The women writing AI’s rulebook

As artificial intelligence becomes woven into complex business systems—from software development to healthcare and retail—the challenge is no longer just building smarter models, but embedding safeguards into how they operate. Bias, accountability and oversight must be designed into the technology from the start. Behind some of this critical work are women leaders across global technology firms, shaping the architectures, governance frameworks and engineering practices that ensure AI systems remain transparent, reliable and responsible as they scale.
Non-coders are creating AI solutions
"I am an engineer by education and have spent the last decade leading business and operations. A growing part of my role today involves shaping how AI is adopted, scaled, and governed across the business operations. Managing large, distributed operations means dealing with complex workflows, vast amounts of data, and high stakes decisions every day, and this is where AI has become a critical enabler. In the past, data and analytics felt intimidating to many business users. With the latest wave of AI tools, we can break down that complexity and offer simple, intuitive interfaces, while still delivering powerful insights. At Cognizant, embedding AI into everyday work is a leadership priority, guided by a clear AI charter that emphasises responsible adoption, strong data governance, ethical use, and risk management," saidVijayalakshmi Vikram, VP , chief operating officer , core technology & insights , Cognizant

"Practical applications include AI assisted resume screening, AI driven evaluation of skills and personalised learning paths. When deployed thoughtfully, these systems can improve speed, consistency, and transparency. Today, many of these AI solutions are created directly by business users with little or no programming background. This democratisation of AI is reshaping enterprise decisionmaking and reflects a broader trend across India’s technology ecosystem. And in many cases, women leaders are steering AI strategy striking a balance between innovation and responsibility," she added.
Rethinking the enterprise for AI
"The next era of enterprise advantage will be defined by how intelligently organisations design for AI, not how quickly they adopt it. As AI becomes embedded into the fabric of decision making, the real transformation lies in reimagining operating models that allow intelligence to scale responsibly, adapt continuously, and earn trust by design. Data integrity, governance, and architectural intent are no longer enablers, they are strategic imperatives that determine whether AI reshapes the enterprise or remains incremental. Much of my charter revolves around helping clients bridge this gap. We embed accountability, auditability, and drift detection directly into our AI pipelines so that trust is engineered into the system and not added later. Sustainability is also top of mind. Many business problems are solved more effectively through efficient, purpose-built models rather than large, compute-heavy systems. To make this real, we invest in GenAI upskilling and new ways of working so teams can shift from automation thinking to redesign thinking. When people understand how AI influences decisions, processes and risk, the organisation becomes far more agile. My approach is simple: create AI foundations that are resilient, responsible, and scalable so clients can unlock value across their end-to-end business with confidence," said Padmashree Shagrithaya, EVP and head of insights & data – India , Capgemini
Engineering AI for the real world
"I lead the Advanced AI Applied Research Centre, where I focus on translating cutting-edge AI research into resilient, enterprise-grade platforms and solutions. My work aligns closely with Infosys’ AI-first vision, helping global organisations move beyond pilots and experimentation to operationalising AI at enterprise scale. Working across our generative and agentic AI suite, I drive the development of composable AI architectures that integrate generative AI, agentic systems, and domain-specific copilots into enterprise platforms. My focus spans areas such as model governance, AI observability, secure data pipelines, and responsible AI frameworks ensuring that enterprises can deploy intelligent systems that are reliable, transparent, and aligned with regulatory and risk requirements. I also work closely with clients to architect AI-native platforms and intelligent automation solutions that enhance decision-making, strengthen operational resilience, and product innovation. By combining applied research with engineering rigour, my work helps accelerate the adoption of emerging AI capabilities while maintaining strong governance and trust. I also collaborate with universities and research ecosystems to explore emerging AI paradigms and co-create new approaches that advance the frontiers of enterprise AI. I am a strong advocate for inclusive innovation and actively support greater representation of women in advanced technology roles and research-driven leadership," said Chetana Amancharla, leader – emerging technologies, Infosys
The real test of enterprise AI is scale
"Enterprise AI has crossed a critical threshold. The question is no longer whether organisations will adopt AI, but whether they can scale it responsibly without compromising performance, security, or trust. The real challenge lies in moving AI out of pilots and into the fabric of core business and engineering operations. In my role at IBM, I work with teams to turn AI ambition into enterprise reality. That means applying AI where complexity is highest and impact is measurable across the product development lifecycle (PDLC). By addressing legacy modernisation, engineering bottlenecks, and late-stage quality and security issues, AI has delivered productivity improvements of 45% across critical stages of development. Our AIfirst developer productivity platform reflects this enterprise-first approach with security-first principles built-in to workflows, not added as a plug-in. Built for large, complex environments, it embeds AI directly into the development lifecycle automating repetitive work while freeing developers to focus on higher-value problem solving. Beyond engineering, we have tools that help enterprises integrate AI assistants and agents into everyday workflows, so insights translate into action and decision-making becomes more predictive and intelligent. Ultimately, while AI can amplify capability, it is human judgment, creativity, and leadership that determine how transformative that impact will be," said Madhuri Madhavan Pillai, program director , data and ai , IBM India
AI needs more women in leadership
"As organisations embed AI across products, operations, and decision‑making, representation in technology leadership directly influences how AI is shaped, governed, and scaled. While more women are entering STEM and digital careers, their presence in senior technology and AI leadership roles remains limited, even as the impact of these roles grows. Driving the AI charter at Wipro means ensuring that rapid adoption is matched with strong governance and ethical guardrails. Given how exponentially AI is transforming enterprises and society, avoiding gender bias requires deliberate action. This includes addressing historical bias in datasets, enforcing transparency across models, and embedding ethical guidelines into how AI systems are designed, deployed, and monitored. Leadership plays a critical role in setting these standards, which is why having women in decision‑making roles is essential to shaping how technology is responsibly used. Inclusion must be intentional and built into leadership pathways. Increasing the representation of women in senior technology roles is both a strategic priority and a responsibility at Wipro. Supporting transitions into leadership requires reimagining work and creating frameworks that balance advocacy, sponsorship, and mentorship. As AI continues to transform our workplace and client ecosystems, my focus is on enabling women leaders to take influential positions, drive innovation, and shape the future of responsible AI at scale," Sandhya Arun, chief technology officer , Wipro
Building AI healthcare can trust
"AI is quickly becoming the intelligence layer of modern healthcare, but its real value lies in how responsibly it is designed and deployed. At CitiusTech, our AI charter is focused on building systems that clinicians can trust, regulators can evaluate, and health systems can scale with confidence. We are applying generative and agentic AI to simplify clinical workflows, unlock insights from complex health data, and strengthen decision support across care journeys. At the same time, governance is central to everything we build, thus ensuring explainability, strong data stewardship and safeguards against bias as these technologies evolve. For me, leading this charter is about aligning innovation with accountability. In healthcare, algorithms influence decisions that affect real lives, so the intelligence we design must reflect that responsibility. What is encouraging is the growing number of women technologists shaping this space, architecting platforms, leading AI teams and setting the standards for how healthcare AI will evolve," said Vaishali Nambiar, EVP , Citiustech
AI is at the core of business reinvention
"I lead Accenture’s Advanced Technology Centres Global Network, helping clients reinvent their businesses for growth by embedding advanced AI into IT modernisation. The conversations I’m having with clients today are no longer about experimentation they’re about tangible outcomes: stronger technology architectures, faster speed-to-market, better customer experiences, and building a future-ready workforce. For example, we built a custom AI platform for a global pharma company that reduced a multi week software rollout to a single day — accelerating drug development and enhancing regulatory compliance. Similarly, an AI-native platform we deployed for a retailer empowers in-store employees with real-time product insights and personalised recommendations for customers. As part of my role, I also shape the next generation of AI engineering talent at scale. Together, we are building capabilities that make AI a repeatable enterprise-wide delivery muscle across client engagements and industries, and developing smarter, faster, and more human-centered business solutions. What excites me most is not just the technology itself, but how we apply AI to empower people—keeping humans firmly in the lead," said Aditi Kulkarni, lead – global technology delivery and advanced technology centers global network, Accenture.