Ruchika Israni Of Deloitte On Five Things You Need To Create A Highly Successful Career In The AI Industry

Artificial Intelligence is now the leading edge of technology, driving unprecedented advancements across sectors. From healthcare to finance, education to environment, the AI industry is witnessing a skyrocketing demand for professionals. However, the path to creating a successful career in AI is multifaceted and constantly evolving. What does it take and what does one need in order to create a highly successful career in AI?

In this interview series, we are talking to successful AI professionals, AI founders, AI CEOs, educators in the field, AI researchers, HR managers in tech companies, and anyone who holds authority in the realm of Artificial Intelligence to inspire and guide those who are eager to embark on this exciting career path.

As part of this series, we had the pleasure of interviewing Ruchika Israni.

Ruchika has a solid foundation in artificial intelligence (AI), data science, and product management and she has established herself as a leader within Deloitte Canada’s Artificial Intelligence Center of Excellence (AI CoE). This role encompasses steering AI solutions that substantially impact clients by championing ethical, transparent, and reliable AI practices. Her journey in the AI is bolstered by a solid educational foundation, holding a Master of Science in Information Management from Syracuse University, and is enriched with 13 years of invaluable experience across the U.S. and Canada at esteemed firms like CA Technologies and Deloitte.

Ruchika’s professional narrative is a witness to dedication and success within the field, underscored by numerous certifications and awards that signify expertise and contributions. Noteworthy accolades include a custom TREK bike for exemplifying CA Technologies’ DNA through top performance and a steadfast commitment to excellence.

At Deloitte, Ruchika leads a diverse team of engineers, analysts, and data scientists in launching impactful AI and Data products, achieving remarkable efficiencies and advancements in trustworthy AI. Beyond technical achievements, she is deeply committed to fostering diversity in technology, she has co-founded AI Product Management Study Group and actively contributing to the Women Defining AI (WDAI) and Women in AI (WAI) communities.

Thank you so much for joining us in this interview series! Before we dive in, our readers would like to learn a bit about your origin story. Can you share with us a bit about your childhood and how you grew up?

Thank you. I’m honored to be a part of this interview series.

I grew up in the bustling city of Mumbai, India, in a large and loving family. I was one of the few members in my family who decided to pursue a degree in technology, which was a bit of a departure from the more traditional career paths. However, my family was incredibly supportive of my decision. They encouraged me to follow my passion, even when I decided to move across the world to the United States for my higher education.

Looking back, I realize how fortunate I was to have such unwavering support, especially from the two most influential women in my life — my mother and my grandmother. These strong, graceful, and resilient ladies were my biggest cheerleaders, and they continue to inspire me every single day.

My mother has always been a beacon of strength and determination. Even during times of adversity, she reminds me that with dedication and a positive mindset, anything is possible. My grandmother was the embodiment of wisdom and resilience. She had lived through some of the most tumultuous periods in India’s history, and yet, she never lost her sense of optimism and zest for life.

In many ways, my origin story is a testament to the power of family and the transformative impact that strong, remarkable women can have on the lives of those around them.

Can you share with us the ‘backstory” of how you decided to pursue a career path in AI?

The story of how I decided to pursue a career in AI is one that is deeply personal and meaningful to me. It all began back in 2017, when I was working at my previous organization and looking to upskill in new and emerging technologies.

I have always had a profound respect for the work of healthcare professionals, and I came across an intriguing claim by one of the deeply respected founders of deep learning. He had stated that computers would soon make doctors obsolete, and that statement really piqued my curiosity. I probed deeper into the topic, and as I learned more about the advancements in deep learning, I found myself increasingly fascinated by the incredible potential of AI and machine learning. The idea that we could create systems that could mimic human intelligence in the medical field was thought-provoking.

Driven by this newfound fascination, I decided to take the plunge and enroll myself in a comprehensive course to learn more about AI and ML. It wasn’t just about the theoretical knowledge, though — I was determined to get my hands dirty with practical, hands-on projects as well.

From that moment on, there was no looking back. I immersed myself in the world of AI and as I plunged deeper into the field, I was particularly drawn to the ways in which AI could be leveraged to solve real-world problems — from improving healthcare outcomes to enhancing social welfare. The prospect of being able to contribute to these impactful applications fueled my drive.

Now as I reflect on my journey, I realize that it was that initial spark of curiosity and the desire to learn that set me on this path. It’s a story that I hope will inspire others to approach their own career journeys with a similar sense of curiosity and a willingness to embrace the unknown.

Can you tell our readers about the most interesting projects you are working on now?

While I’m afraid I can’t share details about the specific work projects I’m currently working on due to confidentiality reasons, I can tell you about some of the personal initiatives I’m involved in that I find quite fulfilling.

One of the most rewarding things I’m engaged with is co-founding an AI Product Management study group. What started as a small gathering of around 15 like-minded individuals has now grown into a vibrant community of over 130 people, all of us dedicated to learning and growing together in the field of AI product management. Through this group, we’ve been able to share knowledge and lessons learned from our respective experiences. It’s been tremendously valuable to connect with others who are navigating similar challenges and to collaborate on projects that push the boundaries of what’s possible in this rapidly evolving space.

In addition to this study group, I’m also an active participant in the Women Defining AI community, a network dedicated to supporting and empowering women in AI. As someone who is passionate about diversity and inclusion, I find great joy in contributing to this community and learning from the incredible women who are shaping the future of AI.

Most recently, I’ve taken on the role of Education Lead for the Women in AI Canada chapter. In this capacity, I’m working to develop and curate educational resources and certification programs that can help women from all backgrounds gain the skills and confidence they need to thrive in the AI field. It’s incredibly rewarding to be able to give back and play a part in creating a more inclusive and equitable AI industry.

While my day job is fulfilling, these personal initiatives allow me to explore my passions, collaborate with inspiring individuals, and contribute to the AI domain in a way that truly aligns with my values.

None of us are able to 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 about that?

Throughout my career, I’ve had the privilege of working with and learning from a number of remarkable individuals who have played pivotal roles in shaping my journey. However, if I had to single out one person who has been particularly instrumental in getting me to where I am today, it would be my former manager at my previous organization.

He took me under his wing, providing me with opportunities to work on high-profile initiatives and challenged me to step outside my comfort zone. He provided me with invaluable guidance, offering insights and suggestions that helped me navigate the complexities. He encouraged me to think creatively and to question assumptions.

Even after I eventually moved on to a new role, he has continued to be a steadfast supporter and trusted advisor.

As with any career path, the AI industry comes with its own set of challenges. Could you elaborate on some of the significant challenges you faced in your AI career and how you managed to overcome them?

As an AI leader, I’ve certainly faced my fair share of challenges throughout my career, but I’ve also learned invaluable lessons along the way. Let me share a few of the significant hurdles I’ve encountered and how I’ve managed to overcome them.

One of the challenges I’ve had to navigate is the tendency for businesses to view AI as a silver bullet that can solve any problem. In the early days, I often found myself having to educate stakeholders that not all AI projects will be successful and more recently, AI is not the answer to everything. To mitigate this, we’ve developed an approach to assessing product-market fit, which involves evaluating the business need, success metrics, assessing data quality, and technical feasibility before embarking on any AI initiative.

This has been crucial, as statistics show that up to 70% of AI projects end up in the proverbial graveyard due to a mismatch between expectations and reality. By taking the time to thoroughly assess the viability of a product upfront, we’ve been able to set realistic expectations and focus our efforts on the initiatives with the greatest potential for success.

Another challenge I’ve encountered is the inherently cross-functional nature of AI product development. It’s not enough to simply have a team of data scientists; you need to bring together a diverse set of skills and perspectives, including user experience experts, data engineers, data owners, legal, security and privacy professionals, and even diversity, equity, and inclusion specialists.

One personal challenge I’ve taken on is ensuring the AI we build is ethical and inclusive. As AI technology advances, so do the ethical considerations. It’s not just about what we can do with AI, but what we should do. This means constantly educating myself and my team on ethical AI practices, actively seeking diverse datasets to avoid bias, and ensuring the solutions we develop are accessible to a wide range of users.

Ok, let’s now move to the main part of our interview about AI. What are the 3 things that most excite you about the AI industry now? Why?

Absolutely, here are the 3 things that most excite me about the AI industry now:

Firstly, I’m thrilled by the advancements we’ve seen in natural language processing (NLP) in recent years. The ability of AI systems to understand, interpret, and generate human language has opened up so many new possibilities for how we can interact with and leverage technology. From automating mundane, repetitive tasks to enabling more natural and intuitive communication between humans and machines, NLP has the power to dramatically improve our productivity and free us up to focus on the higher-value, more meaningful aspects of our work.

Secondly, I’m in awe of the fact that we’re just scratching the surface of what AI is capable of. It’s been likened to the invention of electricity or fire — things that have fundamentally transformed the way we live and work. And just as those discoveries led to countless applications and use cases that were unimaginable at the time, I believe the future of AI holds an equally limitless array of possibilities that we’ve yet to even conceive of.

Third, AI is becoming more accessible to everyone, and this is exciting. With the rise of conversational AI, open-source AI tools and platforms, more people can experiment and build AI applications, regardless of their background or expertise. This democratization of AI will lead to more diverse and innovative solutions, as people from different backgrounds and industries bring their unique perspectives and ideas to the table.

What are the 3 things that concern you about the AI industry? Why? What should be done to address and alleviate those concerns?

Big tech companies have a huge say in AI because they have lots of data and the tech to do cool things with AI. But this can be a problem because it doesn’t leave much room for others to join in, and it could make things less diverse and fair. To address this, we should support the open-source AI projects. They’re doing great stuff but don’t always have the money or tools to keep up with the big players. Also, it would help if laws and rules were put in place to make sure there’s fair play and no one or few companies gets to hold all the cards in AI.

Secondly, AI moves super-fast, and that can be tough for people, especially if they’re not coming from a tech background. They might feel like they can’t catch up. To address this, we should make learning about AI more straightforward and offer mentorship and practical experiences that welcome everyone, no matter their starting point. Making AI easier to understand and use can also help bridge the gap between the tech heads and everyone else.

Lastly, as AI systems become increasingly capable and autonomous, the ethical considerations around their development and deployment have become increasingly complex. Issues such as algorithmic bias, privacy, transparency, and the societal impact of AI-powered decision-making must be rigorously addressed. We can work on this by setting up clear rules for how AI should be used and making sure there’s a way to check that these rules are followed. Plus, investing in learning and talking more about AI ethics is key to making sure AI helps us in ways that are good for everyone.

For a young person who would like to eventually make a career in AI, which skills and subjects do they need to learn?

For a young person interested in eventually making a career in the AI industry, I would encourage them to explore the diverse range of opportunities available, as not everyone needs to be an expert coder or have a deep technical background. For instance, an AI Product Manager, requires a strong understanding of AI/ML capabilities and limitations, ability to translate business requirements into effective AI-powered solutions, project management and cross-functional collaboration abilities. For an AI Policy Developer role, one needs deep knowledge of AI ethics, bias, privacy, and governance frameworks and policy writing and advocacy skills to shape regulations and guidelines. For User Experience (UX) Designer role, you require human-centered design skills to deeply understand user needs and pain points, expertise in interaction design and knowledge of AI/ML capabilities to envision innovative user experiences.

One of the most valuable things a young person can do is to start networking with individuals who are already successful in the various AI career paths that interest them.

During these informal meetings, I would suggest focusing on the following key areas:

• Understanding the day-to-day responsibilities and skill sets required for their particular role. This will help them gain a realistic perspective on what the job entails and whether it aligns with their interests.
• Identifying the educational and professional backgrounds of those in the role.
• Gaining insights into the challenges, mistakes, and lessons learned that the professionals have encountered throughout their journeys.
• Seeking advice on the best ways to prepare for and enter the field, such as relevant coursework, certifications, internships, or entry-level roles to consider.

In parallel, they should also research the foundational skills and knowledge that are commonly valued across any industry for instance, problem solving, critical thinking, data literacy, soft skills and emotional intelligence.

As you know, there are not that many women in the AI industry. Can you advise what is needed to engage more women in the AI industry?

As a passionate advocate for diversity and inclusion in the AI industry, this is a question that is near and dear to my heart. It’s a well-known fact that women are significantly underrepresented in AI, with only around 35% of women utilizing AI technologies compared to their male counterparts. Here are some steps that can be taken to engage more women in the AI industry:

1. Encourage experimentation: AI technology is no longer confined to highly technical resources or large tech companies. Today, with the spread of user-friendly tools and cloud-based platforms, AI is more accessible than ever before. This presents a unique opportunity to encourage women to experiment, get their hands dirty, and explore how AI can be leveraged to improve the quality of their lives and the lives of their communities.
2. Seek out communities: Women should seek out communities for support, mentorship, and collaboration. These communities can provide a safe space for women to share their experiences, ask questions, and learn from others.
3. Promote role models: We should promote role models of women who are successful in the AI field. This can inspire other women to pursue careers in AI and provide them with a clear path to success.
4. Address bias: The technology industry should actively work to address bias in AI algorithms, data sets, and hiring practices. This includes creating diverse teams that can identify and mitigate bias, and implementing fair and transparent recruitment processes.

Ethical AI development is a pressing concern in the industry. How do you approach the ethical implications of AI, and what steps do you believe individuals and organizations should take to ensure responsible and fair AI practices?

As a strong proponent of ethical AI development, I firmly believe that addressing the ethical implications of this transformative technology should be a top priority for both individuals and organizations working in AI.

I believe that AI systems and their decision-making processes must be understandable and explainable, not only to the developers and researchers but also to the end-users and the broader public. This level of transparency is essential in building trust and accountability.

Another crucial aspect is a relentless focus on mitigating bias. It’s well-documented that AI systems can easily perpetuate and amplify the biases present in the data used to train them. To address this, I advocate for the use of robust bias testing mechanisms, such as counterfactual fairness evaluations, to identify and address any unintended biases that may have crept into the AI models.

Equally important is the need to maintain a “human in the loop” approach, particularly for any AI-powered systems that have the potential to impact the lives of individuals. By ensuring that there are human oversight and decision-making processes in place, we can help to safeguard against the unintended consequences of relying on autonomous AI systems.

The privacy and consent of data owners is critical in AI development. This involves securing explicit consent for the use of personal data, ensuring data protection measures are in place, and maintaining the confidentiality and integrity of data. It also means giving individuals control over their data and respecting their choices regarding its use.

The ethical development of AI is a complex and multifaceted challenge, but one that I believe is absolutely essential to getting right.

Can you please share the “Five Things You Need To Create A Highly Successful Career In The AI Industry”?

1 . Learn the Basics First: Before diving into the more advanced aspects of AI, it’s essential to have a strong foundation in the fundamentals. A common challenge I’ve observed among executives and peers is the tendency to jump straight into advanced technologies like generative AI without first understanding the basics, such as the importance of high-quality, relevant data for solving business problems. Without this foundational knowledge, it’s easy to misapply AI solutions and end up with suboptimal results.

2 . Understand the Strengths and Limitations of AI: It’s crucial to have a deep understanding of the capabilities and limitations of AI technology in order to leverage it effectively for solving business problems. AI is a powerful tool, but it’s not a magic solution that can address every business problem.

One limitation I’ve observed is the difficulty of AI systems in dealing with complex, context-dependent tasks that require nuanced decision-making. For instance, while AI can excel at analyzing large volumes of financial data and identifying patterns, it may struggle to make the kind of holistic, strategic decisions that a seasoned finance professional would be able to make. Knowing when to rely on AI and when to involve human expertise is key to unlocking its full potential.

3 . Continuously Learn and Update Your Skills: The AI industry is rapidly evolving, with new breakthroughs and advancements happening at an incredibly fast pace. Staying up-to-date with the latest developments and continuously expanding your skillset is essential for maintaining a successful career in this field.

I make it a point to dedicate time each week to exploring new AI techniques, attending industry events/conferences, and engaging with online communities.

4 . Be Willing to Experiment and Dive into Hands-On Learning: In the world of AI, a willingness to experiment and get your hands dirty with practical applications is crucial. Theoretical knowledge is important, but ultimately, it’s the ability to translate that knowledge into working solutions that truly sets successful AI professionals apart.

I encourage my team to constantly seek out opportunities to apply their skills, whether it’s building personal projects, or collaborating on real-world client engagements. It’s through this hands-on experience that we can truly understand the nuances of AI development and the challenges of deploying models in production

5 . Chart your path: There are various roles in the AI domain, including data scientists, AI engineers, product managers, and policy/ethics experts. It’s essential to chart your path and choose a role that aligns with your interests and skills.

For instance, a professional with a legal background might consider a role in AI ethics and policy, while a software engineer might consider an AI engineering role.

Continuous learning and upskilling are vital in a dynamic field like AI. How do you approach ongoing education and stay up-to-date with the latest advancements in the AI industry? What advice do you have for those looking to grow their careers in AI?

Continuous learning and upskilling are crucial in the dynamic field of AI. As an AI leader, I approach my ongoing education with a combination of curiosity, strategic learning, and practical application.

I follow my natural curiosity to explore the latest advancements in the field. For instance, I recently came across the concept of “tree of thought prompting”. I also read about “mixture of experts” architecture used in a popular large language model. I dug deeper into the research and learned how experts are now combining “mixture of experts architecture” with “transformer” architectures (which is the ‘T’ in ChatGPT), leveraging the strengths of both approaches.

Inspired by this, I decided to experiment. I wrote a tree of thought prompt by making the model act like three distinct “experts,” each with their own specialized knowledge gaining deeper insights into the similarities and differences between these techniques.

In addition to this self-directed learning, I also actively seek out relevant courses, webinars, conferences and podcasts to expand my knowledge.

Additionally, I stay closely connected with Data Science and AI communities, both online and offline. Engaging with peers, participating in discussions help me stay up-to-date and identify emerging areas worth exploring. These interactions also allow me to share my own experiences and perspectives, fostering a collaborative exchange of ideas.

It’s important to remember that AI is always changing, and it’s impossible to know everything. Instead of trying to catch every update, I focus on the big ideas and the most useful new tools for my work or to help others.

For those looking to grow their careers in AI, I have two key pieces of advice. First, don’t feel like you’ve missed the boat — the field of AI is rapidly evolving, and there is still so much to explore and discover. In fact, this is an excellent time to dive into learning about AI and ML.

The second piece of advice is to seek out and engage with AI communities. These communities can provide invaluable knowledge, mentorship, and support as you develop your skills. At the same time, it’s crucial to complement this learning with hands-on experience through personal projects. The more you can put your knowledge into practice, the faster you’ll be able to grow your expertise in this dynamic field.

What is your favorite “Life Lesson Quote”? Can you share a story of how that had relevance to your own life?

Sheryl Sandberg’s quote from “Lean In” about self-advocacy, “We hold ourselves back in ways both big and small, by lacking self-confidence, by not raising our hands, and by pulling back when we should be leaning in,” has influenced my approach while working in tech. This principle highlights the importance of self-belief and taking action, especially for women and underrepresented groups in tech.

Early in my career, I hesitated to present a significant project to executives, fearing I wasn’t ready. Remembering Sandberg’s words, I chose to advocate for myself and share my work confidently.

This lesson has shaped my career, encouraging me to seize opportunities, and speak up in meetings. Self-advocacy has not only propelled my growth but also inspired others to pursue their goals. Embracing this mindset is crucial in fields like AI, where innovation and leadership can drive significant progress.

You are a person of great influence. If you could start a movement that would bring the most amount of good to the most amount of people, what would that be? You never know what your idea can trigger. :-)

I am passionate about harnessing the power of collective positive action to bring the most good to the most people. By committing acts of kindness and volunteering time and talents, individuals can bring positive change to their local and global communities.

In a divided world, tapping into human compassion is key to unlocking transformative change. Through this movement, I aim to strengthen the interconnectedness of people and foster a sense of shared responsibility and belonging. The fact is, when we support others, we ourselves are being supported; when we help others, we ourselves are actually being helped. Imagine a future where people are empowered and encouraged to look beyond their own immediate needs and actively contribute to the greater good of society.

The potential for such a movement to catalyze positive change is boundless. From addressing global crises like poverty, disease, and climate change, to strengthening the social fabric of our communities, the combined force of compassionate people working together can reshape the world in profound and enduring ways.

We’d need to work with lots of different people to make this happen, like charities, government, and tech companies. But I believe if we start with the simple idea of helping out where we can, we can do a lot of good.

How can our readers further follow your work online?

Readers who are interested in following my work and staying up-to-date with my latest activities can connect with me on LinkedIn. I regularly post updates on the projects and the challenges I’m tackling, and my learnings in the field of AI. I’m always eager to connect with like-minded individuals who share my passion for creating positive change through the responsible development of AI.

This was very inspiring. Thank you so much for joining us!

About The Interviewer: David Leichner is a veteran of the Israeli high-tech industry with significant experience in the areas of cyber and security, enterprise software and communications. At Cybellum, a leading provider of Product Security Lifecycle Management, David is responsible for creating and executing the marketing strategy and managing the global marketing team that forms the foundation for Cybellum’s product and market penetration. Prior to Cybellum, David was CMO at SQream and VP Sales and Marketing at endpoint protection vendor, Cynet. David is a member of the Board of Trustees of the Jerusalem Technology College. He holds a BA in Information Systems Management and an MBA in International Business from the City University of New York.