Women in AI Leadership: 22% of Positions and 34% Salary Gap
Only 22% of leadership positions in artificial intelligence in Brazil are held by women. This data, gathered by FGV in 2026, exposes a structural problem that the economy's most promising sector has not been able to solve on its own.
The scenario becomes even more serious when looking at compensation. Women in the AI field earn, on average, 34% less than men in equivalent positions, according to Datafolha/IA 2026. This is a gap that cannot be explained by education or experience.
But there are signs of change. Programs like "Elas na IA" (Women in AI), from MCTI, increased female hiring by 40% in just 12 months. The movement is real, but still insufficient to reverse decades of exclusion.
The Portrait of Inequality in Leadership Positions
Female leadership in AI in Brazil is not just low—it is concentrated. The 22% of women in command positions are mostly in middle management or project coordination roles. Director and C-level positions remain almost exclusively male.
The FGV IA 2026 survey shows that in technology companies with over 500 employees, the proportion drops to 15% in director positions. In startups, the number rises slightly to 25%, but still far from parity.
The absence of women in leadership is not a pipeline problem—it is a filter problem. Professionals enter the field but do not advance. The 34% salary gap is proof that the market is not correcting the bias on its own.
The research also reveals that 68% of women in AI report having experienced some type of gender bias in promotion processes. This data is consistent with international studies but takes on specific contours in Brazil, where corporate culture is still marked by informal referral networks.
Salary Gap: 34% Difference That Cannot Be Justified
The most striking data from Datafolha/IA 2026 is the salary difference. In equivalent positions—same education, same experience, same role—women earn 34% less than men.
The disparity is greater in high leadership positions. In AI director roles, the difference reaches 42%. In senior technical positions, such as machine learning engineers, the gap is 28%.
The study controlled for variables such as years of experience, educational level, and company size. Even so, the difference persisted. This indicates that the problem is not one of qualification, but of salary negotiation, unconscious biases, and lack of transparency in salary ranges.
The table below summarizes the comparative data:
| Position | Average Male Salary (R$) | Average Female Salary (R$) | Gap (%) |
|---|---|---|---|
| AI Director | 85,000 | 49,300 | 42% |
| AI Manager | 52,000 | 37,440 | 28% |
| Senior ML Engineer | 38,000 | 27,360 | 28% |
| Mid-Level Data Scientist | 22,000 | 17,160 | 22% |
| Junior AI Analyst | 12,000 | 10,320 | 14% |
Source: Datafolha/IA 2026
Acceleration Programs That Are Changing the Game
Faced with this scenario, structured initiatives are beginning to show concrete results. The "Elas na IA" program, coordinated by MCTI, is the most cited example. In 12 months, participating companies increased female hiring for AI leadership positions by 40%.
The program operates on three pillars: mentorship with senior executives, specialization scholarships in machine learning, and a blind selection process for leadership positions. Adhering companies commit to reaching a target of 30% women in management positions by 2028.
Another relevant initiative is "IA para Todas" (AI for All), from FGV, which offers free AI training for women in socially vulnerable situations. Since 2025, it has trained 1,200 students, with an employability rate of 78% within six months of completion.
Companies like Nubank and iFood have also created internal career acceleration programs focused on Black and peripheral women in the AI field. Results are still preliminary, but the first cohorts show 50% higher retention than the company average.
The Path to Parity
The numbers show that there is no lack of female talent in the AI field. What is lacking is the structure for that talent to reach leadership. The 34% salary gap and the 22% representation in command positions are symptoms of a system that needs to be redesigned.
Programs like "Elas na IA" prove that direct interventions work. The 40% increase in female hiring in 12 months shows that when there is real commitment, results appear quickly.
But there is still a long way to go. To achieve gender parity in AI leadership in Brazil, it would be necessary to triple the current number of women in command positions. This requires not only acceleration programs but also structural changes in promotion policies, salary transparency, and combating harassment.
Artificial intelligence is shaping the future of work, the economy, and society. If women are not at the decision-making table, that future will be built from a one-sided perspective. The 2026 data shows that the market is beginning to understand this—but it is still far from acting on the necessary scale.