AI Strategy Consulting

AI strategy consulting answers a practical question: which AI use cases are worth your money, in what order, and with what technology. StepTo runs readiness assessments, feasibility studies, and build-vs-buy analyses, then implements the resulting roadmap with our own engineers — from LLM integrations and RAG systems to production ML pipelines — as part of our custom software development practice. Working from Serbia's 60,000-strong IT talent market at $35–75/hr, we make serious AI work affordable for mid-sized companies, not just enterprises.

AI Consulting Services

Where AI Delivers ROI First

Engagement Models & Pricing

Why StepTo for AI Strategy

How an AI Strategy Engagement Runs

  1. Discovery (week 1–2): Stakeholder interviews, data and systems audit, and a long-list of use cases.
  2. Prioritisation (week 3–4): Feasibility and ROI scoring; build/buy/API recommendation per short-listed use case.
  3. Roadmap delivery (week 5): Sequenced plan with budgets, governance requirements, and success metrics per initiative.
  4. Pilot (6–10 weeks): The top use case built and evaluated on real data.
  5. Scale: Production hardening, MLOps, and successive roadmap items under a dedicated team or staff augmentation.

FAQ: AI Strategy Consulting

How much does AI strategy consulting cost?
An AI readiness assessment — auditing your data, systems, and candidate use cases, and delivering a prioritised roadmap — typically costs $10,000–25,000 over 3–5 weeks. A proof of concept for one use case usually runs $20,000–60,000 over 6–10 weeks. Production implementation depends on scope but benefits from the same rate structure: StepTo engineers bill $35–75/hr, roughly 40–60% below Western European or US AI consultancies.
How do you decide whether we should build, buy, or use an API?
We compare three paths per use case: an off-the-shelf AI product, a solution assembled on foundation-model APIs (OpenAI, Anthropic, Google, or open-weight models), and custom model training. For most business use cases, API-based solutions with retrieval (RAG) win on time-to-value and cost; custom training only pays off with proprietary data at scale or hard latency/cost constraints. The recommendation comes with a cost model covering licences, inference spend, and engineering effort over 24 months.
What makes a good first AI use case?
The best first projects have three properties: the task is high-volume and repetitive (document processing, support triage, report drafting), the data needed already exists in accessible systems, and an imperfect output is reviewable by a human rather than catastrophic. We deliberately steer first projects away from mission-critical automated decisions — the goal is a measurable win that builds organisational confidence and infrastructure for the harder use cases.
How do you address AI governance, privacy, and the EU AI Act?
The roadmap includes a governance track: data-protection review of what may be sent to which model providers (with EU-hosted or self-hosted options where required by GDPR), risk classification of use cases against the EU AI Act, human-oversight design for higher-risk workflows, and evaluation procedures that log and measure model behaviour before and after deployment.
Can StepTo implement the strategy, not just write it?
Yes — that is the point of working with an engineering firm rather than a pure advisory. The consultants who scope your roadmap are backed by engineers who build the pilots and production systems, through a fixed-scope project, staff augmentation from $4,500/month per engineer, or a dedicated AI team from $13,500/month. You are never handed a slide deck that another vendor must interpret.

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