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The New Face of Leadership: Redefining Thinking in the Age of AI

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The New Face of Leadership: Redefining Thinking in the Age of AI

Open Innovator organized a groundbreaking knowledge session on “The New Face of Leadership: Redefining Thinking in the Age of AI” on December 11, 2025, bringing together three distinguished women leaders from across the globe to address a critical challenge facing organizations today.

As AI rapidly reshapes how teams think, how organizations move, and how leaders must lead, the session explored an uncomfortable truth: the leadership mindsets that drove success in the past decade cannot sustain us through the coming years.

Hosted in collaboration with Net4Tech-a global ecosystem advancing women’s careers in technology- the 60-minute panel discussion moved beyond tools and algorithms to examine the deeper evolution of leadership required when machines think alongside humans, touching on essential themes of empathy, ethics, psychological safety, and the critical thinking skills leaders need to stay trusted, relevant, and effective in 2026 and beyond.

Expert Panel

The session featured four distinguished women leaders in technology and innovation as part of the Open Innovator Knowledge Sessions:

  • Begonia Vazquez Merayo (Moderator) – Founder of Net4Tech, a global ecosystem advancing women’s careers in technology, and leadership coach advocating for equality in tech.
  • Adriana Carmona Beltran – CEO and Founder of Tedix, global entrepreneur with experience building innovative tech startups across continents.
  • Deborah Hüller – Partner at IBM Consulting, expert in analytics and AI since 2014, advising federal agencies on digital transformation and public sector modernization.
  • Dr. Kamila Klug – Director of Business Development, Altair , Advisory Board Member.

Key Insights: Leadership Capabilities for the AI Era

The Curiosity Imperative

Adriana Carmona opened the discussion by identifying curiosity as the most underestimated leadership skill. “We cannot lead people in a future that we are afraid of,” she emphasized, advocating for a discovery mindset over fear when approaching AI. She positioned AI not as a replacement but as a tool to augment human capabilities, stressing that leaders must inspire curiosity in their teams to explore new possibilities.

Critical Thinking as a Compass

Dr. Kamila Klug highlighted the shift from traditional leadership to navigating changing terrain with values as a compass. She emphasized that in the AI era, critical thinking is essential for challenging assumptions and choosing the right path from multiple AI-generated options. Leaders must question not just AI outputs but their own biases to avoid creating echo chambers.

Psychological Safety in Fast-Changing Times

Deborah Hüller introduced psychological safety as a crucial leadership focus, noting that “AI accelerates change and change only works when people feel safe to learn.” She stressed that as teams face constant unlearning and relearning, creating environments where people can fail forward becomes essential rather than optional.

Cultural Philosophy and Human-Centric Innovation

Adriana shared insights from building companies across continents, emphasizing that leadership and innovation are inherently cultural. Her leadership philosophy combines emotional intelligence, empathy, and curiosity to understand diverse cultures and build meaningful connections. “AI is not here to replace us. AI is here to augment us,” she stated, positioning human relationship-building as the key differentiator in an AI-enhanced world.

Public Sector Transformation Challenges

Deborah addressed the complex challenge of transforming government institutions, which operate under zero-error tolerance and strict public fund management. She identified a critical tension: public servants are desperate to experiment with AI and fail forward, but the system doesn’t permit it. “We need to change the culture AND the system,” she emphasized, calling for systemic reforms that allow responsible experimentation while maintaining public trust.

Leading Through Continuous Transformation

Dr. Kamila Klug drew from her experience across countries and industries to advocate for coherent adaptability—maintaining core values while navigating constant change. She emphasized asking the right questions rather than simply asking many questions, and using AI as a “thinking sparring partner” that challenges rather than simply provides solutions.

Critical Warnings: AI Bias and Inclusion

The panel raised crucial concerns about AI perpetuating biases. Adriana provided a compelling example: most AI systems trained predominantly on English-language, US-based data could recommend California for agricultural projects while overlooking opportunities in Tanzania or Mozambique due to data scarcity. “If we are not aware of that, we are actually leaving behind a big part of society,” she warned.

Dr. Kamila Klug added a linguistic dimension, explaining how language itself shapes thought—a bridge described as masculine in one language is viewed as “strong,” while in languages where it’s feminine, it’s seen as “beautiful.” These biases embed themselves in AI training data.

Deborah emphasized the importance of inclusive automation design, noting that much AI will operate in the background without human oversight. “If we are not having inclusion in mind when building these systems, it will end in a non-inclusive world,” she cautioned.

Balancing Agility and Structure

Responding to audience questions about maintaining agility without chaos, the panel offered practical guidance. Adriana advocated for defining clear “North Stars”—specific goals that guide decision-making amid constant change. Deborah added that even agile environments need agreed-upon structures, with transparent communication when those structures evolve.

The Path Forward

The session concluded with a call to action from Begonia: “We are democratizing technology. We are opening doors for everyone to become a leader in AI.” She urged participants to avoid creating a new “AI gap” that would disproportionately affect women, encouraging everyone to be conscious creators who challenge biases and shape the future deliberately.

The consensus: AI presents unprecedented opportunities, but leaders must approach it with curiosity, critical thinking, psychological safety, and unwavering commitment to inclusion. As Adriana summarized, AI should be treated as a “junior collaborator” that requires training, guardrails, and guidance—not as a perfect oracle.

This Open Innovator Knowledge Session was part of “The New Face of Leadership” movement in collaboration with Net4Tech. Open Innovator specializes in digital transformation and innovation strategies, co-creating solutions where bold ideas turn into action. Write to us at open-innovator@quotients.com

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Ethics by Design: Global Leaders Convene to Address AI’s Moral Imperative

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Ethics by Design: Global Leaders Convene to Address AI’s Moral Imperative

In a world where ChatGPT gained 100 million users in two months—a accomplishment that took the telephone 75 years—the importance of ethical technology has never been more pressing. Open Innovator on November 14th hosted a global panel on “Ethical AI: Ethics by Design,” bringing together experts from four continents for a 60-minute virtual conversation moderated by Naman Kothari of Nasscom. The panelists were Ahmed Al Tuqair from Riyadh, Mehdi Khammassi from Doha, Bilal Riyad from Qatar, Jakob Bares from WHO in Prague, and Apurv from the Bay Area. They discussed how ethics must grow with rapidly advancing AI systems and why shared accountability is now required for meaningful, safe technological advancement.

Ethics: Collective Responsibility in the AI Ecosystem

The discussion quickly established that ethics cannot be attributed to a single group; instead, founders, investors, designers, and policymakers build a collective accountability architecture. Ahmed stressed that ethics by design must start with ideation, not as a late-stage audit. Raya Innovations examines early enterprises based on both market fit and social effect, asking direct questions about bias, damage, and unintended consequences before any code is created. Mehdi developed this into three pillars: human-centricity, openness, and responsibility, stating that technology should remain a benefit for humans rather than a danger. Jakob added the algorithmic layer, which states that values must be testable requirements and architectural patterns. With the WHO implementing multiple AI technologies, identifying the human role in increasingly automated operations has become critical.

Structured Speed: Innovating Responsibly While Maintaining Momentum

Maintaining both speed and responsibility became a common topic. Ahmed proposed “structured speed,” in which quick, repeatable ethical assessments are integrated directly into agile development. These are not bureaucratic restrictions, but rather concise, practical prompts: what is the worst-case situation for misuse? Who might be excluded by the default options? Do partners adhere to key principles? The goal is to incorporate clear, non-negotiable principles into daily workflows rather than forming large committees. As a result, Ahmed claimed, ethics becomes a competitive advantage, allowing businesses to move rapidly and with purpose. Without such guidance, rapid innovation risks becoming disruptive noise. This narrative resonated with the panelists, emphasizing that prudent development can accelerate, rather than delay, long-term growth.

Cultural Contexts and Divergent Ethical Priorities

Mehdi demonstrated how ethics differs between cultural and economic environments. Individual privacy is a priority in Western Europe and North America, as evidenced by comprehensive consent procedures and rigorous regulatory frameworks. In contrast, many African and Asian regions prioritize collective stability and accessibility while functioning under less stringent regulatory control. Emerging markets frequently focus ethical discussions on inclusion and opportunity, whereas industrialized economies prioritize risk minimization. Despite these inequalities, Mehdi pushed for universal ethical principles, claiming that all people, regardless of place, need equal protection. He admitted, however, that inconsistent regulations result in dramatically different reality. This cultural lens highlighted that while ethics is internationally relevant, its local expression—and the issues connected with it—remain intensely context-dependent.

Enterprise Lessons: The High Costs of Ethical Oversights

Bilal highlighted stark lessons from enterprise organizations, where ethical failings have multimillion-dollar consequences. At Microsoft, retrofitting ethics into existing products resulted in enormous disruptions that could have been prevented with early design assessments. He outlined enterprise “tenant frameworks,” in which each feature is subject to sign-offs across privacy, security, accessibility, localization, and geopolitical domains—often with 12 or more reviews. When crises arise, these systems maintain customer trust while also providing legal defenses. Bilal used Google Glass as a cautionary tale: billions were lost because privacy and consent concerns were disregarded. He also mentioned Workday’s legal challenges over alleged employment bias. While established organizations can weather such storms, startups rarely can, making early ethical guardrails a requirement of survival rather than preference.

Public Health AI Designing for Integrity and Human Autonomy

Jakob provided a public-health viewpoint, highlighting how AI design decisions might harm millions. Following significant budget constraints, WHO’s most recent AI systems are aimed at enhancing internal procedures such as reporting and finance. In one donor-reporting tool, the team focused “epistemic integrity,” which ensures outputs are factual while protecting employee autonomy. Jakob warned against Goodhart’s Law, which involves overoptimizing a particular statistic at the detriment of overall value. They put in place protections to prevent surveillance overreach, automation bias, power inequalities, and data exploitation. Maintaining checks and balances across measures guarantees that efficiency gains do not compromise quality or hurt employees. His findings revealed that ethical deployment necessitates continual monitoring rather than one-time judgments, especially when AI replaces duties previously conducted by specialists.

Aurva’s Approach: Security and Observability in the Agentic AI Era

The panel then moved on to practical solutions, with Apurv introducing Aurva, an AI-powered data security copilot inspired by Meta’s post-Cambridge Analytica revisions. Aurva enables enterprises to identify where data is stored, who has access to it, and how it is used—which is crucial in contexts where information is scattered across multiple systems and providers. Its technologies detect misuse, restrict privilege creep, and give users visibility into AI agents, models, and permissions. Apurv contrasted between generative AI, which behaves like a maturing junior engineer, and agentic AI, which operates independently like a senior engineer making multi-step judgments. This autonomy necessitates supervision. Aurva serves 25 customers across different continents, with a strong focus on banking and healthcare, where AI-driven risks and regulatory needs are highest.

Actionable Next Steps and the Imperative for Ethical Mindsets

In conclusion, panelists provided concrete advice: begin with human-impact visibility, undertake early bias and harm evaluations, construct feedback loops, teach teams to acquire a shared ethical understanding, and implement observability tools for AI. Jakob underlined the importance of monitoring, while others stressed that ethics must be integrated into everyday decisions rather than marketing clichés. The virtual event ended with a unifying message: ethical AI is no longer optional. As agentic AI becomes more independent, early, preemptive frameworks protect both consumers and companies’ long-term viability.

Reach out to us at open-innovator@quotients.com or drop us a line to delve into the transformative potential of groundbreaking technologies and participate in our events. We’d love to explore the possibilities with you.

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Open Innovator Virtual Session: Responsible AI Integration in Healthcare

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Open Innovator Virtual Session: Responsible AI Integration in Healthcare

The recent Open Innovator Virtual Session brought together healthcare technology leaders to address a critical question: How can artificial intelligence enhance patient care without compromising the human elements essential to healthcare? Moderated by Suzette Ferreira, the panel featured Michael Dabis, Dr. Chandana Samaranayake, Dr. Ang Yee, and Charles Barton, who collectively emphasized that AI in healthcare is not a plug-and-play solution but a carefully orchestrated process requiring trust, transparency, and unwavering commitment to patient safety.

The Core Message: AI as Support, Not Replacement

The speakers unanimously agreed that AI’s greatest value lies in augmenting human expertise rather than replacing it. In healthcare, where every decision carries profound consequences for human lives, technology must earn trust from both clinicians and patients. Unlike consumer applications where failures cause inconvenience, clinical AI mistakes can result in misdiagnosis, inappropriate treatment, or preventable harm.

Current Reality Check:

  • 63% of healthcare professionals are optimistic about AI
  • 48% of patients do NOT share this optimism – revealing a significant trust gap
  • The fundamental challenge remains unchanged: clinicians are overwhelmed with data and need it transformed into meaningful, actionable intelligence

The TACK Framework: Building Trust in AI Systems

Dr. Chandana Samaranayake introduced the TACK framework as essential for gaining clinician trust:

  • Transparency: Clinicians must understand what data AI uses and how it reaches conclusions. Black-box algorithms are fundamentally incompatible with clinical practice where providers bear legal and ethical responsibility.
  • Accountability: Clear lines of responsibility must be established for AI-assisted decisions, with frameworks for evaluating outcomes and addressing errors.
  • Confidence: AI systems must demonstrate consistent reliability through rigorous validation across diverse patient populations and clinical scenarios.
  • Control: Healthcare professionals must retain ultimate authority over clinical decisions, with the ability to override AI recommendations at any time.

Why AI Systems Fail: Real-World Lessons

The Workflow Integration Problem

Michael Dabis highlighted that the biggest misconception is treating AI as a simple product rather than a complex integration process. Several real-world failures illustrate this:

  • Sepsis prediction systems: Technically brilliant systems that nurses loved during trials but deactivated on night shifts because they required manual data entry, creating more work than they eliminated
  • Alert fatigue: Systems generating too many notifications that overwhelm clinicians and obscure genuinely important insights
  • Radiology AI errors: Speech recognition confusing “ilium” (pelvis bone) with “ileum” (small intestine), leading AI to generate convincing but dangerously wrong reports about intestinal metastasis instead of pelvic metastasis

The Consulting Disaster

Dr. Chandana shared a cautionary tale: A major consulting firm had to refund the Australian government after their AI-generated healthcare report cited publications that didn’t exist. In healthcare, such mistakes don’t just waste money—they can cost lives.

Four Critical Implementation Requirements

1. Workflow Integration

AI must fit INTO clinical workflows, not on top of them. This requires:

  • Co-designing with clinicians from day one
  • Observing how healthcare professionals actually work
  • Ensuring systems add value without creating additional burdens

2. Data Governance

Clean, traceable, validated data is non-negotiable:

  • Source transparency so clinicians know data age and origin
  • Interoperability for holistic patient views
  • Adherence to the principle: garbage in, garbage out

3. Continuous Feedback Loops

  • AI must learn from clinical overrides and corrections
  • Ongoing validation required (supported by FDA’s PCCP guidance)
  • Mechanisms for users to report issues and suggest improvements

4. Cross-Functional Alignment

  • Team agreement on requirements, risk management, and validation criteria
  • Intensive training during deployment, not just online courses
  • Change management principles applied throughout

Patient Safety and Ethical Considerations

Dr. Gary Ang emphasized accountability as going beyond responsibility—it means owning both the solution and the problem. Key concerns include:

Skill Degradation Risk: Over-reliance on AI may erode clinical abilities. Doctors using AI for endoscopy might lose the capacity to detect issues independently when systems fail.

Avoiding Echo Chambers: AI systems must help patients make informed decisions without manipulating behavior or validating delusions, unlike social media algorithms.

Patient-Centered Approach: The patient must always remain at the center, with AI protecting safety rather than prioritizing operational efficiency.

Future Directions: Holistic and Preventive Care

Charles Barton outlined a vision for AI that extends beyond reactive treatment:

The Current Problem: Healthcare data is siloed—no single clinician has end-to-end patient health information spanning sleep, nutrition, physical activity, mental health, and diagnostics.

The Opportunity: 25% of health problems, particularly musculoskeletal and cardiovascular issues affecting 25% of the world’s population, can be prevented through healthy lifestyle interventions supported by AI.

Future Applications:

  • Patient education about procedures, medications, and screening decisions
  • Daily health monitoring instead of reactive treatment
  • Predictive and prescriptive recommendations validated through continuous monitoring
  • Early identification of disease risk years before symptoms appear

Scaling Challenges and Geographic Considerations

Unlike traditional medical devices with predictable inputs and outputs, AI systems are undeterministic and require different scaling approaches:

  • Start with limited, low-risk use cases
  • Expand gradually with continuous validation
  • Recognize that demographics and healthcare issues vary by region—global launches aren’t feasible
  • Prepare organizations for managing AI’s operational complexity

Key Takeaways

For Healthcare Organizations:

  • Treat AI as a process requiring ongoing commitment, not a one-time product purchase
  • Invest in hands-on training and workforce preparation
  • Build data foundations with interoperability in mind
  • Establish clear governance frameworks for accountability and patient safety

For Technology Developers:

  • Spend time in clinical environments understanding actual workflows
  • Design for transparency with explainable AI outputs
  • Enable easy override mechanisms for clinicians
  • Test across diverse populations to avoid amplifying health inequities

For Clinicians:

  • Engage actively in AI development and implementation
  • Maintain clinical reasoning skills alongside AI tools
  • Approach AI suggestions with appropriate professional skepticism
  • Advocate for patient interests above operational efficiency

Conclusion

The Open Innovator Virtual Session made clear that successfully integrating AI into healthcare requires more than technological sophistication. It demands deep respect for clinical workflows, unwavering commitment to patient safety, and genuine collaboration between technologists and healthcare professionals.

The consensus was unequivocal: Fix the foundation first, then build the intelligent layer. Organizations not ready to manage the operational discipline required for AI development and deployment are not ready to deploy AI. The technology is advancing rapidly, but the fundamental principles—earning trust, ensuring safety, and supporting rather than replacing human judgment—remain unchanged.

As healthcare continues its digital transformation, success will depend on preserving what makes healthcare fundamentally human: empathy, intuition, and the sacred responsibility clinicians bear for patient wellbeing. AI that serves these values deserves investment; AI that distracts from them, regardless of sophistication, must be reconsidered.

The future of healthcare will be shaped not by technology alone, but by how wisely we integrate that technology into the profoundly human work of healing and caring for one another.

Reach out to us at open-innovator@quotients.com or drop us a line to delve into the transformative potential of groundbreaking technologies and participate in our events. We’d love to explore the possibilities with you.

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OI Session- Climate Tech Experts Address Urgent Need for Resilient Innovation

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OI Session- Climate Tech Experts Address Urgent Need for Resilient Innovation

A distinguished international panel of climate technology experts recently convened at our recent Open Innovator Virtual Session to address the urgent challenges facing innovation in the climate crisis era. The discussion featured:

  • Doreen Rietentiet, Founder & CEO based in Berlin, a climate adaptation technology specialist focused on energy solutions
  • Rajarshi Ray, Co-Founder & CEO based in London, an expert in regional climate tech implementation and market analysis
  • Wendy Niu, Co-Founder & CMO based in Bangalore, a sustainability strategist emphasizing regulatory adaptation
  • Tassilo Weber, Co-Founder & CTO based in Berlin, a climate tech ecosystem development professional
  • Yacine Cherraoui, Founder & Independent Consultant based in Berlin, a specialist in sustainable business models and market viability
  • Mrudul Mudothoty, Head of Product based in Bangalore, founder of an AI-powered waste management solution.

The session was moderated by Naman K, Nasscom COE who opened with the sobering statistic that climate disasters have cost the world over the past two decades, setting the urgent context for discussing how technology must evolve to address not just climate mitigation but adaptation to irreversible environmental changes.

Key Discussion Points

The Critical Shift from Mitigation to Adaptation

Doreen emphasized the fundamental need to transition from purely mitigation-focused climate technologies toward adaptation solutions that help communities survive and thrive despite changing environmental conditions. This represents a significant mindset shift for the climate tech industry, which has traditionally focused on preventing climate change rather than preparing for its inevitable impacts.

The discussion highlighted innovative air conditioning and cooling technologies as critical adaptation needs, particularly as rising global temperatures make traditional cooling methods unsustainable and insufficient for maintaining human health and productivity in extreme heat conditions.

Regional Disparities and Market Challenges

Rajshri Ray brought crucial insights about the significant disparities in climate tech market conditions across different global regions. He stressed that solutions effective in developed markets often require substantial adaptation for implementation in developing economies, where resource constraints and infrastructure limitations create unique challenges.

The panel discussed how understanding these regional differences becomes essential for creating truly scalable climate tech solutions that can address global challenges while remaining economically viable across diverse market conditions.

Navigating Regulatory Uncertainty and Flexibility

Wendy emphasized the importance of building flexibility into climate tech solutions to adapt to rapidly evolving regulatory landscapes. As governments worldwide implement new climate policies and standards, technology companies must design products and services that can quickly adapt to changing compliance requirements without losing effectiveness or market viability.

This regulatory uncertainty creates both challenges and opportunities for climate tech innovators, requiring strategic approaches that balance compliance with innovation speed and market responsiveness.

Ecosystem Collaboration and Sustainable Business Models

Some panelists addressed critical barriers to launching climate-focused products, emphasizing that successful climate tech requires unprecedented collaboration across traditional industry boundaries. They argued that climate challenges are too complex for any single organization to address effectively, requiring coordinated efforts among innovators, investors, policymakers, and community organizations.

The discussion focused on developing sustainable business models that maintain economic viability while delivering genuine environmental benefits, challenging the traditional assumption that environmental responsibility necessarily conflicts with financial success.

Transparency and Ethical Responsibility

Rajshri Ray stressed the crucial importance of transparency and auditability in climate tech solutions, particularly for startups seeking investment in sustainability-focused ventures. Investors and customers increasingly demand verifiable evidence of environmental impact, requiring climate tech companies to build transparency into their core operations rather than treating it as a marketing afterthought.

This emphasis on ethical responsibility extends beyond environmental impact to include social equity and community benefit, ensuring that climate tech solutions don’t inadvertently exacerbate existing inequalities while addressing environmental challenges.

Innovative Solutions in Practice

Mrudul presented a practical example through an AI-powered home appliance that manages waste decomposition by converting organic waste into usable soil. This demonstration illustrated how climate tech innovations can address multiple sustainability challenges simultaneously while providing clear value propositions for consumers.

The example highlighted key principles for successful climate tech: addressing real user needs, providing measurable environmental benefits, and creating economically sustainable value chains that support widespread adoption.

Core Principles for Climate-Resilient Technology

The panel identified several fundamental principles for developing effective climate tech solutions:

  • Systems Thinking Approach: Climate challenges require holistic solutions that consider interconnected environmental, social, and economic systems rather than addressing isolated problems independently.
  • Long-term Sustainability Focus: Successful climate tech must prioritize long-term environmental and social benefits over short-term financial gains, though economic viability remains essential for scaling impact.
  • Adaptive Design Philosophy: Climate tech solutions must be designed for flexibility and adaptation as environmental conditions and regulatory requirements continue evolving rapidly.
  • Cross-Sector Collaboration: No single organization or industry can address climate challenges effectively, requiring unprecedented collaboration across traditional boundaries.

Practical Implementation Strategies

The experts provided concrete recommendations for developing climate-resilient technologies. Innovators should focus on user-centered design that addresses real community needs while delivering measurable environmental benefits. This approach ensures that climate tech solutions gain adoption and create genuine impact rather than remaining theoretical possibilities.

Startups and established companies should build transparency and auditability into their core operations from the beginning rather than adding these capabilities later. This proactive approach builds investor confidence and customer trust while ensuring that environmental claims can be verified and validated.

Business model development must balance environmental impact with economic sustainability, creating value propositions that support widespread adoption while generating sufficient revenue for continued innovation and scaling.

Future Outlook and Vision

The panelists shared their visions for climate tech development over the next five to ten years, emphasizing the need for sustained long-term thinking and unwavering commitment from stakeholders across industries. They envision a future where climate adaptation technologies become as common and essential as current digital technologies.

The discussion highlighted the importance of maintaining optimism and determination despite the scale of climate challenges, focusing on actionable solutions that can create measurable progress toward climate resilience.

Call for Collective Action

The session concluded with strong encouragement for continued collaboration and innovation in addressing climate challenges. Panelists emphasized that the climate crisis requires collective action across all sectors of society, with technology playing a crucial but not exclusive role in creating sustainable solutions.

The experts stressed that everyone involved in innovation and technology development has a responsibility to consider climate impacts and adaptation needs in their work, regardless of their specific industry or focus area.

The panel reinforced that building climate-resilient technology requires not just technical innovation but fundamental changes in how organizations approach business models, collaboration, and long-term planning, making climate adaptation a central consideration in all technology development decisions.

Reach out to us at open-innovator@quotients.com or drop us a line to delve into the transformative potential of groundbreaking technologies and participate in our OI sessions. We’d love to explore the possibilities with you.

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OI Session: Tech Leaders Address Gender Inclusion and Diversity Challenges

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OI Session: Tech Leaders Address Gender Inclusion and Diversity Challenges

Expert Panel Explores Strategies for Creating More Inclusive Technology Environments

A distinguished panel of technology leaders recently gathered at the Open Innovation Virtual session to address the critical issue of gender inclusion and diversity in the tech industry. The discussion featured Neo Chatyaka, a technology innovator focused on creating solutions for diverse communities; Ashley McBeath, a tech executive specializing in embedding diverse perspectives into technological development; Ella Türünima, Enterprise Architect at Siemens Mobility GmbH; Begonia Vazquez Meraya, Tech Founder of Net4Tec; and Mercedes Pantoja, Head of Global Data & AI at Siemens Healthineers. Together, these trailblazing women shared bold insights and actionable strategies to foster inclusive workplace cultures and redefine leadership in global tech.

The session was moderated by Naman K, Nasscom CoE, on the Open Innovator platform, a community dedicated to fostering innovation and collaboration among technocrats, industry leaders, and startups. The discussion opened with a thought-provoking scenario about gender stereotypes, highlighting how ingrained mental models continue to shape perceptions about professional roles, particularly in technology sectors.

Key Discussion Points

Confronting Unconscious Bias and Stereotypes

The panel began by addressing fundamental challenges around gender stereotypes in professional settings. Through an engaging scenario about assumptions regarding surgeons and other professional roles, the discussion highlighted how deeply embedded mental models influence perceptions about who belongs in technology positions. This opening set the stage for examining how these biases impact women’s representation and advancement in tech roles.

Defining Meaningful Innovation Through Inclusion

Neo emphasized that meaningful innovation must serve diverse communities rather than focusing solely on dominant market segments. She argued that technology solutions developed without diverse perspectives often fail to address real-world problems faced by underrepresented groups. This approach requires intentionally including varied viewpoints throughout the innovation process.

Ashley reinforced this perspective by discussing how embedding diverse perspectives directly into technological development processes leads to more comprehensive and effective solutions. She stressed that diversity extends beyond gender to include varied mindsets, experiences, and cultural backgrounds that enrich problem-solving approaches.

Transforming Leadership and Workplace Culture

The panel addressed the critical need for inclusive leadership that actively fosters environments where women can thrive. Panelists shared personal insights about their career paths and experiences navigating male-dominated technology environments, emphasizing that leadership must be intentional about creating inclusive cultures rather than assuming they will develop naturally.

The discussion highlighted the importance of encouraging women to apply for leadership roles even when they don’t meet every listed requirement, challenging the tendency for women to self-select out of opportunities due to perceived qualification gaps.

Redesigning Talent Pipelines in Technology

Ashley focused specifically on artificial intelligence and technology sectors, discussing the urgent need to redesign talent pipelines to include diverse candidates. She emphasized that organizations must implement systemic changes in recruitment, retention, and advancement strategies rather than relying on individual efforts to drive inclusion.

The conversation addressed barriers that prevent women from entering and remaining in technology careers, including cultural expectations, lack of mentorship, and organizational environments that don’t support diverse working styles and perspectives.

Personal Leadership Development and Resilience

Panelists shared personal moments that shaped their leadership approaches, emphasizing the importance of resilience, continuous learning, and personal experiences in developing effective leadership styles. These stories illustrated how diverse backgrounds and experiences contribute to stronger leadership capabilities.

The discussion highlighted how personal narratives can inspire others to recognize their own leadership potential and overcome barriers that might otherwise prevent career advancement in technology fields.

Core Principles for Inclusive Technology Environments

The experts identified several fundamental principles for creating more inclusive technology workplaces:

  • Proactive Cultural Change: Organizations must actively work to create environments where women and other underrepresented groups can succeed, rather than expecting individuals to adapt to existing cultures that may not serve them effectively.
  • Comprehensive Mentorship Systems: Effective mentorship programs that connect women with both technical and leadership development opportunities prove essential for retention and advancement in technology careers.
  • Systemic Recruitment Reform: Traditional recruitment and hiring practices often perpetuate existing biases, requiring deliberate redesign to attract and retain diverse talent pools.
  • Leadership Visibility: Women in leadership positions must be visible throughout organizations to provide role models and demonstrate career advancement possibilities for other women.

Call to Action for Technology Professionals

The session concluded with strong encouragement for attendees to actively participate in creating more inclusive technology environments. This includes networking with and supporting other women in technology, advocating for inclusive practices within their organizations, and continuously developing leadership capabilities.

The panel stressed that everyone, regardless of their current position or level of influence, can contribute to building more diverse and inclusive technology communities through their daily actions and choices.

The discussion reinforced that creating equitable technology environments benefits everyone by fostering innovation, improving problem-solving capabilities, and ensuring that technological advancement serves broader societal needs effectively.

Write us to at open-innovator@quotients.com to get more information and participate in our upcoming sessions.

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OI Session: Startup Experts Reveal Strategies for Acquiring First 10 Real Customers

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OI Session: Startup Experts Reveal Strategies for Acquiring First 10 Real Customers

Panel Discussion Addresses Critical Challenge of Moving from Product Creation to Customer Acquisition

An expert panel of startup specialists recently participated in virtual session convened by Open Innovator. The goal was to address one of entrepreneurship’s most critical challenges: acquiring the first 10 real customers.

The discussion featured Angelie Mullin, a branding expert specializing in storytelling and narrative development; Jack Winter, a strategic marketing professional with expertise in demand validation; Celen Ebru, a community building specialist focused on targeted audience engagement; and featured a live startup pitch from Punit Agrawal, founder of an AI-powered customer support platform. The session was moderated by Naman K, who brings years of startup experience and emphasized the harsh reality that while every founder believes their product will succeed, the true test lies in actual customer acquisition.

Key Discussion Points

The Customer Acquisition Reality

The panel opened with a sobering statistic that 42% of startups fail due to lack of customers, not product issues. Naman highlighted the common founder illusion that first customers will come easily, describing this as a dangerous trap that leads many promising startups to failure. The discussion emphasized the critical difference between building a product and building a sustainable customer base.

Essential Mindset Shifts for Founders

Angelie stressed the importance of transitioning from founder-led sales to scalable sales models. She explained that founders must resist the temptation to over-customize their products for individual customers and instead focus on developing core offerings that appeal to broader market segments. This shift requires founders to think beyond their personal attachment to specific features.

Input-Focused Decision Making

Jack introduced the concept of validating demand before building products, using Dropbox as a prime example. The founder tested market interest through a simple video demonstration before investing in full product development. This approach emphasizes gathering real market feedback rather than making assumptions about customer needs.

Strategic Focus Over Scatter Approach

Celen emphasized the critical importance of focusing marketing efforts on fewer, more impactful activities rather than adopting a scattered approach. She stressed understanding specific audience segments deeply, arguing that trying to appeal to everyone often results in appealing to no one effectively.

Building Relationships Beyond Transactions

The panel unanimously agreed that successful customer acquisition requires moving beyond transactional relationships toward building long-term value connections. Early customers should be viewed as partners in product development rather than simply revenue sources, creating opportunities for referrals and testimonials.

The Power of Authentic Storytelling

A significant portion of the discussion focused on storytelling as a customer acquisition tool. Angelie noted that “people don’t buy what you sell, people believe what you believe,” emphasizing how emotional connections drive purchasing decisions. The panel shared tactics for using personal narratives to create resonance with potential customers.

Core Customer Acquisition Principles

The experts identified several fundamental principles for effective customer acquisition:

Problem-Solution Fit: Successful customer acquisition begins with solving genuine problems rather than promoting product features. Founders must understand customer pain points deeply and position their solutions accordingly.

Network Leverage: Building and utilizing professional networks emerges as crucial during early stages for gaining visibility and generating qualified leads. Personal connections often provide the most effective path to first customers.

Authentic Communication: Customers respond to genuine communication about challenges and solutions rather than polished marketing messages. Authenticity in founder communication creates trust and credibility.

Focused Targeting: Rather than casting wide nets, successful founders identify specific customer profiles and concentrate efforts on reaching these ideal segments effectively.

Practical Implementation Strategies

The panel provided concrete recommendations for implementing these principles. Founders should start with their immediate networks to identify potential early adopters who genuinely need their solutions. This approach provides validation opportunities while building initial customer relationships.

Storytelling should be integrated into all customer communications, focusing on the founder’s journey and the problem they’re solving rather than technical product details. This narrative approach helps potential customers understand the motivation behind the solution.

Community engagement and relationship building should take priority over paid advertising in early stages. Organic growth through genuine connections often produces more loyal customers than paid acquisition channels.

Addressing Long-Term Sustainability

The discussion acknowledged that acquiring first customers represents only the beginning of startup challenges. Panelists emphasized that early success doesn’t guarantee long-term viability without understanding broader market dynamics and developing scalable acquisition systems.

Real-World Application

The session included a live pitch demonstration from Punit Agrawal, showcasing an AI platform for automating customer support voice interactions. This practical example illustrated how founders can present their solutions while incorporating the discussed principles of customer-focused positioning and clear value proposition communication.

Key Takeaways for Entrepreneurs

The expert panel concluded with several critical insights for startup founders. Success requires moving beyond product creation excitement toward systematic customer acquisition approaches. Founders must develop empathy for customer needs while building authentic relationships that extend beyond initial transactions.

The emphasis on storytelling and emotional connections provides a competitive advantage in crowded markets, while strategic focus prevents resource waste on ineffective broad-spectrum marketing approaches. Building strong networks and leveraging personal connections offers the most reliable path to first customer acquisition.

The session reinforced that customer acquisition represents a fundamental business skill that requires dedicated attention and systematic development, challenging the assumption that great products automatically attract customers without strategic effort.

Reach out to us at open-innovator@quotients.com or drop us a line to delve into the transformative potential of groundbreaking technologies and participate in our OI sessions. We’d love to explore the possibilities with you.

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Innovation Experts Champion ‘Fail Fast, Learn Faster’ Approach

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Innovation Experts Champion ‘Fail Fast, Learn Faster’ Approach

At our recent Open Innovator Session, we dove into topic ‘F𝗮𝗶𝗹 F𝗮𝘀𝘁 𝗮𝗻𝗱 L𝗲𝗮𝗿𝗻 F𝗮𝘀𝘁𝗲𝗿’. A distinguished panel of innovation experts gathered to explore the transformative power of failure in driving business success.

The discussion featured Mehdi Khammassi, an experienced entrepreneur specializing in rapid iteration strategies; Professor Dr Yang (Lucy) Lu, an academic leader in innovation education; Dr. Deena Elsori, a researcher focused on entrepreneurial psychology and confidence building; and Belal Riyad, a startup practitioner with extensive experience in customer-centric product development. The session was moderated by Naman K, who facilitated insights on building collaborative innovation communities.

Key Discussion Points

The Failure Reality Check

The panel opened with a striking statistic: 90% of startups fail not because they have bad ideas, but because they learn too slowly from their mistakes. This fundamental insight shaped the entire conversation, with participants arguing that traditional approaches to avoiding failure actually slow down the innovation process.

Redefining Success and Failure

The experts challenged conventional thinking by positioning failure as the actual process of success rather than its opposite. Khammassi emphasized that “it’s not us who fail; it’s our hypothesis,” helping entrepreneurs separate their personal identity from business outcomes. This psychological shift enables faster decision-making and reduces the emotional barriers to necessary pivots.

Building Confidence Through Action

Dr. Elsori provided a counterintuitive insight about confidence, stating that “confidence is a result of overcoming failure, not a prerequisite.” This perspective encourages entrepreneurs to take action despite uncertainty, building resilience through direct experience rather than waiting for complete confidence before moving forward.

Customer-Centric Learning

Belal Riyad stressed the importance of understanding customer pain points and using real feedback to guide product development. He advocated for focusing on small features and minimal viable products to learn faster, rather than building extensive solutions based on assumptions. This approach ensures that innovation efforts address actual market needs.

Academic Innovation

Professor Dr Lu discussed how educational institutions can foster fail-fast principles through structured experimentation. She emphasized creating learning environments where failure becomes a valuable educational tool rather than a source of discouragement.

Core Methodology Principles

The panel identified several key principles for implementing fail-fast approaches:

Speed of Learning: Organizations must prioritize how quickly they can extract lessons from failures rather than focusing solely on avoiding mistakes. Rapid iteration and hypothesis testing become more valuable than extensive planning.

Ego Management: Successful innovators learn to receive objective feedback without letting personal attachment to ideas prevent necessary changes. This emotional discipline enables more rational decision-making throughout the innovation process.

Customer Engagement: Direct interaction with target markets provides the most valuable insights for refining products and services. Customer feedback should drive iteration cycles rather than internal preferences or assumptions.

Risk Reframing: Rather than avoiding risks, successful innovators take calculated risks with rapid feedback mechanisms that minimize potential losses while maximizing learning opportunities.

Practical Applications

The experts provided concrete strategies for implementing these principles across different contexts. Startups can use minimal viable products to quickly test market assumptions before investing in full development. Academic institutions can create experimentation-friendly environments that encourage student innovation. Established companies can develop internal cultures that reward learning from failure rather than penalizing unsuccessful attempts.

Community and Collaboration

Host Naman K emphasized the collaborative nature of innovation, encouraging continued dialogue among innovators, entrepreneurs, and educators.

The session also had a presentation from Puneet Agarwal, Founder, AI LifeBOAT, who introduced his product to the panelists. The virtual event concluded with strong encouragement for community engagement and peer-to-peer learning as essential components of the fail-fast methodology.

Looking Forward

The panel’s insights suggest a fundamental shift in how organizations should approach innovation challenges. By embracing failure as a learning accelerator rather than an outcome to avoid, businesses can develop more effective products, build stronger teams, and create sustainable competitive advantages in rapidly changing markets. The unanimous agreement among these diverse experts indicates growing recognition that strategic failure management will become increasingly critical for innovation success.

Write us to at open-innovator@quotients.com to get more information on our upcoming sessions.

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A Powerful Open Innovator Session That Delivered Game-Changing Insights on AI Ethics

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A Powerful Open Innovator Session That Delivered Game-Changing Insights on AI Ethics

In a recent Open Innovator (OI) Session, ethical considerations in artificial intelligence (AI) development and deployment took center stage. The session convened a multidisciplinary panel to tackle the pressing issues of AI bias, accountability, and governance in today’s fast-paced technological environment.

Details of particpants are are follows:

Moderators:

  • Dr. Akvile Ignotaite- Harvard Univ
  • Naman Kothari– NASSCOM COE

Panelists:

  • Dr. Nikolina Ljepava- AUE
  • Dr. Hamza AGLI– AI Expert, KPMG
  • Betania Allo– Harvard Univ, Founder
  • Jakub Bares– Intelligence Startegist, WHO
  • Dr. Akvile Ignotaite– Harvard Univ, Founder

Featured Innovator:

  • Apurv Garg – Ethical AI Innovation Specialist

The discussion underscored the substantial ethical weight that AI decisions hold, especially in sectors such as recruitment and law enforcement, where AI systems are increasingly prevalent. The diverse panel highlighted the importance of fairness and empathy in system design to serve communities equitably.

AI in Healthcare: A Data Diversity Dilemma

Dr. Aquil Ignotate, a healthcare expert, raised concerns about the lack of diversity in AI datasets, particularly in skin health diagnostics. Studies have shown that these AI models are less effective for individuals with darker skin tones, potentially leading to health disparities. This issue exemplifies the broader challenge of ensuring AI systems are representative of the entire population.

Jacob, from the World Health Organization’s generative AI strategy team, contributed by discussing the data integrity challenge posed by many generative AI models. These models, often designed to predict the next word in a sequence, may inadvertently generate false information, emphasizing the need for careful consideration in their creation and deployment.

Ethical AI: A Strategic Advantage

The panelists argued that ethical AI is not merely a compliance concern but a strategic imperative offering competitive advantages. Trustworthy AI systems are crucial for companies and governments aiming to maintain public confidence in AI-integrated public services and smart cities. Ethical practices can lead to customer loyalty, investment attraction, and sustainable innovation.

They suggested that viewing ethical considerations as a framework for success, rather than constraints on innovation, could lead to more thoughtful and beneficial technological deployment.

Rethinking Accountability in AI

The session addressed the limitations of traditional accountability models in the face of complex AI systems. A shift towards distributed accountability, acknowledging the roles of various stakeholders in AI development and deployment, was proposed. This shift involves the establishment of responsible AI offices and cross-functional ethics councils to guide teams in ethical practices and distribute responsibility among data scientists, engineers, product owners, and legal experts.

AI in Education: Transformation over Restriction

The recent controversies surrounding AI tools like ChatGPT in educational settings were addressed. Instead of banning these technologies, the panelists advocated for educational transformation, using AI as a tool to develop critical thinking and lifelong learning skills. They suggested integrating AI into curricula while educating students on its ethical implications and limitations to prepare them for future leadership roles in a world influenced by AI.

From Guidelines to Governance

The speakers highlighted the gap between ethical principles and practical AI deployment. They called for a transition from voluntary guidelines to mandatory regulations, including ethical impact assessments and transparency measures. These regulations, they argued, would not only protect public interest but also foster innovation by establishing clear development frameworks and fostering public trust.

Importance of Localized Governance

The session stressed the need for tailored regulatory approaches that consider local cultural and legal contexts. This nuanced approach ensures that ethical frameworks are both sustainable and effective in specific implementation environments.

Human-AI Synergy

Looking ahead, the panel envisioned a collaborative future where humans focus on strategic decisions and narratives, while AI handles reporting and information dissemination. This relationship requires maintaining human oversight throughout the AI lifecycle to ensure AI systems are designed to defer to human judgment in complex situations that require moral or emotional understanding.

Practical Insights from the Field

A startup founder from Orava shared real-world challenges in AI governance, such as data leaks resulting from unmonitored machine learning libraries. This underscored the necessity for comprehensive data security and compliance frameworks in AI integration.

AI in Banking: A Governance Success Story

The session touched on AI governance in banking, where monitoring technologies are utilized to track data access patterns and ensure compliance with regulations. These systems detect anomalies, such as unusual data retrieval activities, bolstering security frameworks and protecting customers.

Collaborative Innovation: The Path Forward

The OI Session concluded with a call for government and technology leaders to integrate ethical considerations from the outset of AI development. The conversation highlighted that true ethical AI requires collaboration between diverse stakeholders, including technologists, ethicists, policymakers, and communities affected by the technology.

The session provided a roadmap for creating AI systems that perform effectively and promote societal benefit by emphasizing fairness, transparency, accountability, and human dignity. The future of AI, as outlined, is not about choosing between innovation and ethics but rather ensuring that innovation is ethically driven from its inception.

Write to us at Open-Innovator@Quotients.com/ Innovate@Quotients.com to participate and get exclusive insights.

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Industry Leaders Chart the Course for Responsible AI Implementation at OI Knowledge Session

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Industry Leaders Chart the Course for Responsible AI Implementation at OI Knowledge Session

In the “Responsible AI Knowledge Session,” experts from diverse fields emphasize data privacy, cultural context, and ethical practices as artificial intelligence increasingly shapes our daily decisions. The session reveals practical strategies for building trustworthy AI systems while navigating regulatory challenges and maintaining human oversight.

Executive Summary

The “Responsible AI Knowledge Session,” hosted by Open Innovator on April 17th, served as a platform for leading figures in the industry to address the vital necessity of ethically integrating artificial intelligence as it permeates various facets of our daily lives.

The session’s discourse revolved around the significance of linguistic diversity in AI models, establishing trust through ethical methodologies, the influence of regulations, and the imperatives of transparency, as well as the essence of cross-disciplinary collaboration for the effective adoption of AI.

Speakers underscored the importance of safeguarding data privacy, considering cultural contexts, and actively involving stakeholders throughout the AI development process, advocating for a methodical, iterative approach.

Key Speakers

The session featured insights from several AI industry experts:

  • Sarah Matthews, Addeco Group, discussing marketing applications
  • Rym Bachouche, CNTXT AI addressing implementation strategies
  • Alexandra Feeley, Oxford University Press, focusing on localization and cultural contexts
  • Michael Charles Borrelli, Director at AI and Partners
  • Abilash Soundararajan, Founder of PrivaSapient
  • Moderated by Naman Kothari, NASSCOM CoE

Insights

Alexandra Feeley from Oxford University Press’s informed about the initiatives by the organization to promote linguistic and cultural diversity in AI by leveraging their substantial language resources. This involved digitizing under-resourced languages and enhancing the reliability of generative AI through authoritative data sources like dictionaries, thereby enabling AI models to reflect contemporary language usage more precisely.

Sarah Matthews, specializing in AI’s role in marketing, stressed the importance of maintaining transparency and incorporating human elements in customer interactions, alongside ethical data stewardship. She highlighted the need for marketers to communicate openly about AI usage while ensuring that AI-generated content adheres to brand values.

Alexandra Feeley delved into cultural sensitivity in AI localization, emphasizing that a simple translation approach is insufficient without an understanding of cultural subtleties. She accentuated the importance of using native languages in AI systems for precision and high-quality experiences, especially in diverse linguistic landscapes such as Hindi.

Michael Charles Borrelli, from AI and Partners, introduced the concept of “Know Your AI” (KYI), drawing a parallel with the financial sector’s “Know Your Client” (KYC) practice. Borrelli posited that AI products require rigorous pre- and post-market scrutiny, akin to pharmaceutical oversight, to foster trust and ensure commercial viability.

Rym Bachouche underscored a common error where organizations hasten AI implementation without adequate data preparation and interdisciplinary alignment. The session’s panellists emphasized the foundational work of data cleansing and annotation, often neglected in favor of swift innovation.

Abilash Soundararajan, founder of PrivaSapien, presented a privacy-enhancing technology aimed at practical responsible AI implementation. His platform integrates privacy management, threat modeling, and AI inference technologies to assist organizations in quantifying and mitigating data risks while adhering to regulations like HIPAA and GDPR, thereby ensuring model safety and accountability.

Collaboration and Implementation

Collaboration was a recurring theme, with a call for transparency and cooperation among legal, cloud security, and data science teams to operationalize AI principles effectively. Responsible AI practices were identified as a means to bolster client trust, secure contracts, and allay AI adoption apprehensions. Successful collaboration hinges on valuing each team’s expertise, fostering open dialogue, and knowledge sharing.

Moving Forward

The event culminated with a strong assertion of the critical need to maintain control over our data to prevent over-reliance on algorithms that could jeopardize our civilization. The speakers advocated for preserving human critical thinking, educating future generations on technology risks, and committing to perpetual learning and curiosity. They suggested that a successful AI integration is an ongoing commitment that encompasses operational, ethical, regulatory, and societal dimensions rather than a checklist-based endeavor.

In summary, the session highlighted the profound implications AI has for humanity’s future and the imperative for responsible development and deployment practices. The experts called for an experimental and iterative approach to AI innovation, focusing on staff training and fostering data-driven cultures within organizations to ensure that AI initiatives remain both effective and ethically sound.

Reach out to us at open-innovator@quotients.com to join our upcoming sessions. We explore a wide range of technological advancements, the startups driving them, and their influence on the industry and related ecosystems.

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