If you are looking for an AI consulting company, start by deciding which job you are hiring for. "AI consulting" covers two very different engagements. One is strategy: a firm assesses your data, use cases and org, then hands you a roadmap. The other is delivery: the firm wires a model into your product, gets it through security review, and keeps it running. Most buyers need some mix of both.

This guide explains what each engagement includes, how to pick between them, and which firms in the directory to shortlist. Each firm links to a profile with specialties, size and location.

What AI consulting companies actually do

A real AI consulting engagement usually covers some combination of:

  • Use-case prioritization. Sorting a long list of "we could use AI for X" ideas into the two or three worth funding, based on data availability and expected impact.
  • Data and infrastructure readiness. Most AI projects stall on the data, not the model. A serious firm will assess whether your data is accessible, clean, and permissioned before proposing anything.
  • Model selection and prototyping. Choosing between a fine-tuned model, a retrieval pipeline, an off-the-shelf API, or a custom system, and proving it on a small scope first.
  • Production implementation. Integration with existing systems, evaluation harnesses, monitoring, and the failure modes that don't show up in a demo.
  • Change management. Getting the people who use or oversee the system to adopt it.

Some firms only do the first two: pure strategy shops that hand off before anything gets built. Others, including most of the companies below, run the engagement end to end. Ask which side of that line a firm sits on before you scope a project.

AI consulting vs. AI implementation

The practical difference is where a firm's default engagement starts and ends. For what an implementation-focused engagement looks like, see our AI implementation costs and timelines guide and AI consulting services explained. For the framing question, read AI consulting company vs. implementation partner and AI consulting company vs. independent consultant.

How to choose an AI consulting partner

Define your use case and success metric before you talk to anyone, ask to see a shipped product rather than a slide deck, and get the names of the people who will work on your project. The full framework is in How to Choose an AI Implementation Company; for a scoring approach, see how to compare AI implementation companies. If size is your first filter, read AI consulting firms: boutique vs mid-size vs large or the breakdown of consulting companies by specialty.

AI consulting firms worth knowing

The list is drawn from firms on this directory tagged AI Strategy, Enterprise AI, Generative AI Consulting, or Machine Learning Consulting. The featured partner is disclosed and pinned first; everyone else is ordered alphabetically, unpaid.

Featured partner: asaasin.ai runs small, senior AI engineering pods out of Orange County, CA and Prishtina, Kosovo, covering AI strategy, LLM integration, and enterprise AI integration work for product companies.

  • Addepto — Warsaw-based AI and big data consultancy covering generative AI and machine learning consulting through to MLOps.
  • DOOR3 — New York consultancy offering AI strategy, agentic AI, and machine learning consulting alongside custom software work for legal, insurance, and financial clients.
  • EPAM Systems — publicly traded (NYSE: EPAM) global engineering firm with a generative AI consulting and enterprise AI practice.
  • Grid Dynamics — publicly traded (Nasdaq: GDYN) consultancy combining AI strategy, machine learning consulting, and data engineering for large enterprises.
  • HatchWorks AI — Atlanta-based firm pairing AI strategy with product engineering and adoption/change management.
  • InData Labs — Miami-based data science and AI consulting firm spanning generative AI, machine learning consulting, and MLOps.
  • ITRex Group — generative AI consulting from strategy through proof-of-concept to production, with healthcare and manufacturing experience.
  • Kanerika — Austin-based consultancy combining generative AI consulting with data modernization and machine learning consulting.
  • LeewayHertz — generative AI consulting and machine learning consulting for startups and enterprises, based in Gurugram.
  • Neurons Lab — London-based AI strategy consultancy focused on agentic AI for financial institutions.
  • Publicis Sapient — large digital transformation consultancy with AI strategy and enterprise AI as part of broader transformation programs.
  • RTS Labs — founder-led applied AI consultancy taking enterprise AI strategy through machine learning consulting to production.
  • Slalom Build — product engineering arm of Slalom, combining AI strategy with enterprise AI product delivery.
  • Thoughtworks — global technology consultancy with an AI strategy and enterprise AI practice built around its AI/works platform.

Browse by specialty: AI Strategy, Enterprise AI, Generative AI Consulting, Machine Learning Consulting, Healthcare AI, Data & Analytics and MLOps.

Smaller and regional firms

Not every useful consultancy is on the shortlist above. These profiles cover narrower or regional firms:

More profiles in the directory: ADC Consulting, Centric Consulting, CitiusTech, Master of Code Global, Miquido, Accedia, Braynex, Bridgeforce, 38shift, Hexaview Technologies, Numoru, Logiciel, Velvetech, Zynapse and Sirius AI.

Find firms by city and region

Cities with a single listed firm are a coverage fact, not a verdict on the market. Check where the delivery team sits before you rely on a headquarters city.

Regional pages: North America, Europe, Balkans, Asia and Latin America. The complete list is in the index of every city page.

Compare these firms side by side

Each page sets one firm against the featured partner, asaasin.ai, on the same fields: specialties, size, location and engagement style. The featured partner publishes this directory, so read them as fact sheets, not rankings.

All firms in one table: the full comparison table.

Before you reach out: a short checklist

  • Write down the use case and the metric that defines success before the first call.
  • Confirm whether the firm's engagement ends at strategy or continues through build and production support.
  • Ask for a reference client whose problem looked like yours, not just a logo wall.
  • Check the firm's specialty tags against your actual need — enterprise AI and generative AI consulting are not the same job.
  • Get the data ownership and IP terms in writing before you sign anything.
  • Narrow to two or three finalists and compare them side by side.