From Implementers to Innovators: Shifting the Narrative Towards Women Entrepreneurship in AI

Abstract

The panel explored how women can move from being users and implementers of AI to becoming the architects, founders, and policy‑makers of AI solutions. Drawing on experiences from startups, regulatory bodies, finance, and academia, the discussion highlighted current participation rates, challenges in funding and data, the importance of inclusive regulation, and concrete initiatives (cross‑border collaborations, AI residency programs, and youth innovation contests) aimed at building a pipeline of women AI entrepreneurs. The session closed with actionable advice for aspiring women founders and a vote of thanks from the BRICS CCI leadership.

Detailed Summary

1.1 Welcome by the BRICS CCI Representative (Mr. Sameep Shastri)

• Contextualisation of the BRICS Chamber – emphasized its role in fostering trade, investment, innovation, and policy dialogue across BRICS + countries, with a particular focus on digital transformation and AI.
• Women‑Empowerment Vertical – highlighted the chamber’s commitment to turning women from participants into leaders of economic growth.
• Strategic Vision – under India’s 2026 BRICS presidency, the Chamber seeks “future‑focused partnership, responsible innovation and inclusive economic growth.”

1.2 Formal Welcome (Mr. Sameep Shastri, second address)

• Re‑affirmed AI’s transformative potential and the need for inclusive AI.
• Cited the summit’s theme “Sarvajan Hittaya, Sarvajan Sukhya” (welfare and happiness for all) and linked it to democratising AI with gender equity.
• Thanked Ms. Ruby Sinha (moderator) and the panelists, naming each speaker (note: transcription mis‑spelled some names; the list above reflects the official speaker roster).

2. Moderator Introduction

Ms. Ruby Sinha – President of the Women‑Empowerment Vertical, founder of SHE at Work, former journalist, and past jury member of the Enactus World Cup.

• Outlined the panel’s composition: a mix of founders, investors, regulators, and an international partner.
• Stressed the shift from “finding a seat at the table” to “designing the table” for women in AI.

3. Panelist Contributions

3.1 Amrita Chaudhary – Tech Entrepreneur (Gaia)

• Current statistics: Only ~20 % of startups/MSMEs have women founders/co‑founders; the figure is growing year‑on‑year.
• AI adoption across sectors:
  • FinTech – priority‑sector lending algorithms.
  • Retail & Marketing – AI‑driven personalization, supply‑chain optimisation.
  • Urban development & smart cities – surveillance, incident‑detection, smart‑mobility, and multi‑lane free‑flow tolling systems.
• Observations: Women‑led firms are still under‑represented, but the ecosystem is maturing and scaling with institutional support.

3.2 Elvira Chache – AI Regulation Expert (Cyberbank)

• Gender gap in AI research: In a recent international AI‑ethics project, 99 % of participants were men; only ≈8 % of Russian AI professionals are women.
• Data bias concerns: Current AI models are trained on historic data that under‑represents women, leading to potential bias in credit scoring and other automated decisions.
• Regulatory recommendation:
  • Collect gender‑balanced data continuously to avoid entrenched biases.
  • Integrate gender considerations into AI governance frameworks (especially for “safe and trusted AI”).
• Institutional role: As a financial regulator, she highlighted gender as a feature in credit‑scoring that must be re‑engineered to remove discrimination.

3.3 Male Panelist (Mr. Bibin Babu) – Investor & Ecosystem Builder

• Observation on female‑led startups: Tend to focus on durability and clear problem statements, avoiding hype‑driven pivots.
• Investment criteria (gender‑agnostic):
  1. Proof of concept / early traction (pilot data, first‑hundred users).
  2. Revenue focus over inflated valuations.
  3. Team fit and product‑market timing.
• Qualitative edge: Women founders often validate early users rigorously, delivering iterative improvements.
• Challenge: Despite the merits, funding gaps persist; systemic biases need addressing.

3.4 Najeela Popova – Global Partnerships Lead (Instituto+Mulheres, Brazil)

• Cross‑border collaboration:
  • Upcoming visit of Brazilian President Lula to Asia, bringing 200 + business leaders; an opportunity for India‑Brazil AI partnerships.
  • Launch of a permanent Brazil‑India trade office (Apex Brazil) to boost bilateral SME trade (current total ≈ $15 bn, with huge upside).
• Sectoral collaboration ideas: Female health, creative economy, agriculture, smart‑city tech.
• AI Residency in Rio: A new artistic residency for young female creators to develop AI‑driven content, inviting Indian participation.
• Strategic vision: Emphasised that joint initiatives can unlock a $1.6 bn market for women‑focused AI solutions.

3.5 Shivani Singh Kapoor – Youth‑Focused Entrepreneur (ThinkStartup)

• Youth Innovation Competition – Pan‑India Innovation Entrepreneurship Competition (schools & colleges).
  • 45 % female participation (record high).
  • Notable projects:
    • Wearable health device for the elderly (8th‑grader).
    • Bio‑decomposing drone‑sprayed solution for air‑pollution & crop‑burning (girls from Merut).
    • Cow‑shed cleaner prototype (girls from Tamil Nadu).
• Key insight: Young women are purpose‑driven, tackling local and global challenges with AI‑first solutions.
• Missing link (“the missing middle”): Need ecosystem support (incubation, financing, mentorship) to transition from idea to scalable startup.

3.6 Audience‑Driven Q&A

3.6.1 Investor Perspective (Mr. Bibin Babu) – Funding Women‑Led Startups

• Reiterated focus on durability, proof, and revenue over hype.
• Encouraged women founders to secure early users and avoid excessive pivots.

3.6.2 Regulatory & Financial Perspective (Elvira Chache) – Credit & Loan Access

• Discussed gender‑biased credit‑scoring and the need for more gender‑balanced historical data.
• Highlighted Sberbank’s Accelerator and Skolkovo Foundation programmes in Russia that do not discriminate by gender.
• Suggested government‑led policies to create fair loan criteria for women entrepreneurs.

3.6.3 Sustainability Angle (Amrita Chaudhary) – AI for Climate & Urban Safety

• Presented Smart‑City projects in Noida: digital twins, hotspot detection, improved lighting, and trip‑chaining analysis for women’s mobility patterns.
• Emphasised the need for policy‑driven procurement that mandates gender‑inclusive design in AI‑enabled urban infrastructure.

3.6.4 Skills & Soft‑Skill Development (Najeela Popova)

• Asserted that soft skills and mentorship networks are essential beyond capital.
• The AI residency aims to provide IP ownership, production pipelines, and AI literacy for women creators.

3.6.5 Policy Recommendation (Shivani Singh Kapoor)

• Called for school & college interventions, vertical‑focused innovation challenges, and market‑access pathways to accelerate women’s AI entrepreneurship.

4. Closing Remarks & Vote of Thanks

4.1 One‑Line Advice from Panelists

Speaker	Advice
Amrita Chaudhary	“Skilling and deep contextual understanding are the twin pillars of successful AI solutions.”
Elvira Chache	“Master large‑language models – they’re the core of today’s AI landscape.”
Bibin Babu	“Stop ‘supporting’ women; fix the systems so they can lead autonomously.”
Najeela Popova	“Ask what your career can contribute to AI, not just what AI can do for you.”
Shivani Singh Kapoor	“Discard limiting beliefs; build now, even if you don’t feel ‘ready.’”
Ankita Sajdev (Vote of Thanks)	“Be the change – be a thermostat, not just a thermometer.”

4.2 Vote of Thanks (Ms. Ankita Sajdev)

• Expressed gratitude to the Government of India, Mr. Sameep Shastri, Ms. Ruby Sinha, and all panelists.
• Highlighted the four‑day AI summit as a showcase of India’s commitment to a robust AI ecosystem.
• Concluded with a sign‑off from the BRICS CCI, thanking the audience.

Key Takeaways

• Women‑founder representation remains low (~20 % in startups) but is rising steadily; targeted mentorship and funding can accelerate growth.
• AI adoption is already widespread across sectors (FinTech, retail, smart cities); women‑led firms are beginning to leverage these technologies.
• Gender‑biased data in historical training sets perpetuates inequities in AI applications such as credit scoring; continuous, gender‑balanced data collection is essential.
• Regulatory frameworks must embed gender considerations to ensure “safe and trusted AI.”
• Cross‑border collaborations (India‑Brazil) and AI residencies can create new market opportunities for women creators and entrepreneurs.
• Youth innovation contests reveal a vibrant pipeline of female talent focused on purpose‑driven AI solutions; the “missing middle” (incubation, financing) needs to be filled.
• Investors prioritize proof of concept, early revenue, and problem‑focused durability over hype; women founders often excel in these areas.
• Policy recommendations include school/college outreach, vertical‑focused challenges, and gender‑inclusive procurement to foster AI entrepreneurship.
• Actionable advice for aspiring women entrepreneurs: build technical fluency (especially around large‑language models), develop soft‑skill networks, and adopt a mindset of shaping the AI landscape rather than merely using it.

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