Guardians of AI: Ashu Goel Of WinWire On How AI Leaders Are Keeping AI Safe, Ethical, Responsible, and True
Uphold ethical standards. Ethics are a must. Every organization needs to establish comprehensive ethical guidelines that address potential risks, promote fairness, and ensure AI technologies respect human values. These guidelines must be proactively developed and consistently applied across all AI initiatives. This will help you create a culture of responsible innovation that prioritizes the broader societal impact of AI.
As AI technology rapidly advances, ensuring its responsible development and deployment has become more critical than ever. How are today’s AI leaders addressing safety, fairness, and accountability in AI systems? What practices are they implementing to maintain transparency and align AI with human values? To address these questions, we had the pleasure of interviewing Ashu Goel.
Technology is a powerful driver of change, and Ashu is passionate about using it as a force for good.
As the CEO of WinWire, Ashu helps senior technology leaders representing purpose-driven organizations gain competitive advantage with innovative software solutions. He believes that using technology for positive change is most effective when we combine the “left-brain” thinking of engineers and programmers with the “right-brain” thinking of artists and dreamers. Ashu calls it the right-brain revolution in tech!
Ashu is convinced that promoting this type of diversity in the technology industry is the best way to develop products and services that have a positive impact on the human experience and serve the greater good while injecting some much-needed empathy into the world.
When he founded WinWire in 2007, his goal was to combine the power of technology with a laser focus on core values that reflect that philosophy: People First, Technology Leadership, and Execution Excellence.
Ashu’s team supports AI transformation by stitching the digital fabric — closing the gap between legacy applications and next-generation technology to prepare organizations for a digital future.
Thank you so much for your time! I know that you are a very busy person. Before we dive in, our readers would love to “get to know you” a bit better. Can you tell us a bit about your ‘backstory’ and how you got started?
I started WinWire 18 years ago with a clear vision: helping clients succeed through innovative software solutions. I saw that software was going to become a crucial driver of competitive advantage across industries. Coming from my management consulting background, I understood that companies had many options for gaining a competitive edge. They could hire McKinsey for strategy, Kearney for operations, and Goldman Sachs for financial engineering. However, I saw a growing opportunity in software-driven innovation.
I built WinWire on three core values that I believed were essential:
- People First: Fostering strong relationships and prioritizing clients and employees.
- Technology Leadership: Staying at the forefront of software innovation.
- Execution Excellence: Ensuring consistent, high-quality delivery.
As a leader, I’m a big believer in what I call “purpose-driven innovation,” or balancing purpose with profit. While I know commercial success is important (we’re not a non-profit, after all), I believe that pursuing a broader purpose leads to better outcomes. This philosophy shapes how we approach our client relationships. We don’t want to be just another service provider — we aim to be true partners.
At WinWire, we keep things simple. We focus on understanding what our clients are really trying to accomplish. We help them envision where their end goals can take them. We build warm, flexible and collaborative partnerships. And we maintain those relationships throughout the journey.
None of us can achieve success without some help along the way. Is there a particular person who you are grateful for, who helped get you to where you are? Can you share a story?
Yes, my manager at A.T. Kearney was such a person. Working with him in my early career in setting up the India office of Kearny really exposed me to a true leader and the lessons learned have been invaluable.
You are a successful business leader. Which three character traits do you think were most instrumental to your success? Can you please share a story or example for each?
1: I believe strongly in fostering open communication and trust through a “people-first” approach. Communication at WinWire goes both ways. I think a large part of my success and the company’s success is that we actively promote open dialogue through various forums where employees can share their views, offer suggestions, and seek help. An example of this is our “Coffee with the CEO” sessions, where every employee is given direct access to the leadership team.
2: I believe it’s essential to recognize excellence around you. At WinWire, we reward outstanding performance with a range of internal awards, fostering healthy competition and continuous improvement. I also send personal emails to award winners and letters to the families of promoted employees, expressing gratitude for their contributions.
3: Finally, I believe in being purpose-driven. Integral to my success and WinWire’s success is our commitment to social impact. As a purpose-driven organization, WinWire is committed to driving positive social change. We want to leverage the power of technology to address society’s biggest challenges and build a more sustainable world. That’s why we work closely with clients who themselves are driving positive social change. We also believe our communities are strongest when everyone is included and can reach their full potential. That’s why we work with organizations around the world, including The Milaan Foundation’s Girl Icon Program in India, which is empowering adolescent girls, as well as Narika in California, to confront domestic violence in South Asian American communities.
Thank you for all that. Let’s now turn to the main focus of our discussion about how AI leaders are keeping AI safe and responsible. To begin, can you list three things that most excite you about the current state of the AI industry?
1: The business world stands at a critical juncture in its collective journey with generative AI. I’m excited that we are now shifting from pure excitement and speculation around AI to practical implementations of the technology. Many enterprise users of AI are now progressing from mere experimentation to the actual execution of business solutions, leveraging generative AI and its associated technologies to improve their business fundamentally.
2: I’m also excited about Agentic AI because I believe it will transform the way we interact with AI. I believe AI will become increasingly invisible, operating autonomously behind the scenes and quickly adapting to user preferences while minimizing disruption. At work, Agentic AI will enable enterprises to create autonomous agents that can understand, build, and perform complex business processes. Looking ahead, we can expect both “invisible” and “visible” AI to become standard features in virtually all software products. This integration will go far beyond simple chatbots and fundamentally change how we interact with technology at work and in our daily lives.
3: Finally, I’m not overly worried about the jobs AI will take away. Rather, I’m excited about the new jobs that will be created by AI. The spread of generative AI is now creating a number of new, specialized roles across industries. Like AI strategy consultants, who help organizations develop comprehensive AI implementation plans. Like AI change-management consultants, who focus on managing workforce transitions and workplace disruptions caused by AI adoption. New leadership positions, like Chief AI Officer, will emerge to oversee AI initiatives, while AI ethicists will ensure responsible AI development and deployment. Also, the key will be AI concierges, who will drive adoption and help users effectively utilize AI technologies in their daily work, particularly in blue-collar settings.
Conversely, can you tell us three things that most concern you about the industry? What must be done to alleviate those concerns?
The biggest challenges center on security, accuracy, and reliability, which I believe are the main barriers to widespread adoption. We must also tackle ethical concerns, data bias, and other related issues. While generative AI is powerful, it’s not a universal solution. Effective implementation requires setting up solid guardrails to ensure responsible use.
The related challenges, which are equally daunting, are the aspects of accuracy and reliability. It’s not just about implementing the technology; it’s about trusting the output. In my opinion, achieving this level of trust will be an ongoing process. A human-AI loop is likely necessary, involving human validation of the information generated. Tools are emerging to support this as well, but it’s a challenge that organizations continue to face — how to trust the AI’s output and make informed decisions based on it.
As a CEO leading an AI-driven organization, how do you embed ethical principles into your company’s overall vision and long-term strategy? What specific executive-level decisions have you made to ensure your company stays ahead in developing safe, transparent, and responsible AI technologies?
At WinWire, we are acting now to establish robust controls and ethical frameworks. For instance, I believe that security around generative AI solutions will continue to be of paramount concern, particularly security around data and data sharing. This necessitates greater maturity in security tools built for generative AI. Numerous small companies have emerged in the space, offering solutions that range from bias mitigation to general guardrails. Platform owners like ChatGPT and Anthropic are also integrating these types of features into their platforms. However, when using their APIs to build custom solutions, it will be imperative for all companies to ensure that their own risk mitigation measures are effective.
Have you ever faced a challenging ethical dilemma related to AI development or deployment? How did you navigate the situation while balancing business goals and ethical responsibility?
Look, in the world of transformative technologies, ethical considerations are the foundational infrastructure of responsible innovation. Our approach has always been about maintaining a delicate balance between pushing technological boundaries and doing what is ethically correct.
Many people are worried about the potential for AI to harm humans. What must be done to ensure that AI stays safe?
The main goal is to ensure AI serves humanity’s interests without stifling innovation. We must fine-tune technology to respect human agency, but sometimes, humans will need to step aside. Of course, human oversight remains crucial as AI matures. Yet, in some cases, removing humans from the loop is necessary to unleash the full potential of automation. If AI systems must always wait for human approval, it can slow down the operational efficiency that AI aims to deliver.
Despite huge advances, AIs still confidently hallucinate, giving incorrect answers. In addition, AIs will produce incorrect results if they are trained on untrue or biased information. What can be done to ensure that AI produces accurate and transparent results?
Hallucinations often occur when the model lacks sufficient knowledge about a given topic. As its ability to connect the input to its existing knowledge diminishes, the likelihood of producing an accurate response significantly decreases. While current strategies for mitigating hallucinations show promise for many enterprise applications, they are still inadequate for high-stakes scenarios requiring absolute precision, such as medical diagnostics or autonomous driving. These applications demand genuine logical inference and reasoning — abilities that current large language models are not yet capable of. Achieving true logical reasoning may require a fundamental overhaul of AI model architectures.
Based on your experience and success, what are your “Five Things Needed to Keep AI Safe, Ethical, Responsible, and True”? Please share a story or an example for each.
1: Test continuously to prevent bias: A primary concern of any AI system is the potential for bias. It’s necessary to thoroughly test and evaluate AI models during development to identify and mitigate any potential biases against particular communities or customer groups. This process involves rigorous backend data-model testing to guarantee fair and equitable treatment in all interactions. However, this is not a one-and-done process. It requires continuous monitoring and testing of AI systems in real-world applications to detect any emerging biases or ethical issues.
2: Respect data privacy: Global data-protection laws, such as the EU’s General Data Protection Regulation (GDPR), mandate rigorous consumer data safeguards. So, a key principle in your AI development program should be to gain informed consent from consumers regarding your collection and usage of their data. Transparency is crucial: clearly communicating the scope of data collection during AI interactions and its intended purposes. By making data privacy a core principle, you protect consumer rights, ensure regulatory compliance, and build trust in your AI systems.
3: Keep humans in the loop: People must play a key role in overseeing AI interactions to maintain quality control and ensure the system stays accurate and appropriate. When you deploy AI, build in alerts and “backdoors” so human agents can intervene if things go off track. These measures allow for real-time action, including the option to quickly adjust AI parameters or shut the system down if needed.
4: Safeguard the integrity of your data. Data integrity is the cornerstone of AI system reliability and performance. Your AI’s output quality is directly proportional to the accuracy, comprehensiveness, and cleanliness of input data. Rigorous data validation through cleaning processes, as well as through continuous monitoring, are essential to eliminate inconsistencies and errors that could compromise decision-making.
5: Uphold ethical standards. Ethics are a must. Every organization needs to establish comprehensive ethical guidelines that address potential risks, promote fairness, and ensure AI technologies respect human values. These guidelines must be proactively developed and consistently applied across all AI initiatives. This will help you create a culture of responsible innovation that prioritizes the broader societal impact of AI.
Looking ahead, what changes do you hope to see in industry-wide AI governance over the next decade?
Over the next decade, I hope to see AI governance evolve quickly to keep pace with rapid technological advancements. Effective oversight should ensure that AI strengthens a brand rather than harms it. Achieving this requires businesses to stay deeply engaged with emerging AI developments and continuously refine their governance practices. As AI becomes integral across every industry, proper governance will be vital for organizations to harness AI’s potential and remain at the forefront of innovation and success.
What do you think will be the biggest challenge for AI over the next decade, and how should the industry prepare?
The journey from basic computing to artificial general intelligence (AGI) is one of the most transformative technological quests of our time. We have moved from the earliest mechanical calculations of the 1940s to the development of deep learning and generative AI models that can simulate human creativity and reasoning. However, the path to AGI — a type of artificial intelligence (AI) that surpasses human cognitive capabilities and does not hallucinate or make mistakes — remains unfinished, with significant challenges to overcome.
As we progress through the final stages — developing abstract reasoning, ethical judgment, self-awareness, and unified cognition — AI will increasingly resemble human intelligence in both its depth and flexibility. The road ahead will require not only technological breakthroughs but also a deeper understanding of the complexities of intelligence itself. Only then will we reach the ultimate goal of AGI, where machines possess true, general intelligence capable of transforming our world in unimaginable ways.
You are a person of great influence. If you could inspire a movement that would bring the most good to the most people, what would that be? You never know what your idea can trigger. 🙂
Purpose driven innovation meaning balancing purpose and profit in your pursuits.
Thank you so much for joining us. This was very inspirational.
Guardians of AI: Ashu Goel Of WinWire On How AI Leaders Are Keeping AI Safe, Ethical, Responsible… was originally published in Authority Magazine on Medium, where people are continuing the conversation by highlighting and responding to this story.