Maaly Bukhari, Founder and CEO of GigSA, discusses how artificial intelligence, flexible employment models and digital workforce platforms are transforming recruitment, workforce management and career opportunities across Saudi Arabia and the wider GCC.
As Saudi Arabia accelerates its economic diversification under Vision 2030, the country’s labour market is undergoing a significant transformation. The expansion of tourism, entertainment, sports and major international events is creating new employment opportunities while increasing demand for flexible, technology-driven workforce solutions.
Artificial intelligence is playing an increasingly important role in this shift, helping organisations forecast staffing requirements, improve recruitment efficiency and manage large workforces more effectively. At the same time, changing employee expectations are encouraging businesses to rethink traditional employment models and offer greater flexibility.
Maaly Bukhari, Founder and CEO of GigSA, believes the future of workforce management lies in combining intelligent technology with transparent employment practices and human-centred decision-making.
In this interview with Mid-East Information, Bukhari shares her perspectives on AI-powered recruitment, the rise of flexible work, workforce challenges and the trends shaping the GCC labour market through 2027 and beyond.
1. How is artificial intelligence transforming workforce management and employment practices across Saudi Arabia and the wider GCC region?
AI is moving workforce management from reaction to prediction. For years, managing large shift-based teams in the region meant calling people the night before, filling gaps on the day and reconciling hours afterwards. Now organizations can forecast how many people they need, with which skills and in which locations, weeks in advance.
The change is most visible in sectors that depend on large teams whose size changes with the season: events and sport, hospitality, retail, logistics, security, facilities, and Hajj and Umrah operations. Demand in these sectors follows calendars, seasons and one-off peaks, which is exactly the kind of pattern AI handles well.
Employment practices are changing too. Hiring is shifting from CVs and personal referrals to verified records of attendance and performance. Attendance is captured digitally and tied to location instead of written on paper sheets. And because Saudi Arabia has built strong digital labour infrastructure through Qiwa, Mudad and GOSI, workforce data is becoming more structured and easier to act on. The organizations that combine that data with AI will plan better, spend less and treat people more consistently.
2. What are the key factors driving the growing demand for flexible work arrangements and alternative employment models in the region?
Three forces are driving it. The first is demand. Vision 2030 has grown entire sectors, from entertainment and sport to tourism and major international events, whose staffing needs rise and fall sharply. Fixed headcount cannot follow that curve efficiently.
The second is the workforce itself. Younger Saudis increasingly want to choose when and where they work, build experience across several organizations and fit work around study or family. Women’s participation in the labour market has grown significantly, and flexible roles are often how many women enter it.
The third is regulation. The freelance work document and voluntary social insurance registration for freelancers have made flexible work formal and recognized, which gives employers and workers more confidence in it. Together, these forces make flexible models a structural part of the labour market, not a temporary fix.
3. How can AI-powered workforce solutions help businesses improve recruitment, talent matching, and workforce planning?
Each of these is a data problem that has traditionally been handled by hand.
In recruitment, the challenge at scale is not finding applicants but screening them quickly and fairly. AI can verify documents, check eligibility and shortlist people based on skills, languages and track record, so recruiters spend their time on judgment calls instead of admin.
In matching, the goal is the right person in the right role at the right location. Matching on skills, experience and distance improves performance on the day and reduces no-shows, because people placed close to home and in roles that suit them are more likely to turn up and stay.
In planning, AI forecasts demand from past operations, schedules and the scale of each project, so organizations know how many people they need and when. This is where the largest savings are. Overstaffing wastes budget, understaffing hurts delivery, and both can be avoided with better forecasts. At GigSA, this is the role of our intelligence layer: predicting staffing needs and workforce performance before the first shift is confirmed.
4. What are the biggest challenges companies face when managing flexible or gig-based workforces, and how can technology help address them?
The biggest challenge is fragmentation. A single large operation can involve thousands of workers across several suppliers, each with its own lists, schedules and attendance records. No one has a complete picture of who is working, where, and whether they turned up.
The second is reliability. No-shows and late cancellations are costly when an operation cannot start without a full team. The third is compliance and payment. Verifying eligibility, tracking hours accurately and paying people correctly and on time is difficult when the data is scattered.
Technology addresses all three by bringing the whole workforce into one system. Suppliers and internal teams work from the same schedule. Attendance is captured digitally and verified by location, so hours are not disputed. Reliability and performance are recorded over time, so organizations can rebook the people who deliver and spot problems early. Payment can then be calculated from verified records instead of manual reconciliation. The result is fewer surprises on the day and clear visibility for the people accountable for delivery.
5. How are changing employee expectations influencing the way organizations approach flexibility, career development, and work-life balance?
Expectations have shifted from stability alone to control, growth and fairness. People still want security, but they also want a say in when they work, how work fits around the rest of their lives and what they will learn from it.
For organizations, this means flexibility is no longer a benefit reserved for a few senior staff. It has to be designed into how work is scheduled, especially for frontline and shift-based roles, where it has traditionally been absent. It also means taking development seriously for flexible workers through short training, recognized certifications and a visible record of experience that helps them progress. We are in discussions with universities and training academies so gig workers can earn professional certifications through their work.
Work-life balance is now in the worker’s hands. Freelancers can choose when and where they work, and build a schedule that fits around study, family and the rest of their lives. Technology makes that practical at scale: people see available shifts in advance, pick the ones that suit them and know exactly what each one involves. Organizations that offer that choice will find it easier to attract and keep good people.
6. What role can digital workforce platforms play in creating employment opportunities for young professionals, women, and individuals seeking more flexible careers?
Digital platforms lower the barrier to entry. A young person with no professional network can create a profile, get verified and start building a work history within days. Every completed shift adds to a record that employers can trust, so opportunity depends less on who you know.
Women are already a strong part of this workforce, across events, hospitality, retail, tech and professional services. What helps them is what helps everyone: clear information about each role, the freedom to choose work that fits their lives, and selection based on skills and track record.
7. How can businesses ensure that AI-driven hiring and workforce management tools remain fair, transparent, and supportive of employee well-being?
Fairness starts with what the system is built on. If the data reflects past bias, AI will repeat it at scale, so the inputs must be relevant to the job: skills, availability, location, attendance and performance, and nothing that has no bearing on the work.
Transparency means people understand how decisions are made. Workers should know why they were or were not selected and what they can do to improve their chances. Employers should be able to see why the system recommended someone, not just accept a ranking.
Human oversight comes next. AI should recommend and people should decide, especially on anything that affects someone’s income or reputation. Data protection is equally important. Saudi Arabia’s Personal Data Protection Law sets clear rules on how personal data is collected and used, and workforce platforms handle a great deal of it.
Finally, wellbeing can be built into the rules themselves, through limits on consecutive shifts, minimum rest between them and a fair spread of work across the team.
8. What inspired you to establish GigSA Technologies, and what workforce challenges are you aiming to solve through the platform?
GigSA comes from my own experience. I started freelancing in the events industry in 2017, and in 2023 I managed staff at Formula 1 in Jeddah, so I saw the same problems from both sides. As a freelancer, I waited to be paid and never knew where the next opportunity would come from. As a manager, I saw how much time went into last-minute calls, filling gaps on the day and resolving disputes about hours worked.
None of these problems were caused by people. They were caused by the lack of a proper system. In December 2024, I founded GigSA to build one: a workforce management platform that helps organizations forecast how many people they need, source and match the right people, verify attendance by location and track performance, all in one place.
We started in events and sport because that is where the pressure is highest and where I knew the problem best. But the same challenges exist in any organization that runs on shift-based teams, and that is the problem we are solving.
9. Looking ahead to 2027 and beyond, what trends do you believe will have the greatest impact on the future of work and workforce management in the GCC?
Three trends stand out. The first is scale. The AFC Asian Cup in 2027, Expo 2030 in Riyadh and the FIFA World Cup in 2034, alongside continued growth in tourism, will require larger and more complex workforces than the region has managed before. Planning them by hand will not be possible.
The second is AI moving from tools to agents. Today AI mostly supports individual decisions. Over the next few years, it will increasingly run whole workflows, forecasting demand, sourcing and confirming staff, flagging gaps and reporting on performance, with people supervising the outcome.
The third is the verified, portable work record. Workers will carry a trusted history of their experience, certifications and performance across employers and sectors. That will make hiring faster and fairer, and it will give flexible workers something they have rarely had: a career record that builds over time.
Underneath all three is formalization. Regulation, data protection and social insurance for flexible workers will keep maturing, and organizations that build on that foundation early will have a clear advantage.
10. What advice would you offer to businesses looking to adopt AI-powered workforce solutions while maintaining a human-centered approach to employment?
Start with the problem, not the technology. Identify where you lose the most time or money today, whether that is no-shows, overstaffing, disputed hours or slow onboarding, and apply AI there first. Measure the result before expanding.
Keep people in charge of decisions that affect people. Let the system forecast, recommend and flag issues, and let managers make the final call. Be open with your workforce about what the technology does and how it uses their data.
Invest in data quality early. AI is only as good as the records behind it, so make sure attendance, performance and feedback are captured accurately from day one.
Finally, define success broadly. The strongest results come when better delivery and a better experience for the workforce grow together: fair schedules, on-time pay and good people choosing to come back. That is when the technology is doing its job.
Bukhari’s insights underscore the need for organisations to look beyond automation and focus on building employment systems that combine operational efficiency with transparency, fairness and career development. As flexible employment models continue to evolve, businesses that successfully balance technological innovation with the needs of their workforce will be better positioned to navigate the region’s changing labour market.
