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In-depth Guide to AI Consulting & Top Consultants in 2024

Business adoption of AI is increasing due to the ability to access large volumes of data and the captured value from enterprise AI applications. COVID-19 pandemic has significantly accelerated the pace of adoption.

Source: KPMG

According to a 2021 survey by IBM and Morning Consult, one-third of companies have deployed AI and nearly half of them are exploring it. However, enterprises state these as 3 factors that constitutes a barrier to AI adoption:

  • limited AI expertise or knowledge
  • increasing data complexity and data silos
  • lack of tools/platforms for developing AI model

Moreover, AI failure rates are high. So, success is not guaranteed even if companies can overcome these barriers and implement AI technologies to their business processes.

Like other AI services, AI consultants can enable companies leverage the potentials of AI technologies by helping them to overcome the obstacles and minimizing the chance of failure.

What is AI consulting?

AI consulting is the business of helping companies use AI technologies to improve their businesses.

AI consultants can:

  • Formulate a well-defined business objective and determine whether an AI technique is the best option for achieving it.
  • Design, build, and deploy an AI application that fits your business objectives.
  • Provide employee training about AI technologies.

What are the typical AI consulting activities?

In general, AI consultants help businesses achieve AI transformation. However, consulting can be divided into 4 major categories, AI consulting is not quite different:

1- Strategy formulation

How should the client use AI? It’s necessary to understand the client’s strategy, challenges and opportunities faced by the company, client’s data & analytics capabilities. Combining these with an understanding of state-of-the-art AI, a consultant can identify the most important AI initiatives for the company.

In light of these initiatives, companies’ overall strategy also needs to be revised. For example, Business Process Outsourcing (BPO) companies generate significant revenues by processing invoices for other companies. These services revenues are at risk since invoice automation can be handled by AI technology.

Another example is a translation services company. Those companies need to make dramatic changes to their business to ensure that it survives in 5-10 years when Google translate reaches human level translation capabilities. It is helpful to have strategy sessions envisioning 5-10 years into the future, helping executives understand the future of AI so they can identify how their business needs to start changing today.

Artificial intelligence consulting services formulate strategy in these steps:

  • Understanding your company’s current status: Using solutions like process mining and analyzing the company’s strategy to understand the company’s current status.
  • Creating a portfolio of potential AI initiatives: This step involves identifying pain points and understanding how AI can contribute to the business.
  • Predicting the value of a project: Most AI projects fail to generate intended value. AI consulting firms help businesses predict the value of the project so that businesses don’t invest more than the expected outcome.
  • Choosing AI solutions and data sets to feed machine learning models: AI consultants should be aware of the abilities and limitations of each technology in the space. According to business needs, consultants choose the right AI solution and required data training sets for implementation.
  • Launching pilot projects: Consultants help launch initial small-scale projects to prove the viability of the idea.
  • Identification of scaling challenges and coming up with a solution: After analyzing the results of pilot projects, artificial intelligence consultants provide businesses with a roadmap regarding AI scaling goals.

For more, you can check our article on the components of a successful AI strategy.

2- Commercial due diligence

Though due diligence can be considered a strategy project, it is a special one. A good understanding of the AI market is necessary to conduct effective due diligence because success factors in AI are different than those of other fields. Consulting firms with a significant due diligence track record such as Solon are investing to establish themselves in this emerging market.

Evaluating the commercial success of an AI solution is different than other software mainly because:

  • The superiority of a deep-learning based AI solution requires having more or better labeled data than competitors. Any software improves as product owners learn from usage patterns. However, in the case of AI, the accuracy of the model predictions improve with more data which is unique
  • Evaluating data science teams is different from evaluating engineering teams. For example, academic credentials can be more important for data science teams compared to typical software engineering teams

Therefore, companies are investing in AI-specific due diligence capabilities. These include understanding and evaluating data sources relevant for AI models, formulating fast approaches to benchmarking different AI vendors’ solutions and getting familiar with AI-related academic and work credentials.

3- Implementation

The strategy will result in a number of initiatives. Implementation should also be considered as multiple activities such as planning, vendor selection if needed, project management, development, improvement of business processes impacted by the project, change management and so on.

As with any consulting service, some or all services can be completed by consultants. Or implementation can be in-house and in most cases it is in-house. However, for example, if the client lacks the tech know-how to implement urgent initiatives, starting with consultants can help the client progress faster. However, please bear in mind that, in the long run, relying on consultants completely for implementation will likely be more expensive than completing those activities in-house.

4- Training

Ideally, consulting projects should improve the culture and skills of the client. This is especially relevant in the field of AI where talent is scarce. AI consulting projects need to ensure that client teams are capable and knowledgeable about the technologies they will be working on. There needs to be well documented and organized training materials and an established knowledge transfer process.

Artificial Intelligence Consulting Landscape

A major distinction between AI consultants is their area of focus. While some offer end-to-end consulting services, only AI-focused consultants are also entering this industry.

Tech consulting companies

IBM pushed AI into the spotlight with DeepBlue winning against the world champion in chess and Watson winning against Jeopardy! champions. IBM also invested in AI consulting. In 2018, it launched IBM Data Science Elite as a data science/AI consultancy division.

Accenture also has an advantage in the AI consulting space with its large, tech-focused consulting team.

Top management consultants – MBB

Traditional consulting firms such as MBB (McKinsey, BCG, Bain) have been active in the strategy side of things for a long time, but as the greater dependence on data continues, companies’ focus will likely to shift towards artificial intelligence. So this raises the question of whether consulting will be able to survive without artificial intelligence implementation or not. Those two industries will likely to become more interlinked because of the advantages of a possible partnership. There are numerous acquisitions and investments from consulting firms into AI companies such as McKinsey’s investment in SparkBeyond and BCG Gamma’s launch of

Consulting firms are also trying to achieve thought leadership in how AI will transform the enterprise. They are focusing on AI applications, educating executives on AI and identifying limits of AI:

  • McKinsey: The firm regularly publishes about AI relying on their AI work with clients. Their executive’s guide to AI summarizes the technical side of AI
  • BCG also has been publishing extensively on AI. They examine cross-industry AI adoption annually in partnership with MIT Sloan Management Review. Their 2021 study is about the cultural benefits of AI in the enterprise.

Big 4 accounting firms

Though launched as accounting companies in the early 1900s, Big 4 (Deloitte, PwC, EY and KPMG) have been running consulting businesses for >50 years. However, their prices and in some countries scope of their consulting activities have been limited compared to other consulting companies.

The growth in AI gives them a chance to establish a strong practice in an emerging area. AI is a technology with implications for many business areas where talent is still scarce. Big 4 accounting firms are some of the largest employers in the world and they have deep enough pockets to make large investments in this space and they have the business development know-how and resources to make partnerships across the AI ecosystem to deliver end-to-end services.

Cloud service providers

These are the companies like Google, Microsoft and Amazon. They are the leading players in cloud compute, storage and networking. Their expertise in these fields gives them a greater chance for transferring their technical knowledge into meaningful solutions. Their teams have gained substantial expertise in handling massive amounts of data through their specific cloud architecture, and for a data-intensive activity like artificial intelligence, they can provide the right advisory for their clients. Google through their Advanced Solutions Lab provides both training sessions for their clients and channels their engineers to design a custom project.

(Courtesy of CNN)

End-to-end AI solution providers

These are tech companies that have experience in building AI/ML systems. They also tend to have a few staff that can support companies in identifying AI use cases. This is a lean model, strategy formulation and use case identification are not manpower intensive. These companies can serve multiple clients with relatively small teams focusing on the business side of AI.

For a prioritized list of these companies, feel free to visit AIMultiple’s list of AI consultants and data science consultants on our website.

What are some example case studies?


Kraft Heinz

Kraft Heinz is a consumer packaged goods company and they needed new ways to innovate, test, deploy minimal viable products (MVPs) quickly. With the IBM Garage tool and IBM experts’ consultancy, Kraft Heinz created a new framework that aims to achieve rapid ideation, prototyping and testing. One of those innovative products is LEGO which is an AI-powered algorithm that helps field sales teams understand store performance or identify growth opportunities. When products run low, LEGO sends notifications to field sales in real-time so that Kraft distributes each product more quickly and efficiently to stores and restaurants around the world.

Bradesco Bank

Bradesco Bank is one of the biggest banking and financial services companies in Brazil with over 5,200 branches. Branch managers used to call the headquarter when they had questions about products or services. However, this was causing long waits on the phone while the clients were waiting in the store.

To prevent this undesired customer experience journey, Bradesco Bank partnered with IBM and implemented IBM Watson to answer questions. The main challenge of implementation was language, IBM helped the bank to feed Watson with Portuguese questions and words. The bank first tested Watson in some branches until they were satisfied by responses and then scaled it within the enterprise.

Now, Bradesco Bank claims that Watson is trained on 62 products and answers 283,000 questions a month with a 95% accuracy rate, with 5% requiring calls for further assistance. It also reduced the time-to-response to a few seconds from 10 minutes.

How to choose your AI consultant?

Of course, deciding on which firm to hire depends on many factors; but here are three major questions you need to ask:

  • Is it really necessary? That should be the question you need to start with. There are many publications indicating the potential gains from implementing the solution, but is it going to be a positive return in the short run? You should ask your consulting about her projections for the short-run, medium-run and the long-run. Maybe it would be wiser to implement some other technology for the short-run if the firm is in the early growth stage or there are much more important opportunities to invest in.
  • Do you have the necessary human capital? After the solution scheme is provided it would also be important to decide on doing the project in-house or outsource it. You should always make sure that the people with rights skills deal with the issue so that your employees would have a greater likelihood to learn something from the process and, can help you in later stages. Thus your team’s skill level will make it easier or harder to evaluate the performance of the consultant. So that, there would be constant sharing of information to ensure that state of the art solution is implemented.
  • Does the consultant have the necessary experience? Right now, there are many small size artificial intelligence consulting firms. Depending on your industry you need to make sure you selected the right vendor. Different industries need different types of skill sets. The vendor’s past projects would be the greatest source of information. The profile of the team also matters. It is quite likely that people with advanced degrees have the capability to ensure the highest quality of work. The different consulting firms have different expertise, one can have the best team to do text classification and the other can be good at object detection. 

How do AI consultants price their services?

Some AI consulting companies that also have their own AI products provide AI consulting for free to boost sales. It is common for tech companies to add complementary services on top of product sales or to provide free PoCs to gather new customers. This is a more structured extension of such approaches and is successfully implemented at IBM where it led to 130 engagements at 115 companies in a year.

Time and material based: Most AI consulting projects, like most consulting projects, are priced based on the time and materials necessary for the project as estimated by the consultancy. This is negotiated at the beginning of the engagement.

Success based: Some consulting projects are success-based and there have been efforts to implement this in AI consulting as well. Even though success (or milestone) based projects seem to align consultants’ and clients’ interests, they create uncertainty, are still imperfect measures that are hard to measure resulting in inefficiencies.

  • Uncertainty is a big issue because no client wants to be in the dark about how much they need to pay for a consulting project. Though limits on minimum and maximum fees could be negotiated, uncertainty about the payment amount will remain.
  • Most metrics do not measure success accurately. For example, if a company runs a project to boost its sales and experiences no sales boost after the project, that may not mean that the project is unsuccessful. A myriad of factors such as seasonality, an unexpected recession, churn of a sizable portion of the workforce could all lead to flat or declining sales after a successful project to boost sales.
  • Measurement of success-based fees is complex as it relies on metrics to be measured by the client or the consultant. Minor measurement errors can lead to significant changes in fees that need to be paid.

What is AIMultiple’s approach to AI consulting?

AIMultiple writes about others’ solutions since we can be more objective. However, AI consulting is an area that we are passionate about. As the AIMutiple team, we are one of the few who have extensive experience in working with AI solution providers and explaining AI solutions to businesses. Since we don’t have a global network of senior partners to feed, we are also quite cost effective. AIMultiple implements only 1 type of project: Identifying AI application areas in a company’s specific business. We have a 3 step process that requires minimal involvement from the company:


  • Research the company and its industry
  • Understand its priorities and strategy from off-the-shelf documents shared by the team
  • Prepare a list of AI transformation initiatives prioritized by their impact and strategic fit


  • Talk to business and tech teams to get their feedback and additions to the list of AI use cases or initiatives.
  • Share findings with the project sponsor or C-suite to get their sign-off for top projects


  • Identify potential startups, suppliers and partners to accelerate implementation
  • Identify schedule, KPIs and roles for project setup
  • Oversee project implementation. PMO is high on effort and low on required expertise so we usually prefer not to take on the PMO part of projects. MBB, Big 4 and others have plenty of junior consultants they can throw at PMO projects to ensure adequate monitoring and coaching. 

What is the future of AI consulting?

We see two trends shaping the industry:

Rise of AI-focused consultants

The largest consultancy of the internet era, in terms of the number of consultants, is Accenture which is focused on software consultancy & implementation. As we have seen with acquisitions like QuantumBlack and initiatives like BCG Gamma, established consulting companies take AI seriously. However, we see an innovator’s dilemma here:

  • Established companies in general and consultancies can not easily reduce prices as this would cannibalize their existing products
  • When you have a hammer, everything looks like a nail. Consultancies have a lot of industry experts and resources trained to do manual data analysis. It is difficult for such organizations to embrace machine learning in insight generation and automation of analytics.

Based on these, we expect specialized, machine learning focused consultancies to grow while established consultancies remain sources of expensive AI implementation that only the most profitable companies can rely on.

Continued influence of startups driving consulting projects

Startups have significant influence in emerging areas like AI. This may mean more work for consultants as startups tend to partner with consultants to promote and integrate their solutions.

At AIMultiple, we see that AI vendors are becoming highly specialized and provide industry-specific solutions. But it is relatively early to make accurate predictions, tech giants could easily dominate AI solutions by buying off AI startups and hiring researchers as they have been doing for the past year. 

Traditional Consulting in a Post AI World

We discussed how AI consulting works. It is also worth considering what will happen to traditional consultants as AI becomes widely adopted. In our research, we looked at how unique selling points of consultancies will be disrupted by the rise of AI and why we expect consulting, especially the business of traditional management consultants to shrink in the future.

For more on AI,

If you identified your AI challenge and are looking for the right AI consultant for your company, don’t hesitate to contact us:

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You can also check out our whitepaper on custom AI development:

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Access Cem's 2 decades of B2B tech experience as a tech consultant, enterprise leader, startup entrepreneur & industry analyst. Leverage insights informing top Fortune 500 every month.
Cem Dilmegani
Principal Analyst
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Cem Dilmegani
Principal Analyst

Cem has been the principal analyst at AIMultiple since 2017. AIMultiple informs hundreds of thousands of businesses (as per similarWeb) including 60% of Fortune 500 every month.

Cem's work has been cited by leading global publications including Business Insider, Forbes, Washington Post, global firms like Deloitte, HPE, NGOs like World Economic Forum and supranational organizations like European Commission. You can see more reputable companies and media that referenced AIMultiple.

Throughout his career, Cem served as a tech consultant, tech buyer and tech entrepreneur. He advised businesses on their enterprise software, automation, cloud, AI / ML and other technology related decisions at McKinsey & Company and Altman Solon for more than a decade. He also published a McKinsey report on digitalization.

He led technology strategy and procurement of a telco while reporting to the CEO. He has also led commercial growth of deep tech company Hypatos that reached a 7 digit annual recurring revenue and a 9 digit valuation from 0 within 2 years. Cem's work in Hypatos was covered by leading technology publications like TechCrunch and Business Insider.

Cem regularly speaks at international technology conferences. He graduated from Bogazici University as a computer engineer and holds an MBA from Columbia Business School.

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karoline steward
Mar 17, 2021 at 10:37


Your blog was very informative!
The most refined data shows that artificial intelligence’s market size was value at $27.23 billion in 2019 (Fortune Business Insights, 2020). This figure has predicted to reach $266.92 billion by 2027—a nearly tenfold increase in just eight years and a Compound Annual Growth Rate (CAGR) of 33.2 percent.

I would also like to address you with the Top AI-based online Invoicing software for consulting firms with this little information.
INVOICERA-Custom Consultant Billing Software
Your time is worth a thousand pounds! Don’t let inaccurate calculations lose your money. Focus on consultations and Invoicera will track your time efficiently and then convert it into invoices directly.


Cem Dilmegani
Mar 17, 2021 at 22:00

For a company that claims to use AI, your comment bot is not very refined.

Aug 09, 2020 at 14:38

I think it’s silly not to include Nuance consulting services to this list. Don’t you think?

Cem Dilmegani
Aug 09, 2020 at 19:08

Hi Arun, we have not heard about them in our interactions. They can reach out to us if they want to explain their services

Al Gharak
Jan 26, 2020 at 00:07

Do you have any recommendations on training and/or educational resources that can help hands-on AI developers gain exposure to the strategic consulting angle?

May 27, 2020 at 20:40

There are too many companies chasing AI talent. For those with a background in computer science and statistics, IMHO the best hands-on experience would be working in an AI company.

Dec 04, 2019 at 18:32

Nice article

Oct 09, 2019 at 12:12

That’s a complete guide to cover this subject, awesome job! GoodAI Consulting is great company, heard many positive reviews on them, they definitely know what they are doing. I think it’s important for any business to consider implementing AI to their processes these days. But to start an Artificial Intelligence and Machine Learning transformation, the right consultation is required, and I can’t imagine better place to start searching for AI consulting company other than this article!

May 31, 2020 at 09:09

Thank you

Adrian Munguia
Sep 20, 2019 at 16:06

Very good article. Certainly gives a clear idea of what to expect. I’ve worked with Fortune 500 and startups as an AI Consultant for many years. There is always a feeling that we do “magic tricks” that are hard to manage and understand. Training the in-house talent to adopt these technologies should be a priority.

-Adrian Munguia

Sep 19, 2019 at 14:41

Great post!
My company – Radicalbit – developed a platform to accelerate and operationalize AI deployment

GK Palem
Aug 15, 2019 at 05:04

Summarizes the current state of AI consultations. As others pointed, however, the state of Artificial Intelligence to benefit the businesses can be divided into generic AI and specific machine learning techniques that are powering the driver-less cars etc. initiatives. Nice summary.

Thank you,
AI Consultant

May 10, 2019 at 16:31

Good article!

Apr 29, 2019 at 23:39

Interesting post, and I am firmly of the opinion that AI consulting with ultimately blend into technology consulting within various sectors. I am a doctor by training, and have founded DeepHealth here in Sydney (and also KL, Jakarta and Auckland) to try and address the growing need for AI strategy and implementation within healthcare. We are a small boutique firm, with a focus on the healthcare sector. Check us out if you want:

Apr 19, 2019 at 11:21

AI Consulting is a growing industry for SMEs. Not every company can afford to hire the huge players to help them and some consultancies are more specialist. But, AI is not just about Machine Learning, companies like are U.K. Based consultancies who specialise in Optimisation Algorithms that have multitudes of real world applications. Machine Learning always grabs the headlines but for companies looking to solve the hugely dimensional problems that are often present in finance, medicine, engineering etc then it is an Optimisation specialist consultancy that you need.

Mar 08, 2019 at 15:45

Great info. Thanks.

Aug 30, 2018 at 14:08 is an APAC (ANZ) focused AI Consulting Firm. I suppose most of these larger firms are from the USA.

Warren Zafrin
Apr 29, 2018 at 15:39

I think this needs to be updated. AI is moving into sub speciality. @ UHY my team and I are focusing on Cyber Crime, AML and Cyber

May 16, 2018 at 12:31

I think there are 2 types of consultants leveraging AI:
1- Generalist AI consultants helping companies identify how they can use AI in their business.
2- As you said, there are consultants that already offer services in areas like AML that learnt about AI to improve their services.
We are not covering the second group in this post yet but we plan to either cover the topic on a separate post or on this one.

learning alphabets
Jan 18, 2018 at 07:16

good information..

May 16, 2018 at 12:25