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Foreign consultancies in Saudi Arabia are reining in a years-long boom in hiring, recruiters and analysts say, as the kingdom reviews its priorities and slows parts of its economic transformation plan.

Consulting firms have piled into the Middle East’s largest economy since 2016 when it embarked on several transformational “gigaprojects”, including futuristic economic area Neom with its 170km linear city, The Line. 

But low oil prices that are cutting into government budgets and doubts about the feasibility of some projects have slowed activity this year, as Saudi officials weigh up where to direct spending.

“There’s a bit of a panic, at least within KPMG,” said one former partner at the Big Four firm. “Understandable, considering 60-70 per cent of [advisory] revenue was public sector.”

KPMG said businesses worldwide were “navigating an uncertain economic environment”, and that “many professional services organisations” had been affected. The firm said its Middle East business continued to “align its services to current client demand”.

Dane Albertelli, senior research analyst at consultancy-focused advisory firm Source Global Research, said “there’s definitely been a realignment in the year but it’s becoming even more acute I think in the last two or three months”. He expects “a marked decrease” in the Saudi consulting market’s growth from 25 per cent in 2024 to about 11 or 12 per cent this year.  

Consultants are at a “crossroads because the Saudis are realigning what projects are top of the agenda, and obviously contracts are going to be awarded in different ways because of that”, Albertelli added, saying there would be “losers” as well as winners. 

Jason Grundy, Middle East and Africa managing director at executive recruitment firm Robert Walters, said that with many of the kingdom’s gigaprojects having moved from planning to delivery phase, less consulting was required. “Strategy consultancy firms don’t mix cement,” he added.

Bashar Kilani, United Arab Emirates managing partner at recruitment firm Boyden and a former managing director at Accenture in Dubai, said that what was once rapid-fire hiring by the consulting firms “is slowing and in some cases there are cutbacks”.

“It’s driven by two forces,” he added. “One is the actual reduction in spend [by clients] but the other one is technology,” with artificial intelligence forcing firms to show greater efficiencies.  

An Accenture consultant working in the kingdom added some firms were getting “majorly hit” by staffing cuts as a result of the new environment, while “AI is actually doing many tasks better than humans at analyst level”.

Kilani estimated that in consulting teams focused on banking and finance there had been a “15-20 per cent reduction” in middle management jobs, while in teams focused on construction the decrease was “much higher”.

But curbs on employee numbers come after an “unprecedented” increase in staffing levels for consulting firms in Saudi Arabia since the pandemic, Kilani added. According to researcher Albertelli, “this is a pause rather than a decline”.

The workforce boom had been driven by government entities looking for help from consultancies in accelerating the ambitious projects in Crown Prince Mohammed bin Salman’s “Vision 2030” plan, with outsiders assisting in everything from drawing up strategies to attract tourists to setting up entirely new ministries.

Consulting in Saudi Arabia “is softening back to a real market”, said one retired PwC partner. “It’s been an extraordinary market for the last five years”.

The FT has previously reported downward pressure on fees for consulting services, which some in the sector say have fallen as much as 40 per cent this year. 

Industry insiders report increasing scepticism from government clients about the role of consultancies, as value for money becomes paramount. Officials are concerned about consultants “overpromising on mega-projects, over-optimism”, said the retired PwC partner, as well as “the talent churn inside firms, and . . . conflicts of interest”. 

Companies under the umbrella of Saudi Arabia’s sovereign Public Investment Fund, which is driving the kingdom’s economic diversification efforts, are also coming under increasing pressure to deliver results. Management teams are facing more scrutiny from their boards, many of them populated by government ministers, to meet targets and tighten their spending, including their outlay on consultants.

It was taking longer for government entities to approve consulting contracts because the agreements were being more closely scrutinised, said Omer Zakaria, Robert Walters’ Saudi Arabia country head. 

“If someone wants to use a Bain or a BCG or a Big Four, they have to go through a process of getting it approved by the main government . . . it’s taking a while to do that,” he added, estimating a four-to-six-month lag. “The Big Four can’t wait and they were already heavily staffed based on the old model.”

However, some consultants say approval processes were already lengthy.

A former local PwC consultant said some government agencies had also become more restrictive about hiring foreign consultants at sensitive ministries over security concerns, limiting work on certain projects to Saudi nationals.

Grundy and Zakaria said there had been a “significant” decline this year in the number of placements Robert Walters makes for senior roles in professional services firms in Saudi Arabia, even as demand has risen in sectors such as healthcare, tourism and law.

The former KPMG partner said he was receiving messages from recruiters “several times per day offering me very senior talent based in Saudi Arabia”. 

Others in the industry said consulting firms were still taking on new staff but that the pace had slowed. While hiring continues because of constant attrition, one strategy consultant said, overall headcount growth was lower than in the past as firms adjusted after a period in which they “overhired”.

While many say they expect the consulting market in Saudi Arabia to weather the slowdown, others are more pessimistic.

“The glory days are over,” said one executive. “Now it’s a hard slog with more people in the room.” 

MIT engineers have developed a printable aluminum alloy that can withstand high temperatures and is five times stronger than traditionally manufactured aluminum.

The new printable metal is made from a mix of aluminum and other elements that the team identified using a combination of simulations and machine learning, which significantly pruned the number of possible combinations of materials to search through. While traditional methods would require simulating over 1 million possible combinations of materials, the team’s new machine learning-based approach needed only to evaluate 40 possible compositions before identifying an ideal mix for a high-strength, printable aluminum alloy.

When they printed the alloy and tested the resulting material, the team confirmed that, as predicted, the aluminum alloy was as strong as the strongest aluminum alloys that are manufactured today using traditional casting methods.

The researchers envision that the new printable aluminum could be made into stronger, more lightweight and temperature-resistant products, such as fan blades in jet engines. Fan blades are traditionally cast from titanium — a material that is more than 50 percent heavier and up to 10 times costlier than aluminum — or made from advanced composites.

“If we can use lighter, high-strength material, this would save a considerable amount of energy for the transportation industry,” says Mohadeseh Taheri-Mousavi, who led the work as a postdoc at MIT and is now an assistant professor at Carnegie Mellon University.

“Because 3D printing can produce complex geometries, save material, and enable unique designs, we see this printable alloy as something that could also be used in advanced vacuum pumps, high-end automobiles, and cooling devices for data centers,” adds John Hart, the Class of 1922 Professor and head of the Department of Mechanical Engineering at MIT.

Hart and Taheri-Mousavi provide details on the new printable aluminum design in a paper published in the journal Advanced Materials. The paper’s MIT co-authors include Michael Xu, Clay Houser, Shaolou Wei, James LeBeau, and Greg Olson, along with Florian Hengsbach and Mirko Schaper of Paderborn University in Germany, and Zhaoxuan Ge and Benjamin Glaser of Carnegie Mellon University.

Micro-sizing

The new work grew out of an MIT class that Taheri-Mousavi took in 2020, which was taught by Greg Olson, professor of the practice in the Department of Materials Science and Engineering. As part of the class, students learned to use computational simulations to design high-performance alloys. Alloys are materials that are made from a mix of different elements, the combination of which imparts exceptional strength and other unique properties to the material as a whole.

Olson challenged the class to design an aluminum alloy that would be stronger than the strongest printable aluminum alloy designed to date. As with most materials, the strength of aluminum depends in large part on its microstructure: The smaller and more densely packed its microscopic constituents, or “precipitates,” the stronger the alloy would be.

With this in mind, the class used computer simulations to methodically combine aluminum with various types and concentrations of elements, to simulate and predict the resulting alloy’s strength. However, the exercise failed to produce a stronger result. At the end of the class, Taheri-Mousavi wondered: Could machine learning do better?

“At some point, there are a lot of things that contribute nonlinearly to a material’s properties, and you are lost,” Taheri-Mousavi says. “With machine-learning tools, they can point you to where you need to focus, and tell you for example, these two elements are controlling this feature. It lets you explore the design space more efficiently.”

Layer by layer

In the new study, Taheri-Mousavi continued where Olson’s class left off, this time looking to identify a stronger recipe for aluminum alloy. This time, she used machine-learning techniques designed to efficiently comb through data such as the properties of elements, to identify key connections and correlations that should lead to a more desirable outcome or product.

She found that, using just 40 compositions mixing aluminum with different elements, their machine-learning approach quickly homed in on a recipe for an aluminum alloy with higher volume fraction of small precipitates, and therefore higher strength, than what the previous studies identified. The alloy’s strength was even higher than what they could identify after simulating over 1 million possibilities without using machine learning.

To physically produce this new strong, small-precipitate alloy, the team realized 3D printing would be the way to go instead of traditional metal casting, in which molten liquid aluminum is poured into a mold and is left to cool and harden. The longer this cooling time is, the more likely the individual precipitate is to grow.

The researchers showed that 3D printing, broadly also known as additive manufacturing, can be a faster way to cool and solidify the aluminum alloy. Specifically, they considered laser bed powder fusion (LBPF) — a technique by which a powder is deposited, layer by layer, on a surface in a desired pattern and then quickly melted by a laser that traces over the pattern. The melted pattern is thin enough that it solidfies quickly before another layer is deposited and similarly “printed.” The team found that LBPF’s inherently rapid cooling and solidification enabled the small-precipitate, high-strength aluminum alloy that their machine learning method predicted.

“Sometimes we have to think about how to get a material to be compatible with 3D printing,” says study co-author John Hart. “Here, 3D printing opens a new door because of the unique characteristics of the process — particularly, the fast cooling rate. Very rapid freezing of the alloy after it’s melted by the laser creates this special set of properties.”

Putting their idea into practice, the researchers ordered a formulation of printable powder, based on their new aluminum alloy recipe. They sent the powder — a mix of aluminum and five other elements — to collaborators in Germany, who printed small samples of the alloy using their in-house LPBF system. The samples were then sent to MIT where the team ran multiple tests to measure the alloy’s strength and image the samples’ microstructure.

Their results confirmed the predictions made by their initial machine learning search: The printed alloy was five times stronger than a casted counterpart and 50 percent stronger than alloys designed using conventional simulations without machine learning. The new alloy’s microstructure also consisted of a higher volume fraction of small precipitates, and was stable at high temperatures of up to 400 degrees Celsius — a very high temperature for aluminum alloys.

The researchers are applying similar machine-learning techniques to further optimize other properties of the alloy.

“Our methodology opens new doors for anyone who wants to do 3D printing alloy design,” Taheri-Mousavi says. “My dream is that one day, passengers looking out their airplane window will see fan blades of engines made from our aluminum alloys.”