How AI is Supporting the Circular Economy: Innovations from Saudi Startups

Sep 15, 2025

Kholoud Hussein 

 

As the world increasingly focuses on sustainability, the concept of a circular economy—a system where resources are reused, recycled, and repurposed to minimize waste—has gained prominence. Through its ambitious Vision 2030, Saudi Arabia is actively pursuing sustainable economic growth by integrating cutting-edge technologies into its business ecosystem. In this effort, artificial intelligence (AI) is emerging as a powerful tool in supporting circular economy models. Saudi startups are at the forefront of leveraging AI to drive innovations that support resource efficiency, waste reduction, and environmental sustainability.

 

The Importance of the Circular Economy in Saudi Arabia

 

The circular economy contrasts with the traditional linear economy, which follows a "take-make-dispose" model that leads to significant waste and environmental degradation. By contrast, the circular economy emphasizes keeping resources in use for as long as possible, extracting maximum value, and regenerating products at the end of their life cycle. This model is essential for Saudi Arabia as it seeks to reduce its reliance on oil and shift towards a more diversified and sustainable economy.

 

Saudi Arabia is undergoing an unprecedented transformation, with NEOM, The Red Sea Project, and other mega-projects setting ambitious sustainability goals. These initiatives are pushing the Kingdom to explore innovative solutions to achieve zero waste and carbon neutrality targets. According to the World Bank’s 2024 report on sustainability in the MENA region, Saudi Arabia's transition to a circular economy could save the country billions in resource extraction costs and significantly reduce its environmental footprint.

 

AI: A Key Enabler of the Circular Economy

 

Artificial intelligence is playing a critical role in advancing circular economy models in Saudi Arabia. By automating processes, improving resource efficiency, and enabling smarter decision-making, AI technologies are helping businesses optimize their use of materials, reduce waste, and minimize environmental impact. AI-driven systems can analyze data on a large scale, helping companies identify inefficiencies in their supply chains, predict future resource needs, and create innovative solutions for reusing materials.

 

Hala Al-Tuwaijri, the CEO of the Saudi Green Initiative, recently remarked in an interview with Saudi Gazette, "AI will be an indispensable tool in driving sustainability efforts across the Kingdom. Whether it's optimizing energy use, managing waste more effectively, or creating new recycling technologies, AI enables us to make smarter, greener decisions."

 

Saudi Startups Leading the Circular Economy Revolution with AI

 

Several Saudi startups are making significant strides in integrating AI into circular economy solutions, offering innovative technologies that support the sustainability goals of Vision 2030.

Sadeem, a Riyadh-based environmental tech startup, is using AI-powered sensors to optimize water and waste management systems. Founded in 2017, Sadeem developed a platform that monitors wastewater systems in real-time, helping cities and businesses reduce water wastage. The platform collects and analyzes data to predict potential failures in water systems, allowing for proactive maintenance and preventing leaks that lead to massive water loss.

 

By utilizing machine learning algorithms, Sadeem is also able to identify patterns in water usage and waste generation, enabling cities to optimize resource allocation. As Dr. Ahmed Al-Kahtani, CTO of Sadeem, noted in a recent interview, "Our AI solutions are not only making water management more efficient but are also contributing to broader sustainability goals by reducing waste and conserving precious natural resources."

 

Another innovative startup is the Plastic Bank Saudi Arabia that is driving circular economy solutions is Plastic Bank Saudi Arabia, which uses AI to track plastic waste across the Kingdom. Plastic Bank operates a blockchain-based marketplace where waste collectors can trade recyclable plastics for digital tokens. These tokens are then exchanged for essential goods, creating an incentive for waste collection and recycling.

 

Plastic Bank employs AI algorithms to track plastic waste collection data, identify recycling bottlenecks, and optimize waste management routes. This AI-driven approach has led to a 25% increase in plastic recycling rates in areas where the startup operates. According to 2024 statistics from the Saudi Ministry of Environment, Water, and Agriculture, the Kingdom produces over 3 million tons of plastic waste annually, much of which could be recycled if more efficient systems like Plastic Bank's were implemented.

 

David Katz, founder of Plastic Bank, stated during an interview at the World Economic Forum in 2024, "By combining AI with blockchain, we are creating a transparent, scalable model for managing plastic waste. Our goal is to turn plastic into a currency that benefits local communities and helps build a circular economy."

 

Naqaa Solutions, a Jeddah-based startup, focuses on sustainable waste management by leveraging AI-powered robotics for sorting waste materials more efficiently. The company has developed an automated system that uses computer vision and AI algorithms to sort recyclable materials from general waste, significantly reducing the amount of waste that ends up in landfills. This solution is particularly valuable for Saudi Arabia, where urbanization is leading to increasing waste production.

 

According to Naqaa's CEO, Fahad Al-Mutairi, "Our AI-driven sorting systems have increased recycling efficiency by 40%. We believe that smart waste management is essential for achieving the goals of Vision 2030, especially as the Kingdom moves towards building sustainable cities."

 

Naqaa has already partnered with local municipalities and large-scale industrial players to deploy its AI-driven sorting technology, contributing to the development of zero-waste cities in Saudi Arabia.

 

AI and Sustainable Supply Chains: A Perfect Match for the Circular Economy

 

One of the most significant ways AI is advancing the circular economy is through the optimization of supply chains. In traditional linear supply chains, materials are used once and then discarded. However, in a circular economy, materials must be continuously reused, recycled, or repurposed. AI can help by improving resource tracking, predicting demand more accurately, and identifying opportunities to reuse materials.

 

Predictive Maintenance and Resource Efficiency

 

AI's ability to monitor systems in real time and predict failures before they happen is transforming industries that rely heavily on machinery and equipment. For instance, AI-based predictive maintenance tools can analyze the performance of industrial equipment, allowing businesses to reduce downtime and extend the life of machinery. This reduces the need for new materials and resources, making the entire production process more sustainable.

 

Aramco, Saudi Arabia's oil giant, has already begun integrating AI for predictive maintenance in its supply chains, reducing resource consumption and minimizing waste. By applying similar technologies to the manufacturing sector, Saudi startups can extend the life of products and create more sustainable supply chains that align with circular economy principles.

 

Circular Economy Opportunities in Saudi Arabia’s Mega Projects

 

Mega projects such as NEOM, The Red Sea Project, and the Green Riyadh Initiative are setting high standards for sustainability. These projects are incorporating circular economy principles from the planning stages, and AI is playing a key role in ensuring these ambitions are met.

 

For example, NEOM has set a target of generating 100% renewable energy and zero-waste cities. AI systems are being deployed to manage energy consumption, optimize construction materials, and monitor environmental impact. The Red Sea Project is also integrating AI into its waste management systems to ensure all waste is recycled or repurposed, contributing to the project's carbon neutrality goals.

 

Mansour Al-Maimani, head of sustainability at the Red Sea Development Company, recently highlighted the importance of AI: "The circular economy cannot exist without innovation, and AI is the backbone of that innovation. In projects like The Red Sea, AI enables us to make real-time decisions that reduce waste, optimize energy, and create long-term sustainability."

 

Overcoming Challenges: The Role of AI in Regulatory and Market Integration

 

While AI holds great promise for supporting the circular economy, challenges remain. The integration of AI technologies requires significant data infrastructure, a highly skilled workforce, and clear regulatory frameworks. Many startups face challenges in accessing the data needed to develop effective AI models and in navigating the complexities of Saudi Arabia’s regulatory environment.

 

However, the Saudi government is taking steps to address these challenges. In 2024, the Saudi Data and AI Authority (SDAIA) launched new initiatives to support startups by providing access to government data and offering grants to develop AI solutions in the sustainability sector. Additionally, SDAIA is working on establishing ethical guidelines for the use of AI in industries like waste management and resource efficiency, ensuring that AI technologies are deployed responsibly.

 

AI as a Catalyst for the Circular Economy

 

As Saudi Arabia moves towards achieving its Vision 2030 sustainability goals, AI-powered startups are playing a crucial role in driving the transition to a circular economy. From waste management and recycling to resource efficiency and predictive maintenance, AI is enabling businesses to rethink how they use materials and optimize processes for a greener future.

 

With continued support from the government, investment in data infrastructure, and the innovation-driven efforts of Saudi startups, AI will be a key catalyst in building a sustainable, circular economy that not only benefits the Kingdom but serves as a model for the broader region.

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Why fringe benefits matter more than ever for employers and employees

Noha Gad

 

Offering a strong salary is no longer enough to attract and retain top talent in today’s competitive job market, as employees increasingly look beyond base pay to evaluate the full value of a job offer, and that is where fringe benefits come in.

Fringe benefits are forms of non-wage compensation provided to employees in addition to their regular salary, including cash equivalents, property, services, or other privileges, such as health insurance, retirement contributions, company cars, tuition assistance, or paid time off.

Although they are viewed as extras, fringe benefits play a pivotal role in modern compensation packages for both employers and employees. For employers, they serve as powerful tools to enhance employer branding, boost employee morale and productivity, and gain tax advantages when structured correctly. For employees, they can significantly increase the real value of their compensation while improving financial security, health, and work-life balance.

 

What are fringe benefits?

Fringe benefits are additional remuneration that employees receive from their employers. They are designed to enhance the overall employee experience and provide added value beyond monetary compensation, serving as incentives that attract top talent and boost employee morale and satisfaction. By offering these extras, companies aim to create a positive work environment where employees feel valued and motivated.

Fringe benefits encompass a wide range of non-wage compensation that add another layer of appeal to any employment package, while creating a supportive workplace culture where employees feel appreciated for their hard work and dedication without only relying on financial remuneration.

 

Examples of fringe benefits

There are various types of fringe benefits that companies can offer to their employees, including:

  • Health insurance: Many employers offer comprehensive health insurance plans, covering medical, dental, and vision expenses for employees and their dependents.
  • Retirement plans: Companies may contribute to retirement savings accounts or offer pension schemes to ensure financial security for employees after they retire.
  • Paid time off: In addition to statutory holidays, companies often provide vacation leave, sick leave, personal days off, or paid parental leave to support employee well-being and family needs.
  • Employee Assistance Programs (EAP): These programs offer confidential counseling services for employees dealing with personal issues such as stress management or substance abuse problems.
  • Education reimbursement: Some organizations support continuous learning through tuition reimbursement programs or scholarships for further education or professional development courses.
  • Wellness programs: These initiatives promote employee health through gym membership discounts, wellness challenges, on-site fitness classes, or access to mental health resources.

 

Why do companies offer fringe benefits?

Offering fringe benefits gives companies a competitive edge in the job market, helping them to attract and retain top talent. Some advantages of providing fringe benefits include:

  • Increasing employee satisfaction. These benefits make employees feel valued and appreciated, leading to higher job satisfaction and making them more likely to be loyal and committed to their work.
  • Improving morale and motivation. Through fringe benefits, employers show they prioritize employees’ well-being, thereby boosting their morale and motivation.
  • Attracting top talent: A comprehensive package that includes attractive fringe benefits can be a major draw for highly skilled professionals.
  • Enhancing productivity: Offering fringe benefits helps create a positive work environment where individuals are motivated to excel. 
  • Reducing turnover: Investing in fringe benefits can help reduce employee turnover rates as individuals are less likely to leave an organization that provides valuable perks beyond salary alone.
  • Saving costs for employees: Some fringe benefits, like health insurance or retirement plans, may come with cost savings for employees compared to purchasing these services individually.

To sum up, fringe benefits have evolved from optional extras into a core component of strategic compensation, enabling employers to differentiate their offers, strengthen retention, and build a culture where employees feel genuinely supported.

These non-wage benefits can materially raise the real value of employees’ compensation while improving health, financial security, and work-life balance. For employers, a well-designed mix, aligned to workforce needs and local tax rules, can drive morale, productivity, and long-term cost efficiency.

Fringe benefits become a genuine investment in employees and a real advantage when it comes to winning and keeping great talent. For employers, all what they need to do is to choose benefits that truly fit their team and their goals, understand the full cost and tax picture, explain them in plain language, and revisit them often to see how they stack up.

Same Data, Different Eyes: Why Insight Beats Information Every Time

Ghada Ismail

 

In this second part, Abu Zannad turns to the resource startups actually have plenty of: creativity. He explains why “out-noticing” the competition matters more than out-spending them, and why so many founders confuse visibility, reputation, and meaning when they talk about “building a brand.”

 

How can startups use creativity as a competitive advantage when they cannot compete with larger companies on advertising budgets, resources, or brand recognition?

I think we first need to stop treating creativity as incidental, as this magical thing that occasionally happens when a talented person walks into a room. Creativity is becoming a much more important competitive capability precisely because AI is making so many other capabilities abundant.

Today, almost everyone can produce more content, more variations, more designs, more headlines and more analysis, faster and cheaper than ever before. So producing more is becoming less interesting. The competitive advantage increasingly lies in seeing something other people did not see.

I often describe it as the difference between information and insight. Two companies can have access to exactly the same data and come to completely different conclusions. Same data. Different eyes. That difference is human judgement.

And I don’t think insight has to be left to luck. There are conditions that make it more likely. Experience gives you patterns. Curiosity makes you notice what does not fit. Scepticism stops you accepting the first explanation. Contradictions reveal where reality is behaving differently from the category’s assumptions. Connections allow two things that normally live separately to collide.

Sometimes even constraint helps. I call that creative desperation: when you genuinely cannot solve the problem in the conventional way, you are forced to find another path. That is why startups may actually have an advantage. A large incumbent can often buy another media plan. A startup cannot. It has to notice something the incumbent has stopped noticing.

Look at the extraordinary group of younger businesses emerging around us:

Dollar Shave Club did not beat the shaving establishment by producing a more expensive shaving commercial. It understood internet humour and attacked the seriousness of the category.

Liquid Death looked at bottled water and asked why water had to behave like bottled water at all. It borrowed from punk, heavy metal and entertainment culture.

PRIME understood that creator communities themselves could become an extraordinary distribution system.

Crumbl turned cookies into something closer to sneaker drops; weekly anticipation, scarcity, reviewing and participation.

Sleep or Die looked at the soft, calming visual language of the sleep category and contradicted it completely.

And Dubai Chocolate may be one of the most fascinating cases of all. Someone created an unusually sensory product: “the crack of the chocolate, the colour of the pistachio, the texture of knafeh and a platform discovered that people could not stop watching it”. The algorithm accelerated the phenomenon; it did not originate the human fascination.

I think we should stop treating cases like these as amusing stories about things that “went viral.” They are evidence. We are watching something close to a new applied science of cultural creativity develop in front of us.

Every platform is producing an enormous live laboratory of human behaviour. Every unexpected breakout gives us something to study. What was the human tension? What cultural code did the brand recognize? What category convention did it violate? What community carried the idea? What made somebody want to participate rather than merely watch? What behaviour did the platform reward? What made the idea travel from one subculture into another?

Those are not questions only for advertising people anymore. They are questions for founders, anthropologists, behavioural scientists, strategists and technologists. And over time, we can begin building frameworks around them; not formulas for producing virality, because culture will never be that obedient, but better places to look for the unexpected.

That distinction matters. Creativity is not a formula. But neither is it magic. We can study it. We can develop our intuition. We can accumulate cases. We can recognize patterns. We can learn the grammar of a platform, a category, a culture or a subculture; and then have the courage to break that grammar when the human insight tells us to.

This, to me, is where AI becomes enormously useful. Let the machine search wider. Let it retrieve more cases, make more connections, generate more possibilities and accelerate experimentation.

But the human still has to ask: Which one matters? Which contradiction is interesting? Which observation is merely strange… and which one reveals something genuinely human? Which idea deserves to exist?

Because AI can increasingly generate ten thousand possibilities. The scarce capability is knowing which possibility is worth pursuing.

So my advice to startups would be: don’t try to out-produce the large companies. You probably can’t. And increasingly, there is little advantage in doing so anyway. Out-notice them. Out-understand them. And then use creativity to turn what you noticed into something the culture cannot ignore.

 

What do you think startups misunderstand most about building a brand: is it about visibility, reputation, or creating an identity people want to associate with?

I think what startups misunderstand most is the word brand itself.

They often think the sequence is: Build the product. Acquire customers. Grow. And when we become big enough, we will “do the brand.” Usually that means a new logo, a brand book, perhaps a large campaign.

But the uncomfortable truth is that you are building the brand from the first day whether you intend to or not. The first product experience builds it. The first customer complaint builds it. The way your founder speaks builds it. The price builds it. The packaging builds it. The people who choose you build it. The things you repeatedly say, and the things you repeatedly do, build it. So visibility, reputation and identity are not really three competing answers. They are three different layers.

Visibility means: I know you exist.

You can buy visibility. You can hack it. You can go viral and acquire enormous visibility almost overnight. But visibility is not a brand. We are surrounded today by things that became very visible and disappeared six months later.

Reputation means: I have learned what to expect from you.

You deliver. The product works. You keep your promises. There is consistency between what you say and what actually happens. Reputation takes longer because it has to survive contact with reality. And then there is something more interesting.

Meaning.

At some point, the strongest brands begin to signify something beyond the immediate utility of the product. Choosing the brand says something. Sometimes it says something to other people. Sometimes, more importantly, it says something to ourselves.

That is very close to the argument I make in AdEntity. Modern advertising became powerful because it taught objects to carry meaning. A watch stopped being only an instrument for telling time. A car was not only transportation. A pair of shoes was not only protection for the feet. Commercial objects became signals through which ambition, taste, rebellion, belonging, care or achievement could become socially legible.

And AdEntity does not argue that brands invented those desires. It argues that the surrounding system; the brand, product, image, celebrity and media environment… helped teach people how those desires could be recognized.

That is why I would hesitate to tell a founder, “Create an identity people want to associate with.” It is almost right. But it can lead to another mistake: inventing a beautiful brand personality with no relationship to the actual business.

Meaning has to be earned through product truth.

If Liquid Death behaved like a rebellious entertainment brand but the product, packaging and every interaction reverted to conventional bottled-water behaviour, the mythology would eventually collapse.

If Apple talks about creativity but produces experiences that feel careless, the symbolism weakens.

A brand cannot indefinitely advertise a meaning that the business itself does not substantiate. And this is where I think startups face a particularly modern trap. Startups live inside dashboards: ‘CAC. ROAS. Conversion. Cost per click. Retention. Downloads. Funnels’.

These numbers matter enormously. I would never advise a founder to ignore them. But because they are visible every morning on a dashboard, they begin to acquire psychological authority. What we can measure immediately starts to look more important than what is accumulating slowly.

And brand accumulates slowly. Memory accumulates. Familiarity accumulates. Trust accumulates. Distinctive assets accumulate. Meaning accumulates. This is why performance marketing is so seductive. You spend today and something happens tomorrow.

Brand building is more like compound interest. For a while, it can look as though very little is happening. And then one day people search for your name instead of the category. They recommend you without being paid. They recognize you before they see the logo. They forgive you a small mistake because there is accumulated trust. They consider you before the performance ad arrives. They may even pay slightly more because the alternative does not feel equivalent.

That is an economic asset, not a communications indulgence.

Airbnb gave us a fascinating demonstration of this. When the company dramatically reduced marketing during the pandemic, traffic recovered to roughly 95% of its 2019 level before marketing expenditure fully resumed. By the fourth quarter of 2020, more than 90% of traffic was direct or unpaid. Brian Chesky’s conclusion was essentially that Airbnb had become culturally established enough that the brand itself was generating demand.

That is what founders should aspire to. Not necessarily becoming a verb. But getting to the point where every customer does not have to be rented again from an advertising platform. Because if every sale requires another paid impression, another promotion and another retargeting message, you may have built an efficient acquisition machine. You have not necessarily built a brand.

There is another problem that optimization culture creates for startups: they change too much. New headline. New proposition. New design. New tone. New campaign. New audience. New creative every week because something performed 4% better. Experimentation is essential for discovering what works. But once you discover something valuable, brand building requires the opposite capability: the discipline to repeat it.

Memory needs consistency. And let’s not confuse consistency with repetition.

The Ehrenberg-Bass work on distinctive assets is useful here. Colours, sounds, shapes, characters, packaging and other recognizable cues only become assets when people repeatedly learn to associate them with one brand. They are built and protected over time; they do not become distinctive because somebody declared them distinctive in a brand guideline.

So perhaps I would give founders a very simple architecture: Be visible enough to enter the mind. Be good enough to earn a reputation. Be consistent enough to become remembered. Be meaningful enough to stand for something.

And make sure the product continuously earns the story you are telling.

Because a brand, in the end, is not the campaign. It is not the logo. It is not the number of followers. It is not even what the founder says the company stands for. A brand is the memory and meaning that remain when the advertising disappears. That is what startups should start building from day one.

What makes a 'VC-backable' startup?

Ghada Ismail

 

Not every good startup is a venture capital startup.

That can be hard for founders to hear, especially when they have built a product people like, attracted their first customers, and started generating revenue. But venture capital is not simply looking for businesses that work. It is looking for businesses that could become much, much bigger.

That is what makes a startup “VC-backable.” It is less about having a well-prepared investor presentation and more about showing investors that there is a real opportunity to build something with significant scale.

 

Market Size and Growth Potential

One of the first questions investors will ask is how big the opportunity really is.

A startup can solve a genuine problem and still have limited room to grow if its potential customer base is too small. For a VC-backed company, the ambition usually needs to go beyond building a profitable small business.

This is particularly relevant for startups in Saudi Arabia and the wider GCC. A founder may begin with a solution designed for Saudi customers, but investors will want to understand whether that business can eventually expand across the region or into other markets.

The bigger question is not just, “Who will buy this?” It is, “How many people or businesses could eventually need it?”

 

Customer Demand and Market Traction

A great idea is still only an idea until someone is willing to use it or pay for it.

This is where traction matters. Revenue, customer numbers, repeat purchases, retention, and transaction volumes can all show whether a startup is gaining genuine momentum.

For an early-stage company, traction does not necessarily mean millions in revenue. A growing user base, successful pilots, strong engagement or commercial partnerships can also demonstrate demand.

But there is a difference between growth and meaningful growth. Adding customers through heavy discounts, for example, does not necessarily prove that they will stay.

 

The Problem and the Value Proposition

The strongest startups tend to begin with a problem rather than technology for technology’s sake.

If a company can help businesses reduce costs, make a complicated process faster, improve access to finance, or solve a problem customers face regularly, its value becomes easier to understand.

Saudi Arabia’s rapidly developing fintech, healthcare, logistics, and technology sectors offer plenty of opportunities. The challenge is proving that the solution is valuable enough for customers to change their existing habits.

 

Founder Experience and Execution

Investors are putting money into a company, but they are also betting on the people running it.

Founders do not necessarily need decades of experience or impressive corporate backgrounds. What matters is whether they understand the problem, know their customers, and can keep adapting when things do not go according to plan.

Startups rarely follow the original business plan perfectly. Markets change, products need to be rebuilt, and early assumptions can prove wrong. Being able to respond to those changes can be just as important as having the original idea.

 

Scalability and Business Economics

Rapid growth sounds impressive until you look at how much it costs.

Investors will want to understand how much it costs to acquire a customer, how long that customer stays, and how much value they generate. A startup does not need perfect economics from day one, but there should be a credible path toward becoming more efficient as it grows.

That is also where scalability comes in. A Saudi startup might expand from one city to the wider Kingdom, then into the GCC or other international markets. The opportunity does not have to be global from day one, but investors will want to see what the next stages could look like.

Ultimately, being VC-backable does not mean a startup has to be perfect. Very few early-stage companies are.

It means giving investors a reason to believe the business can become significantly larger than it is today, and that the founders have a realistic way of getting there.

Why companies freeze hiring and how it affects their people

Noha Gad

 

Companies increasingly turn to cost-control measures to safeguard their financial stability. Among the most common and visible of these measures is the hiring freeze. While often presented as a temporary, strategic pause, a hiring freeze carries significant implications for employees, job seekers, and the organization’s long-term growth trajectory.

A hiring freeze is a business decision that sounds simple on paper but ripples through every corner of an organization. At its core, it is a temporary pause on bringing new people on board, no new roles, no backfills for departing employees, and often a hard stop on most recruitment activity. Companies often take this decision when they need to tighten budgets, navigate economic uncertainty, or reevaluate their workforce strategy without resorting to layoffs.

For current employees, a hiring freeze can feel like a mixed signal: there is short-term reassurance that jobs are safe, but also the creeping reality of heavier workloads, stalled promotions, and growing anxiety about the company’s future. For job seekers, it can mean suddenly stalled offers or roles that vanish midway through the interview process. And for leadership, it’s a balancing act between preserving cash and protecting morale, productivity, and long-term talent pipelines.

 

Why do companies implement a hiring freeze? 

Leaders may implement a hiring freeze to protect company finances and keep the business operational. They may also freeze new hires if the organization is plateauing or declining. There are a few other reasons why a halt in hiring may be necessary:

  • Budget deficit: If the process of hiring and paying new employees has the potential to cause overspending, leaders may halt recruitment. They may decide to delay hiring candidates until they improve the business's financial situation. 
  • Emerging liquidity issues: Liquid assets are a type of capital businesses have, such as cash balances and bank deposits. If an employer is uncertain whether a company is maintaining enough liquid assets, it might stop hiring efforts.
  • Upcoming layoffs: Layoffs are the discharge of temporary or permanent employees due to a lack of work or money available. Company leaders may implement a hiring freeze to save funds, preserve the fiscal stability of the business, and avoid layoffs.
  • Changes in market conditions: The shifts in market conditions can have a notable impact on revenue generation and overall profitability. Thus, leaders may implement a hiring freeze to counter the impacts of these changing conditions.

A hiring freeze may have an impact on current employees, as they might be responsible for completing additional tasks and working longer hours to keep a business operational. Professionals can overcome the challenge of a hiring freeze by:

  • Strengthening professional relationships with peers to position themselves as a valuable team member.
  • Seeking leadership opportunities, as a hiring freeze may leave certain positions open, including leadership positions.
  • Maintaining a positive mindset and attitude to be able to develop a positive reputation among colleagues and supervisors.  

 

Pros and cons

Although the hiring freeze delivers immediate financial relief, it sets off a chain of operational and cultural side effects that can last well beyond the freeze itself. Potential benefits include:

  • Immediate cost control: Halting new hires quickly reduces cash outflow without the legal, financial, and reputational costs of layoffs.
  • Preserving institutional knowledge: Because existing employees keep their jobs, a freeze avoids severance costs and the loss of expertise that come with mass redundancies.
  • Signaling fiscal discipline to investors and lenders: A freeze can be read as a proactive, responsible move to protect the balance sheet and extend runway.
  • Flexibility and reversibility: Unlike layoffs, a hiring freeze can be lifted relatively quickly when conditions improve, allowing the company to resume growth without rebuilding from scratch.

 

Key risks and downside include:

  • Increased workload and burnout: Vacant roles and natural attrition mean remaining staff absorb extra responsibilities, which can reduce performance, quality, and customer service over time.
  • Retention risks: Employees may interpret a freeze as a warning sign of deeper trouble, leading to disengagement or voluntary turnover.
  • Talent pipeline damage: Prolonged freezes can harm the employer brand, making it harder to attract top candidates later and causing promising prospects to drop out of the funnel.
  • Management challenges: Leaders may avoid addressing poor performance because removing an underperformer would leave a gap that can’t be filled, quietly lowering team standards.

To sum up, a hiring freeze can be a necessary, short-term response to financial pressure, but it is not a cost-free solution. While it buys time and preserves jobs in the near term, the hidden costs accumulate in heavier workloads, strained morale, stalled growth, and a weakened talent pipeline.

The Algorithm Isn't the Strategist: Ahmad Abu Zannad on Culture, AI in Marketing

Ghada Ismail

 

Ahmad Abu Zannad is an advertising strategist and author of AdEntity, a new book arguing that advertising did more than sell products over the past century; it helped build modern identity itself, turning ancient human signals like status, belonging, and ambition into a shared language understood across cultures. The book’s central warning is that this role is now shifting to algorithms, which Abu Zannad argues are moving beyond shaping what we buy to shaping who we become.

In the first installment of Sharikat Mubasher’s interview with Abu Zannad, we explore the deeper forces shaping brand-building today: how culture actually works (and how startups misread it), what has really changed as advertising has moved from the TV era to the age of AI, and why an obsession with algorithms and data can quietly replace understanding people with merely measuring them.

 

Your book looks at how advertising became deeply connected to culture and technology. How can startups use culture to build brands that people genuinely connect with?

“I would start by changing one word in the question. I don’t think startups should use culture. I think they should understand it.

Culture is not putting a local celebrity in an advertisement, borrowing a dialect, or adding familiar symbols to a campaign. Those are expressions of culture. Culture itself is much deeper. It is the shared understanding of what success looks like, what generosity means, what makes somebody trustworthy, what feels prestigious, what feels embarrassing, what belongs and what does not.

And beneath culture sit very old human motivations.

People everywhere want belonging, recognition, security, status, love and hope. But cultures give those motivations different expressions. Ambition in Riyadh does not necessarily look exactly like ambition in London or Tokyo. The human motivation may travel; its cultural meaning changes.

And when I say culture, I don’t only mean national culture. Internet culture, youth culture, creator culture and subcultures are cultures too.

Look at Dollar Shave Club. They entered shaving against companies with enormous budgets and decades of category authority. They couldn’t outspend Gillette, so they understood something happening culturally: people were increasingly suspicious of over-engineered products, corporate language and inflated prices. Their famous low-budget 2012 launch film spoke in the irreverent language of internet culture and generated 12,000 new subscribers immediately after launch.

Or look at Liquid Death. They entered perhaps the ultimate commodity, water, and behaved nothing like a water brand. They borrowed the visual codes, humour and attitude of punk, heavy metal and energy-drink culture: tall cans, a skull, “Murder Your Thirst,” absurd entertainment. The founder has explicitly described the ambition as building an entertainment company that monetizes through beverages.

PRIME did something different again. Logan Paul and KSI entered one of the world’s most competitive beverage categories with something Coca-Cola and Pepsi could not simply manufacture overnight: an existing cultural relationship with millions of people. The product launched in 2022 out of creator culture, turning two former rivals into partners and their audiences into an extraordinary distribution network for attention.

None of these companies began with the advantages traditionally needed to enter such categories. What they possessed was cultural capital before they possessed category power.

That is where I think startups have an interesting advantage over very large companies. They may have less money, but they are often much closer to the tension they are trying to solve. The founder may have lived the frustration, spoken the language of the community and understood a behaviour long before somebody turned it into a market-research chart.

So I would tell a startup: don’t begin by asking, “How do we make our brand culturally relevant?”

Ask: What is already alive in culture that nobody in our category is seeing… and what legitimate role can our product play inside it?

Because if you cannot outspend the category, you may still be able to out-understand it culturally.

The best brands do not impose themselves on culture. They find something already alive within it… and become useful enough, meaningful enough and distinctive enough to belong there.”

 

From the traditional advertising era to today’s AI-driven landscape, what has changed most about how brands earn consumers’ attention, and what has remained the same?

“I think the biggest change is that we have moved from an age of persuasion to an age increasingly shaped by selection.

In the traditional advertising era, a brand would buy access to an audience through television, newspapers, magazines or outdoor, and then the creative idea had to do the difficult part: make people notice, remember, feel something and perhaps change their behaviour.

There was still a human author in the middle of that process. A strategist, a writer, a creative director, a filmmaker. Someone was making a judgement about people and culture and saying: I think this idea will matter.

Today, the system is very different.

The algorithm increasingly decides what reaches you, how often you see it, what disappears, what gets amplified and what comes next. And AI is accelerating this dramatically. We can now create hundreds or thousands of variations, personalize them, test them in real time and optimize continuously around whatever generates a measurable response.

So the machinery of attention has changed enormously.

But the strange thing is that the human being underneath it has changed very little.

We still want many of the things our grandparents wanted: belonging, recognition, status, love, security, hope, companionship, achievement. This is one of the central arguments in AdEntity. Advertising did not invent these desires. At its best, it understood them, translated them through culture and gave them contemporary symbols, products and stories.

A diamond could become a signal of commitment. A car could become a signal of achievement or freedom. A sports brand could turn effort into a story of personal transcendence.

The technology changed. The human motives did not.

And I think that distinction matters enormously now because AI creates a temptation to confuse response with meaning.

An algorithm can learn that outrage keeps me watching. It can learn which image makes me click, which headline makes me pause and which version converts 3% better. But a reaction is not necessarily a relationship. And attention is not necessarily admiration.

This is where I worry about the direction of advertising. We are becoming extraordinarily good at optimizing the signal while sometimes forgetting to ask whether the signal means anything.

The old advertising industry could certainly produce terrible work, but its greatest work tried to create something people would voluntarily carry into culture: a line, a story, an aspiration, a piece of music, an image, sometimes even a new way of seeing themselves.

The danger today is that we settle for something much smaller simply because we can measure it more precisely. So if I had to put the whole transition in one sentence:

The old challenge was, “How do I persuade you?” The new power is increasingly, “What will the system keep showing you?”

That is an extraordinary technological shift. But brands should remember that behind every data point is still a very old human animal trying to belong, aspire, love, achieve and make sense of the world. The screen keeps changing. The human being behind the screen changes far more slowly.”

 

Has advertising become too obsessed with algorithms and data at the expense of understanding people? What can startups learn from that?

“Yes, but I would be careful with the criticism because I am not against data, algorithms or AI. Quite the opposite. I think they are extraordinary tools.

The problem begins when we confuse efficiency with intelligence.

Years ago, in Adman vs. Chomsky, I challenged Noam Chomsky’s description of advertising as an industry whose prime task is to ensure that “uninformed consumers make irrational choices.” I still disagree with that as a definition of advertising. Human beings were irrational long before the first advertising agency existed. Behavioural economics has simply helped us understand some of the shortcuts through which people navigate a complicated world.

But there is a danger today that we take those cognitive biases; scarcity, social proof, loss aversion, immediacy, outrage, fear of missing out… and hand them to an algorithm whose only instruction is: find what produces a response and do more of it.

Then AI allows us to generate another hundred versions, test them faster, target them more precisely and optimize them continuously.

We should ask ourselves: is that progress?

Or have we simply become better at doing mediocre advertising faster, cheaper and more intrusively?

That, to me, is the misuse of the algorithm. Because there is another possibility.

Look at Sleep or Die, a young sleep brand that looked at an entire category filled with lavender colours, peaceful bedrooms and soft wellness language and basically said: this is not what insomnia feels like. The brand called exhausted customers “zombies,” used provocative cigarette-style packaging and built an entire irreverent world around the seriousness of sleep. One unconventional product post on LinkedIn reportedly reached more than 180,000 people, and around 4,000 people joined the waitlist before launch.

The algorithm did not come up with that idea. It discovered that people found the idea interesting.

And Dubai gave us an even more extraordinary example.

FIX Dessert Chocolatier did not begin with a dashboard saying, “Pistachio content has a high completion rate.” Sarah Hamouda began with a craving and created something genuinely different: chocolate, pistachio, tahini, and the crunch of knafeh. Then a creator filmed herself breaking the bar open. You could see the green filling, hear the crack and crunch, and almost experience the texture through the screen.

That video eventually exceeded 120 million views, and FIX reportedly received more than 30,000 orders after it took off. The phenomenon became so large that “Dubai chocolate” became a global food category, copied by some of the world’s biggest confectionery companies.

Again, the algorithm did not invent Dubai Chocolate. It recognized that human beings could not stop looking at it.

Crumbl is another useful example. Its weekly rotating cookie drops created anticipation and FOMO before TikTok amplified them; on the platform, its campaign reached 22 million people and grew followers by 1,500% in two months. The interesting part is that the platform was amplifying an existing behavioral idea, the weekly drop, not substituting for one.

And that is what I think startups should learn. Don’t ask AI to compensate for the absence of an idea. Don’t use behavioral science merely to locate the next vulnerability you can press.

Understand people first. Create something distinctive enough to deserve attention. Then let the algorithm do what it is exceptionally good at: find the people for whom that idea resonates and help it travel.

The algorithm should be an amplifier, not the strategist. And perhaps that is the simplest way I can put it: AI should help great ideas travel faster. It should not merely help mediocre ideas become cheaper.”