replenish, for example, or customer-risk scores. Use AI for new questions and deeper follow-up analysis.
The dashboard needs a calculation or model behind it, an appropriate refresh cycle and the right access rules. Reuse must still deliver an answer that is fresh enough for the decision. Snowflake can also reuse certain query results when its conditions are met; actual savings must reflect any reuse already present. [5]
FIG. 03 Two complementary routes: shared results for recurring needs and targeted AI for further exploration.
A simple test for the investment
EXPECTED NET COST SAVING S = (N × C) − D
N
AI questions the dashboard genuinely replaces.
C
Average cost per question that can actually be avoided.
D
All additional dashboard costs over the same period: building, calculating, refreshing, storing, serving and maintaining it.
In a hypothetical three-month example, replacing 2,000 questions at THB 4 each, with THB 5,000 of dashboard costs, saves THB 3,000. Replacing only 500 questions adds THB 3,000 of cost instead. Break-even is 1,250 questions.
Illustrative assumptions, not Snowflake prices or measured results. A fixed fee that stays unchanged is not a cash saving.
FIG. 04 Frequency matters. A useful dashboard can still cost more than the calls it replaces.
My starting rule for a cost-saving investment is: S is positive, answer quality and freshness are sufficient, and total project payments fit within B without creating a cash shortfall. Then compare it with other opportunities. If questions keep changing or usage is low, continuing to experiment with AI first may be the better choice.
Give people limits that match their work
Shared answers will not cover every need. People still need room to investigate and experiment. I suggest allocating that room according to business impact, frequency and deadlines, with a named owner who can explain what extra spending is meant to achieve.
FIG. 05 Suggested policy tiers, to be adapted to the organisation. A person may perform more than one type of work.
For routine users, track which answers lead to action. For analysts and developers, review cost per experiment and what was learned. For deadline-critical work, consider the consequence of interruption and prepare capacity in advance.
A higher limit for a person does not make every request important. The design needs to consider both the user and the services or resources supporting the work.
Five practical guardrails
Separate team budgets from individual allowances. Use budgets to monitor aggregate spend and notifications, alongside individual quotas. Ten users with 100 credits each can collectively reach 1,000 credits, not 100. [3]
Group users by usage needs. Tags can scope separate quotas for different allowances. Within one quota, users share the same per-user limits. Check overlapping scope when moving someone into a higher tier. [4]
Warn before work stops. A proposed starting policy is an alert at 80% of usage. Review real demand before enabling blocking. The percentage is an example, not a Snowflake recommendation.
Pair daily and monthly limits. They apply independently. Monthly headroom does not override a daily ceiling. Prepare allowance for approved heavy work; enforcement has a delay, so overshoot is possible. [4]
Make extra allowance easy to justify. Ask for the task, intended outcome, extra amount and end date. A named approver reviews the business case; an administrator makes the change and reviews it when the work ends.
Implementation matters: warehouse monitoring and AI blocking are not interchangeable. Warehouse and AI scopes use separate quotas; built-in blocking applies to supported AI domains, not warehouse compute. Currency budgets need conversion using actual service rates and contract terms. [4]
Good cost governance gives people a clear path to do useful work and a clear route to request more capacity. Finding the Real Budget connects those choices to financial readiness and the opportunities the business wants to pursue.
Start with what matters to your business.
Power Ladder helps design this approach through Discovery Consulting. We begin by interviewing executives and the people involved: what matters most, who makes the decisions, who uses the answers, who owns the data, and who manages Snowflake and the budget.
We then work with you to design which answers should be calculated and shared through dashboards, where AI should support further analysis, and how access, user allowances, alerts and exceptions should work in your Snowflake environment.
FIG. 06 The service starts with business needs and stakeholders, then connects design, spending rules and review.
Our aim is to fit the system to real work, then track outcomes and adjust spending so your Data & AI budget creates the greatest practical benefit within your priorities and constraints.
Begin with the decisions that matter and the people who need to be involved.
References & example notes
Official documentation checked 28 September 2026. Platform features and pricing can change; use the current documentation when implementing.
Natural-language access to prepared structured data and SQL generation.
Snowflake: Snowflake AI pricing
Service-specific AI charges and associated compute costs.
Snowflake: AI cost management and governance
Team budgets, cost attribution and the distinction between pooled spend and individual quotas.
User tags, limits, overlapping scope, notifications and enforcement limitations.
Snowflake: Using Persisted Query Results
Conditions for reusing query results. Caching is not a guarantee that every dashboard view or AI request is free.
The resort experience is the author’s own account. Business Play, the proposed policy tiers and the simplified equations are Power Ladder’s explanatory framework, not vendor-endorsed rules. All cash and cost examples are hypothetical, use Thai baht (THB), and cover three months.
The cash equation is preliminary headroom, not a complete investment model. The saving equation measures avoidable costs, not every opportunity cost. If C is zero, there is no break-even from avoided query costs alone. Building costs are counted in full in the illustrative period.
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