Welcome to the MediaGamma blog

The gap is widening between those with a handle on their AI strategy and those only scratching the surface of its potential.

AI in-house talent vs consultancies: what's right for your business?

Posted by Victor Malachard

AI in-house vs consultancies

AI in-house talent vs consultancies: what's right for your business?

Businesses across sectors are scrambling to capitalise on the value of AI right now, with usage growing by as much as 270% in the last four years alone. Despite this influx, it can be hard to get started here, or to know which of the many arising AI implementations is best. Still, with predictions widely pointing to the fact that 80% of technologies will have AI foundations by next year, getting your head around the issue should be a primary concern. 

Unsurprisingly, demand for AI talent has doubled in the last two years, and it looks set to rise further as we enter the tech-centric decade that is 2020. On a basic level, turning your attention here will see you facing two primary choices for implementation — build an in-house team or bring on consultants. You could also choose to take a hybrid approach, which integrates the benefits of both methods. The chances are that you’ll even come across AI alternatives during your research, including MLaaS (machine learning as a service) and APIs (application programming interfaces), but developing a fundamental basis of AI understanding is usually best before attempting these more focused implementations. In-house vs AI consulting are the dual choices that you need to understand. 

Here, we are going to break down the benefits of each approach and help you make the right decision for your business. 


AI in-house teams: what you need to know

With AI already at the heart of processes for 29% of businesses and set to continue rising, in-house teams can be an appealing option. While this approach isn’t without setbacks, many businesses manage to make it work. But, how exactly do you know whether in-house intelligence would be your best option?


An in-house AI team could be for you if…

  • You want skills on-demand

In-house teams offer fast solutions — once established. You’ll be able to take action on new tech in seconds, as well as ensuring there’s always someone on-hand to troubleshoot and address AI issues as they arise. 

  • You’re looking for long-term investments

An in-house AI team can cost anywhere between £250,000-£500,000 a year. That’s no small investment, but it’s money that brings a certain level of assurance. With adequate training and job focus, in-house team members could become lucrative for you in the long-term as skills rise but not necessarily pay brackets. 

  • You need a solution that will change with your business

The real benefit of building an in-house team is having access to people who understand AI and are deeply ingrained with your business. Although consultants will get to know your business (and may have a better understanding of AI technology), they won't have the same kind of long-term expertise that an in-house team can develop regarding the intricacies of your operation.  


You shouldn’t hire in-house if…

  • Your funds are limited

With high annual price points, an in-house AI team is off the cards for startups, small businesses, and even some medium enterprises. This is especially the case with wide-scale AI integrations still in their infancy. Predictions may point towards AI increasing profits by as much as 40%, but that isn’t guaranteed.

  • You need a comprehensive AI skillset

If you’re working with multiple AI applications, a wide-ranging skillset is fundamental. Sadly, that will be hard to get with in-house employment, where individuals will only be able to apply broad focuses to specific challenges, and may not always be able to address issues at all. 

  • You need immediate AI assistance

AI waits for no business, yet hiring in-house is a lengthy process that could see you without for at least a few months. An in-house team can offer rapid response once established. But if you want AI help today, looking to jump-start that project with consultants is your best option. Without access to consultants, your AI processes could stall to a fatal degree, allowing your competitors to swoop in and take the AI air from under your wings. 


The good - 

  • A nuanced service specific to you
  • Skills on your doorstep — once a team is established 
  • Investments that last

The bad - 

  • Expensive
  • Potentially limited expertise
  • A long hiring process that can delay the start of your project 


AI consultancies: what you need to know

On the flip side is the possibility of outsourcing with an AI consultancy. Third-party solutions are incredibly popular right now, and managers find that these are the most workable solutions in the majority of cases. This is mainly because a consultancy will be ready and waiting to improve AI and implement even complex services with insider know-how. The question is, why should you let someone else in?


AI consulting could be for you if…

  • You’re seeking fast results

AI has already taken the business world by storm, and experts predict that it will lead to an almost entire reinvention of most systems within 15 years. With this in mind, speed is of the essence when it comes to implementation, and an AI consultancy can match that need like no one else. From the moment you reach out, you’ll be able to utilise a broad talent pool, often on a 24-hour basis. Forget employment processes, training, and the rest. AI will be at your fingertips within days.

  • You only want to pay for what you use

All AI consultancies offer different payment structures, but many give the choice of either paying by subscription or per job. In both instances, you’ll pay for talent as you need it, rather than on an ongoing basis. Undeniably, costs will still add up, but those are expenses you should easily be able to cover as your profits upturn as a result.

  • You’re looking to scale on-demand

Scalability within AI implementations is an absolute must, yet it can be difficult with small teams and limited expertise. By comparison, a wider-reaching AI consultancy will be able to continually observe and improve processes. They’ll also have access to increased  knowledge and software, allowing you to scale up whenever you feel the need. This is particularly true if looking to bring onboard area specialists to devise highly-specialised systems.  

  • You want real expertise

The big thing that consultancies offer is expertise. By partnering with a consultant, you will often be able to gain access to talent for a short period of time that you could never afford full time. With in-demand skills, the best people generally don’t want to be tied down. Although your in-house team will understand your business better — they will likely be outclassed by the top talent at an agency.


You might not want to invest in AI consultancies if…

  • You’re worried about overspending in the long-term

AI consultancies are an undeniably cheaper option short-term, but costs will grow over time. If you plan to outsource for five years or more, you need to be sure that you can afford it before committing. Of course, this is also a downside of in-house operations, so seeking payment options that best suit your need, such as pay-as-you-go, could well be the only way around such concerns.

In truth, this is the only real downside of a consultancy. This is why consultancies that will also help you build in-house capabilities are increasingly popular. They allow businesses to get started today, but also build a sustainable solution for the future. Fundamentally, if you don’t have any understanding of AI, a consultant could build you a tool, but you will struggle to use it.


The good - 

  • Immediate results
  • Easily manageable payments
  • Scalability as you need it

The bad - 

  • Intricate product knowledge can take time
  • Costs can add up
  • Challenges using and adapting tool later that were built by an agency


Are all AI consultancies the same?

By seeking outside help, you can undoubtedly take your AI furthest right now. But, before you can enjoy those benefits, it’s fundamental to understand unique consultancy differences.

Like employees, no consultancy is the same, and selecting a company you work well with on every level is the only way to avoid the potential pitfalls. Some of the main differences to look out for include - 

  • Pricing - Is there a subscription or pay-per-service model? Are you contracted for a set period, or can you cancel each month? How does this fit within your AI budget?
  • Quality of talent - Quality also varies a great deal, so consider the talent pool on offer. Are there individuals who could meet with your expanding AI needs? Will you be able to get all the help you require from this single consultancy?
  • NDAs - Non-disclosure agreements should be a priority for any business dealing with sensitive client information. We would be very surprised if a consultancy didn’t offer this option — but make sure to investigate and get one signed. 
  • Operations vs theory - The big spit in the consulting world are between agencies who focus on planning vs those that actually get down and do some of the heavy lifting. If you want a full-consulting experience, you need to opt for the latter. Theory consultants can help you decide if your project is fit for purpose, or decide where your investment priorities should be. But if you want help executing, you need to make sure that the business you are partnering with can actually help you build the models you need — not just tell you which models you should use.  

Advisory consultants can be great if you take a hybrid approach. But even there, looking to bring in subject matter experts able to deliver operationally can still be a large added benefit to the system you are looking to build. These same consultants can form an excellent component of training and building your hybrid team.   

As with anything in business, no one can tell you how best to go about AI. Only you can know which option will prove the ideal fit for your focus moving forward. But, one thing’s sure; you’ll soon master AI in an easy-to-handle package by choosing a consultancy with these tips in mind.


Hopefully by now you have a better understanding of the differences between what AI in-house teams and consultancies can both bring. To get a better understanding of how an AI consultancy can help you implement AI in the context of your business, do not hesitate to get in touch. 

Get in touch

Victor Malachard
Victor Malachard
Executive Chairman

Related Posts

Google Privacy Sandbox: What it means for your programmatic ads

Google’s Privacy Sandbox looks like it might be the end of programmatic advertising as we know it, with third-party cookies largely set to become a thing of the past, and reliable automated data collation at risk along with them. The only way to prevent this from significantly unravelling online marketing efforts is to focus on shifting data landscapes, sources, and handling on a business-wide scale.

Is AI the right solution for your business: a 2020 assessment guide

AI adoption is on the rise at a rate of around 25% year-on-year. That’s an increase of approximately 270% in the last four years alone, and it’s a figure that set to continue rising as big data and tech potential continue to grow hand in hand. Still, despite this popularity, AI is far from a panacea for everything, as is evidenced by the fact that only 23% of businesses report using such solutions regularly. More disturbingly, a reported 85% if AI projects fail to deliver on their intended goals.  

How to train your own NLP model transformers

In recent years, search engines have led the way in natural language processing (NLP) and the benefits it stands to bring across business landscapes. Focused around machine learning capabilities, applications like Google’s BERT work to process natural language without human input. Used right, such systems can remove redundant work processes for faster and more efficient handling, analysis, and translation of written or spoken input from various sources.