What is AI consultancy? What does an AI consultant do?
We are in an AI boom. Artificial intelligence is transforming industries with its ability to automate processes, save costs, identify business risks, and provide insights. Every software or platform business is likely to find its way of operating transformed within the next five years. Companies which can adapt quickly to AI technologies are likely to benefit from the AI boom, just as companies which adapted to the internet were able to thrive in the dot-com boom.
If you are looking to integrate AI into your business operations, you may be considering hiring an AI partner or AI consultancy to help your organisation transition to AI.
Fast Data Science - London
Fast Data Science provides a platform-agnostic AI consultancy/AI partnership service. We will listen to your business needs and help your business adapt your AI abilities, avoiding vendor lock-in, to enhance operational efficiency and decision-making. AI consultants bridge the gap between complex technologies and real-world applications.
AI doesn’t have to mean generative AI solutions like ChatGPT. There are often lower cost and simpler alternatives. For example, we could train a customer spend or customer churn model on your in-house data, to gain insights (what drives customer spend, what drives attrition), or even anticipate customers that are likely to switch to a competitor.
An AI consultancy engagement may vary in scope and we may be contracted only to analyse the data, or to help a client go out to tender, or produce an end to end solution. No two AI consultancy engagements are the same. You can navigate the journey of integrating AI into your organisation with our proven four-stage framework, designed for clarity and impactful outcomes.
After signing an NDA, Fast Data Science explores your existing data landscape. We identify all relevant data sources, and assess the data quality, consistency, and completeness. We aim to understand any existing data governance, and evaluate its readiness for AI applications. We uncover what data you have, where it lives, any privacy restrictions, and its potential.
Once we understand your data, we work with your stakeholders to pinpoint specific business challenges and opportunities where AI can deliver significant value. This stage focuses on brainstorming, use case generation, and aligning AI potential with strategic business goals. Depending on your organisation's industry and focus, you may be interested in customer retention, churn prevention, or even anticipating and predicting "grey swans" - expensive but rare events, such as wind power turbine failure, litigation, construction defects, customer complaints, regulatory fines, and other undesirable and unwanted events in your industry.
Not all opportunities are created equal. We help you prioritize the identified AI initiatives based on potential impact, feasibility, required resources, and alignment with your organizational objectives, ensuring you focus on the projects with the highest ROI. We plot the opportunities on an opportunity canvas (like at the top of this page) with technical effort on one axis and value to the business on the other axis.
Depending on your needs, we either assist in preparing comprehensive Request for Proposal (RFP) documents to procure external AI development services, or we design and oversee the technical implementation of the chosen AI solutions in-house, or we develop it ourselves. You don't need to decide on the final option at the beginning of the engagement.
AI consultancy is ideal for businesses that lack in-house AI expertise or need strategic insights to stay competitive in the evolving market. Below is a summary of some of the tasks that an AI partner could assist your business with.
| AI consultancy task | Description |
|---|---|
| Assessment and analysis | Identifying business areas where AI can make the most impact. |
| Data exploration | Under NDA, analyse the quality and potential of the in-house data. |
| Strategy development | Creating a roadmap (AI strategy) to align AI initiatives with business goals. |
| Solution implementation | Building predictive models, chatbots, or AI-enhanced tools. For example, for predicting employee churn, customer churn, customer complaints, or clinical trial failure. |
| Machine learning model deployment | With consultants onboard, companies can accelerate the adoption of AI technologies. |
| Monitoring and optimisation | Ensuring AI systems deliver consistent value post-deployment. |
| Ethical guidance | Navigate regulatory and ethical challenges, such as data privacy, GDPR, HIPAA and algorithmic bias. |
| Fractional head of AI | Fast Data Science can provide a fractional head of AI on a retainer basis. This is similar to the role a CTO would play, but focused on AI. |
| Due diligence and expert witness work | Analysis of target companies in technology related acquisitions, and expert witness statements and depositions for civil litigation. The Director, Thomas Wood, has completed the Cardiff University Bond Solon training for expert witness work in England and Wales. |
We are a team of experienced AI consultants and between us we have worked for small companies, medium sized businesses and some of the world’s largest multinationals. Below you can see a selection of some of our past consulting engagements. You can find out more by reading our case studies. Click through the carousel below to see an overview of some of our interesting AI consulting engagements.
An open-source, NLP and generative AI-driven tool for harmonising questionnaire items, even across different languages, developed for the Wellcome Data Prize in Mental Health. Try Harmony online.
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Foreflight provides a powerful mobile app used by commercial pilots for flight planning and in-flight naviation. It is an electronic flight bag which runs on iOS and iPadOS devices. We analysed Foreflight's customer database to identify any users likely to churn (cancel their subscription).
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The Office of Rail and Road (ORR) is the British national rail regulator, responsible for health and safety on mainline rail, the London Underground, light rail, and trams.
Fast Data Science built a drag-and-drop dashboard which allowed internal users at the ORR to analyse data collected on train delays, flooding, accidents, construction, etc, and build machine learning models on the fly.
Learn MoreA Natural Language Processing-powered tool developed for the Bill and Melinda Gates Foundation, assisting experts in estimating the risk of a clinical trial ending uninformatively. The Clinical Trial Risk Tool also reads a clinical trial protocol and creates an itemised per-subject budget from the schedule of events, looking up costs in hospital charge masters. Try the Clinical Trial Risk Tool.
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For a number of large pharma multinationals, we have been developing natural language processing models to redact sensitive data (PHI) or commercially sensitive information from clinical trial narrative reports, protocols, statistical analysis plans, synopses, ICFs, and other documents.
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Tesco is the UK's largest grocery retailer with over 15 million regular shoppers. We developed machine learning models to predict the amount in kilos that a shopper will put in their basket, as well as the turnaround time of delivery vehicles, in order to improve route optimisation and driver rostering.
Learn MoreWe take on generalist AI consulting engagements and we also have a particular focus on natural language processing, which is the area of AI that deals with processing information in human languages. If you are in an industry with large amounts of unstructured data stuck in documents, PDFs, audio files, scanned documents, or similar (such as pharmaceuticals, legal, or insurance), then you should definitely give Fast Data Science a call.
Above: an introductory video about natural language processing consulting at Fast Data Science.
Generally we have found that most clients use either Microsoft Azure, AWS, or Google Cloud Platform. A small number have used in-house hosted solutions rather than cloud solutions, or even on-premises or on-device apps. We can work with whatever technology stack suits your needs. We are not tied to any large cloud provider and do not receive kickbacks from any of them.
Most machine learning is conducted in Python nowadays by a large margin, however some clients have used other non-Python frameworks such as Spark or C#. We have experience with all the major large language model providers, such as OpenAI, Gemini, Claude, DeepSeek. We also work with more traditional off-the-shelf machine learning libraries such as Scikit-Learn, and we will not use large language models (LLMs) superfluously. We have even fine tuned our own LLMs in the past.
AI consultants can take on any number of tasks around easing the transition to AI in your organisation. Whether you’re part of a large enterprise or a small startup, AI consultants help bridge the technical and strategic gap.
AI consultants begin by evaluating the client’s business operations, identifying areas that can benefit from automation or predictive modeling. This involves data audits and understanding pain points in workflows.
Consultants begin by evaluating the client’s infrastructure and identifying areas for AI intervention. They recommend tools, frameworks, and processes tailored to the business’s needs. For example, natural language processing (NLP) might be used to enhance customer service chatbots.
Consultants help businesses implement AI tools like recommendation engines, computer vision systems, or NLP chatbots. They also provide technical support during and after the deployment phase. Their role ensures smooth integration with existing business workflows.
AI consultants provide training to internal teams, helping them manage new systems. They also offer technical support, ensuring that AI tools are effectively utilized.
Post-implementation, consultants monitor the AI models to ensure they meet performance expectations. They make necessary adjustments to improve accuracy and efficiency over time.
AI consultants advise businesses on best practices to mitigate ethical risks, such as algorithmic bias and data privacy concerns. They also ensure compliance with regulatory frameworks.
Let’s consider Fast Data Science, a consultancy that specializes in NLP solutions. They provide tailored AI tools for businesses, demonstrating how AI can improve operations with minimal disruption. Their approach includes:
Offering end-to-end AI solutions, from initial assessments to deployment.
Fast Data Science ensures seamless integration by identifying AI opportunities, designing models, and supporting businesses throughout the implementation process to maximize efficiency.
Providing detailed NLP models for enhanced business communication.
Their NLP solutions power chatbots and automated systems, improving customer interactions and internal workflows through natural language understanding and sentiment analysis.
Ensuring solutions are ethically sound and comply with industry regulations.
The consultancy prioritises data privacy and bias detection, aligning their models with regulatory standards to foster trust and transparency in AI applications.
By adopting a similar approach, you can position your AI consultancy for success.
The AI consulting industry is rapidly expanding as companies strive to adopt and scale artificial intelligence technologies. The leading consulting firms, such as IBM, Accenture, and Deloitte, are at the forefront of this revolution, offering tailored AI solutions for businesses across various sectors.
| Company | Core AI Services | Special Focus Areas | Notable Projects/Clients |
|---|---|---|---|
| IBM | AI strategy, NLP, automation, data analytics | AI-powered HR operations, conversational AI | ABN AMRO, Watson AI for healthcare |
| Accenture | Intelligent automation, machine learning, NLP | AI-driven digital transformation, Gen AI | Microsoft, Volkswagen, 80,000 AI employees |
| Deloitte | AI governance, analytics, automation | Generative AI solutions, AI in operations | 75,000 employees using internal AI chatbot |
| PwC | Data engineering, ML, digital twins, responsible AI | Intelligent automation, healthcare solutions | Pfizer, AI for regulatory compliance |
| EY | Robotic process automation, analytics, digital services | Unified AI platform (EY.ai), AI-powered finance | Various sectors across 150 countries |
| McKinsey & Co. | AI strategy, simulations, large-scale optimization | AI-at-scale solutions, QuantumBlack division | Emirates Team New Zealand, Formula 1 |
| TCS | IoT, automation, ML-based insights | Big Data solutions, Machine-First delivery | Utilities, financial institutions |
| BCG | ML, optimization, AI in operations | AI in supply chain, organizational change | Microsoft, logistics companies |
| Infosys | Data analytics, automation, responsible AI | AI-powered customer data platform | ABB, Telstra, Pfizer |
| UST | Data insights, seamless automation | Real-time analytics, ML for operations | Various manufacturing and IT sectors |
The following chart provides an overview of the market value (by revenue) of the top AI consulting companies in 2023:
Chart showing market value (by revenue) of the top AI consulting companies in 2023. Dataset source: https://aimagazine.com/top10/top-10-ai-consulting-companies
AI consultancy is rapidly gaining traction, and here’s why:
AI adoption is increasing across industries, with 42% of enterprises already leveraging AI in some capacity. Businesses are eager to integrate AI tools like predictive analytics, chatbots, and computer vision systems, as they seek data-driven solutions to stay agile in fast-changing markets.
AI consultants help businesses automate repetitive tasks, enabling employees to focus on core activities. This leads to improved productivity and operational efficiency, while also reducing costs associated with manual processes and minimizing human error.
By implementing innovative AI solutions, businesses can stay ahead of competitors. For example, predictive analytics enables companies to anticipate market trends and adjust their strategies accordingly, helping them capitalize on new opportunities before others do.
AI tools like chatbots and recommendation engines enhance customer interactions by providing timely and personalized responses. This not only boosts customer satisfaction but also increases brand loyalty, as customers feel valued through more meaningful and efficient interactions.
Starting an AI consultancy business requires a combination of technical expertise, business acumen, and effective networking. Here’s a step-by-step guide:
First, make sure you have a strong background in AI technologies, including machine learning, data science, and automation tools. If you’re lacking in any specific area, consider taking specialized courses in AI or obtaining certifications from platforms like Coursera or edX. Being an expert in just one field (e.g., NLP, computer vision) can also be an advantage, as niche markets often have less competition.
While general AI consultancy can be lucrative, identifying a specific niche like healthcare AI, financial automation, or supply chain optimization allows you to build deep expertise and credibility in that area. This makes it easier to market your services to a targeted audience. For example, some consultancies focus solely on helping hospitals use AI for medical image analysis, while others may specialize in AI-driven fraud detection in banking.
Develop a detailed business plan that outlines your services, pricing model, and target audience. Include a roadmap with measurable milestones for growth. Write a comprehensive business plan that includes:
A solid plan will help you stay on course and secure any necessary funding.
Establish relationships with key players in the AI field. This could involve partnering with AI vendors, collaborating with universities, or even building a team of data scientists and AI engineers. Networking helps you stay updated on the latest advancements and also opens doors for potential projects.
Your consultancy’s MVP might include:
Build a strong online presence through a website and LinkedIn profile. Regularly post blogs, case studies, and whitepapers that demonstrate your expertise. Share examples of your past successes and emphasize how you’ve helped businesses implement AI to achieve their goals.
To stay competitive, AI consultancies need to keep pace with emerging trends. Here are some trends to watch:
NLP is transforming industries by enabling chatbots, sentiment analysis, and text summarization. Companies specializing in NLP, like Fast Data Science, are helping businesses enhance customer interactions and automate repetitive tasks, reducing human involvement in customer service and improving response time.
With growing concerns over AI biases, consultancies focusing on ethical AI will be in high demand. Consultants must ensure that AI solutions are fair, transparent, and compliant with regulations, minimizing risks of reputational damage and building consumer trust through responsible AI practices.
Predictive analytics is becoming essential for forecasting sales, inventory, and customer behavior. AI consultancies play a key role in developing models that help businesses make data-driven decisions, enabling organizations to optimize resources and stay ahead of market trends.
Automation remains a priority for businesses looking to streamline operations. AI consultancies help implement RPA(Robotic Process Automation) solutions that reduce manual tasks and increase efficiency, freeing up employees to focus on strategic roles that drive innovation and growth.
AI is revolutionizing healthcare with tools for predictive diagnostics and medical image analysis. Consultancies focusing on healthcare AI are helping providers improve patient outcomes and operational efficiency, while also enabling faster and more accurate disease detection with minimal human intervention.
An MVP is a great way to test your consultancy’s potential. Here are some ideas to get you started:
Offer audits where you evaluate a company’s processes and identify AI opportunities. This can help businesses understand whether they are ready for AI integration, while also giving you insight into areas that might require further preparation or restructuring before adopting AI solutions.
Help companies build small-scale AI solutions, like a simple chatbot or automated email sorting system. This helps demonstrate the potential impact of AI without a full commitment to large-scale projects, providing businesses with a low-risk way to explore AI capabilities and build internal support for broader initiatives.
Host workshops on AI fundamentals, such as machine learning for business or NLP for customer service. This is a great way to build relationships with potential clients and establish yourself as an expert, while also empowering participants to become advocates for AI adoption within their organizations.
Start with a small project, like implementing predictive analytics for one department of a company. Show measurable results to encourage broader adoption of AI across the organization, making it easier to secure buy-in from stakeholders for future, larger-scale AI initiatives.
Fast Data Science - London
Marketing plays a critical role in growing your consultancy. Consider the following strategies:
Regularly publish blogs, case studies, and whitepapers to demonstrate your expertise. Platforms like LinkedIn are ideal for sharing thought leadership content. Consistent content creation not only builds your online presence but also helps attract inbound leads by showcasing your knowledge and success stories.
Showcase testimonials from satisfied clients to build credibility. Positive feedback can significantly influence prospective clients. You can also highlight case studies with tangible results to illustrate how your consultancy has delivered value, making your offerings more appealing to potential customers.
Collaborate with technology providers and educational institutions to expand your offerings and enhance credibility. Partnerships with trusted industry leaders provide access to new markets and tools, while collaborations with universities allow you to stay updated with the latest AI research and trends.
AI consultancy offers a structured approach to adopting AI technologies, helping businesses stay competitive and innovative. As companies increasingly explore AI solutions, the demand for expert consultants will continue to grow. Whether you’re looking to hire an AI consultant or start your own consultancy, understanding the intricacies of this field is crucial.
Fast Data Science, a leader in AI consulting, empowers businesses to transform operations through innovative AI solutions. Our AI consultancy specializes in navigating the complexities of artificial intelligence adoption, offering end-to-end services tailored to diverse industry needs.
From strategic planning to deployment, we bridge the gap between technology and business value, ensuring seamless integration of predictive analytics, NLP, and automation tools. As one of the premier artificial intelligence consulting companies, we’ve delivered impactful projects, such as the Insolvency Bot for legal Q&A and predictive models for the NHS, showcasing our ability to extract insights from unstructured data. Our artificial intelligence consultancy process begins with data discovery workshops, followed by opportunity prioritization to identify high-ROI initiatives.
We provide hands-on artificial intelligence consulting, leveraging cloud platforms like AWS and Azure for scalable solutions. With 42% of enterprises adopting AI, businesses seek trusted partners to stay competitive. Fast Data Science’s AI consulting ensures measurable outcomes, cost efficiency, and enhanced decision-making, positioning us as a leader among artificial intelligence consulting companies. Founded by Thomas Wood, our team delivers practical, jargon-free results, driving profitability and innovation since 2016.
Get in touch with us today and let’s discuss your AI consultancy needs!
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