Balakrishna (Bali) D.R. of Infosys: How Infosys Scales Enterprise AI by Combining Cross-Functional Teams and Human-Centric Innovation

As part of our series about the future of Artificial Intelligence, I had the pleasure of interviewing Balakrishna (Bali) D.R.

Bali is an executive vice president and heads the delivery for ECS business unit of Infosys catering to energy, utilities, telecommunication, media, entertainment, and services industries. He also heads the AI and Automation unit for Infosys and is responsible for driving both internal automation and providing independent automation services leveraging market-leading products for clients. Bali has been with Infosys for more than 25 years and has held sales, program management, and delivery roles across different geographies and industry verticals.

Thank you so much for joining us in this interview series! Can you share with us the ‘backstory” of how you decided to pursue this career path in AI?

I have been with Infosys for more than three decades, delivering large digital transformation programs for Fortune 500 clients. I spearheaded the creation of new verticals in Infosys, opened new markets and expanded businesses across industries and service lines, spanning all major global markets creating industry-leading growth.

During my stint at data-warehousing for a multi-national tech company, I was fascinated to see how insights are uncovered from enterprise data and how it can be leveraged to transform core business operations. I realized that there is tremendous value that can be unlocked for enterprises if we can develop a platform that can converge AI, analytics, and cloud to unleash the power of the treasure troves of data remaining under-utilized in different organizations.

I also realized then that humanity was slowly reaching an inflection point in AI. A new era was on the horizon, where a wave of AI technology would revolutionize all industries and be embedded into the fabric of society itself.

These realizations, along with questions of how to democratize AI across enterprises and help them scale AI from simple point solutions, inspired some of us at Infosys to consolidate our AI offerings. We developed a new service line and invested in constructing state-of-the-art AI solutions, platforms, and frameworks. From there, I started my journey as the head of AI in Infosys, and it has been an exhilarating experience working on solving some of toughest challenges in the industry.

What lessons can others learn from your story?

I have gathered many invaluable lessons from working with some of the leading enterprises on their burning business problems and using AI. Some of these lessons include:

• The value of executive support in AI projects: Executive sponsors have the authority and influence to champion AI projects. Their endorsement lends credibility and encourages broader acceptance and adoption of AI initiatives within the organization. They also need to be actively involved in building a roadmap, fast-tracking resource acquisition, overcoming hurdles by securing stakeholder buy-in, resolving conflicts during transition, and building a partnership ecosystem.
• Teamwork makes AI work: The success of AI initiatives in an enterprise depends on cross-functional, interdisciplinary collaboration. These can no longer be solely driven by data scientists and ML engineers working in siloed labs. With generative AI rapidly evolving at a breakneck speed, we need experts from legal teams, domain consultants, change managers, UI/UX designers, etc. Proper representation ensures that the team is not limited to a narrow definition of the business problem, as well as sensitizes us to various biases and lapses that we have been overlooking in model building and training.
• It’s Human + AI and not Human vs. AI: We need to foster new ways of thinking and shift our mindset on how we look at AI initiatives. All AI initiatives should focus on amplifying human potential, and not just improving the bottom line. These initiatives should have a broad strategic goal that is communicated clearly to all stakeholders. It should be human-centric, which will help keep it rooted in ethical and responsible AI principles.

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

Presently, I am leading multiple AI initiatives at Infosys that incorporate AI into all of our internal business functions, in order to transform Infosys into an AI-first organization. This includes embedding AI into internal systems for employee experience and administration, building AI-powered smart campuses, using generative AI in employee training and software engineering, etc. We have also recently launched Infosys Topaz, an AI-first set of services, solutions, and platforms that accelerates business value for global enterprises using generative AI. Infosys Topaz brings the advantage of 12,000+ AI use cases, 150+ pre-trained AI models, 10+ AI platforms, steered by AI-first specialists and data strategists. With a ‘responsible by design’ approach at its core, it ensures uncompromising ethics, trust, privacy, security, and regulatory compliance.

I am also working on energy-as-a-service solutions, which are powered by AI at its core for optimization and predictive intelligence. I am also working on complex Vision AI use cases in retail, manufacturing, and telecom by leveraging autonomous drones. Some of the other interesting use-cases include leveraging generative AI for capabilities like document summarization, semantic search, contact center transformation and AI-augmented software engineering.

None of us are able to achieve success without some help along the way. Is there a particular person who you are grateful towards who helped get you to where you are? Can you share a story about that?

I am deeply indebted to Infosys’s Founder and Chairman Nandan Nilekani for inspiring us to be an AI-first live enterprise. His visionary leadership in shaping Infosys and also helping navigate the digital future has paved the way for my success. His unlimited energy, passion, drive, and hunger for continuous learning and self-improvement has motivated me to push my boundaries. His focus on AI and leveraging it to transform the enterprise landscape has provided me with ideas, insights, and unique perspectives in tackling complex business challenges.

I would also like to thank our CEO Salil Parekh. His ability to navigate complex market dynamics with precision and foresight, and his commitment to fostering a culture of innovation and excellence is evident in every aspect of our organization and has made a profound impact on myself and all those who has the privilege of working with him. His viewpoints and wisdom have been a source of constant inspiration in my AI journey and I look towards him for guidance and thought leadership.

What are the 5 things that most excite you about the AI industry? Why?

Some of the exciting developments that we can expect in the coming days in the field of AI are:

1. Generative AI: Generative AI is present in sales and marketing, improving overall customer experience in services management, developing engaging content and also changing the software engineering cycle. With enhanced multi-modal capabilities to synthesize images, audio, video, text and even more powerful language models, there is an endless number of possibilities to explore in media and entertainment, marketing and advertising, traditional work routines, etc. Coupled with capabilities like speech recognition, conversational AI agents will transform customer experience in lots of industries across the board. Generative AI applications in synthetic data generation are also exciting areas that I am looking forward to exploring.
2. Vision AI: Powerful models such as Computer Vision and Edge AI come together to transform retail (inventory management, store heat maps, shrinkage detection, hyper-personalization), CPG (warehouse automation, automated picking and sorting), manufacturing (defect and quality inspection), safety and security inspection, etc. When coupled with the power of drones and UAV’s, these can actually reduce perilous jobs for humans. With most of the heavy lifting happening at the edge, it will be possible to do far more tasks in real time. A related field where we can expect a lot of traction is autonomous vehicular systems. Autonomous mobile vehicles will enter several walks of industries like logistics, transportation, manufacturing, improving efficiency and reducing strain on human labor.
3. Metaverse/Digital Twins/AR/VR: We can expect this to be used in designing new equipment, factory layouts, simulation-based employee training, and also in retail to give a novel customer experience.
4. AI in Cyber-security: AI can power traditional security systems as well as can improve digital fingerprinting, sensitive information detection, deepfake detection, crypto-mining malware detection, and phishing and ransomware detection.
5. Physics Informed Neural Networks: This is an exciting field that can revolutionize core engineering research and development. When we embed the laws of the universe into our AI models, they can predict, detect, and simulate physical systems, giving us much needed insight to build sophisticated physical systems.

What are the 5 things that concern you about the AI industry? Why?

When considering the AI industry, there are several important concerns that individuals and society should be mindful of. Here are five key areas of concern and why they matter:

Policy and Governance landscape is lagging technical development: The ethical considerations surrounding AI are crucial. If AI systems are used maliciously, they could cause severe harm. For instance, generative AI could be used to create very convincing deepfakes and synthetic content that can be passed off as authentic news for disseminating misinformation for nefarious purposes. AI chatbots have also been known to generate toxic content from time to time. Similarly, development of autonomous weapons or applications in cyber-crime could pose threats to global security. It’s important to ensure that AI is developed and deployed responsibly, with proper oversight and adherence to ethical principles. In this regard, there is a lack of adequate policy guidelines and laws surrounding these systems, although lately the conversations are picking up momentum and that is promising.

Reducing carbon footprint of AI: AI models and algorithms require significant computational power, which often leads to high energy consumption. Training deep learning models, for example, can consume substantial amounts of electricity, contributing to greenhouse gas emissions if the electricity comes from fossil fuel-based sources. The energy demands of an AI infrastructure, including data centers, can have a substantial carbon footprint.

We need to focus on developing advanced technology solutions for ensuring Data Privacy, Security and IP protection: AI systems often rely on vast amounts of data to function effectively. The collection, storage, and analysis of personal data raises concerns about privacy and security. Safeguarding sensitive information and establishing robust security measures are crucial to prevent data breaches, identity theft, copyright infringement or the misuse of personal information by malicious actors. There are lots of security attacks that can happen on AI systems like data poisoning, inference attacks (attacking an AI model with different inputs to infer sensitive data), etc. There is relatively low volume of technical research on how these safeguards can be built into AI systems, and that is one area I believe we should all be focusing on.

Transparency and explainability: Many AI models operate as black boxes, making it challenging to understand how decisions are made. Lack of transparency and explainability can lead to distrust and hinder accountability. It is important to develop AI systems that provide clear explanations for their decisions, especially in sensitive areas like healthcare, criminal justice, and finance. We need to put emphasis on building systems that can explain the behavior of complex AI systems to users, as this would go a long way in building trust.

Bias and fairness: AI algorithms can inherit biases present in the data that they are trained on, leading to discriminatory outcomes. This bias can perpetuate social inequalities and exacerbate existing biases in society. It is crucial to address bias and ensure fairness in AI systems through diverse and inclusive data collection, rigorous testing, and ongoing monitoring to mitigate unintended consequences.

By being aware of these concerns and actively addressing them, we can strive to create an AI industry that benefits society while minimizing potential risks and negative impacts.

As you know, there is an ongoing debate between prominent scientists, (personified as a debate between Elon Musk and Mark Zuckerberg,) about whether advanced AI poses an existential danger to humanity. What is your position about this?

There is no denying that there are certain risks inherent in AI systems such as the ones I already touched upon. But none of these risks are unavoidable. Mitigating the risks associated with advanced AI, particularly artificial general intelligence (AGI), requires a multi-faceted and collaborative approach involving various stakeholders. I believe that responsible and ethical AI development should be at the heart of all AI-related services and pursuits.

At Infosys, we have built technical and policy-driven guardrails for safeguarding enterprises and societies against potential risks of generative AI and LLM models. Particularly in the context of generative AI, there are numerous concerns like copyright infringement, privacy violations, spread of misinformation and hallucinations. We are trying to build a strong moderation layer over these foundation models which can mitigate the harm without compromising on the performance and the quality of the output. Lastly, all organizations should come forward and foster an atmosphere of collaboration and share their best practices on how they are self-regulating and work with policy makers to improve the safety of the AI ecosystem. If we do the above, we can certainly increase the trust of different stakeholders in AI systems.

What can be done to prevent such concerns from materializing? And what can be done to assure the public that there is nothing to be concerned about?

Here are some strategies to address these risks:

Technical Safety Measures: Implementing technical safety measures is essential to minimize risks. This includes developing AI systems with built-in safety features, such as value alignment, interpretability, and robustness to adversarial attacks. Research on tools that can ensure data privacy, transparency, and bias mitigation can contribute to safer AI systems.

Ethical Frameworks and Guidelines: Establishing ethical frameworks and guidelines for AI development and deployment is important. Governments, industry leaders, and organizations can collaborate to define standards, principles, and best practices to ensure the responsible and ethical use of AI technologies. Efforts should focus on developing AI systems that are aligned with human values and goals.

International Cooperation: International collaboration and coordination is crucial to address AGI risks effectively. Governments and organizations should engage in dialogue and establish global partnerships to share knowledge, coordinate regulatory efforts, and collectively address the challenges associated with advanced AI.

Public Engagement and Education: Promoting public awareness and understanding of AI and AGI risks is essential. Educating the public about the potential impacts, benefits, and risks of AGI can foster informed discussions, encourage responsible development, and empower individuals to participate in shaping AI policies.

Policy and Regulation: Governments can play a vital role in creating regulations and policies that address the risks of AGI. Policies may cover safety standards, transparency requirements, accountability mechanisms, and frameworks for auditing and certifying AI systems. Regulations should strike a balance between fostering innovation and ensuring public safety.

How have you used your success to bring goodness to the world? Can you share a story?

I have worked with the organization Street Child, and their mission to provide meaningful educational opportunities for all children deeply resonates with me. We are supporting them using our technological expertise to create social impact and trying to ensure that all children have access to the education they deserve.

In one AI project, we tried to develop accessibility-related solutions for hearing and visually impaired people to enjoy television programs using AI. We built a visual and audio captioning system that generates both audio and visual descriptions of scenes and dialogues so that the impaired people can perceive them. This project brought me a lot of satisfaction, as we used technology to create an inclusive world for the differently-abled.

We are also working with several leading think tanks, academia, government agencies and industry bodies to accelerate the development of robust AI governance frameworks so that AI systems are safe and used ethically and responsibly.

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

To engage more women in the AI industry, several steps can be taken:

Raising awareness at an early stage: Encourage girls and young women to pursue education and careers in AI by providing them with information about the field, its potential, and the opportunities available. Promote AI-related programs, courses, and workshops specifically targeting women. Collaborate with schools, universities, and organizations to organize AI-related events, workshops, and programs specifically targeted at women. Collaborate with educational institutions to integrate AI and related technologies into the curriculum at all levels. Encourage and support women to pursue STEM education paths and provide scholarships or financial aid for women interested in AI-related fields. We have launched the Tech-cohere initiative, a program that reached out to 7000+ women engineers and focuses on nurturing and building a vibrant, collaborative tech community of engineers, architects, and technologists to learn, share, teach, practice and refine architecture, design and software engineering practices.

Role models and mentorship: Highlight the achievements and success stories of women in AI. By showcasing female role models, it becomes easier for aspiring women to envision themselves in similar roles. Establish mentorship programs that connect experienced women in AI with aspiring women to provide guidance and support. In this vein, our IamtheFuture program has received external acclaim and recognition in reputed forums including the Brandon Hall Gold Award for Best Advance in Leadership Development for Women and the Women Icons Asia D&I Champions Award in the category of advancement of women in 2022.

Networking and community building: Create and support networks and communities where women in AI can connect, collaborate, and share experiences. These networks can provide valuable support, advice, and opportunities for professional growth. At Infosys, we have instituted DEI councils across regions with formal charters and defined roles and responsibilities for facilitating this. Our engagement with the Confederation of Indian Industries (CII) IWN and National Association of Software and Services Companies (NASSCOM) in India has helped us bring mentoring sessions and learning in the new and emerging technologies to women at Infosys from industry experts.

Address biases and gender stereotypes: Raise awareness about unconscious biases that may exist in the AI industry and work towards eliminating them. Encourage workplaces to promote inclusive practices and ensure equal opportunities for women to advance in their careers. This includes promoting flexible work policies, implementing diversity training, and ensuring fair hiring and promotion practices. We have launched trainings and e-learnings on Unconscious Bias that have been very well-received by all Infosys employees.

Address the gender gap in AI research: Encourage and support women’s participation in AI research by providing grants, scholarships, and fellowships specifically aimed at women researchers. Highlight the importance of diverse perspectives in AI research and its impact on addressing bias and developing ethical AI systems. As a part of our Tech-cohere initiative, we conducted over 50 sessions and panel discussions by women technologists, 11 white papers and 37 POVs authored by women technologists were published.

Policy and industry initiatives: Advocate for policies and initiatives that promote gender equality and diversity in the AI industry. Encourage companies and organizations to set diversity targets, monitor progress, and publicly report on their efforts.

By implementing these strategies, we can help create a more inclusive and diverse AI industry, empowering women to contribute their unique perspectives and talents to this rapidly growing field.

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

“Any sufficiently advanced technology is indistinguishable from magic.” — Arthur C. Clarke.

This quote by the famous science fiction writer is very relevant in this era of advanced AI. Sophisticated AI systems are often not fully understood by the average user, and this engenders a fear of the unknown. This fear causes one to believe in various doomsday scenarios regarding AI, like rogue AI taking over the world, AI causing mass unemployment, etc. However, if we attempt to develop a deeper understanding of AI, we can alleviate these fears and realize the tremendous power that AI has to amplify human potential.

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. :-)

AI has the potential to solve some of the toughest problems of our times like climate change, income inequality, affordable education, breakthroughs in medical science, advancement in fundamental sciences, etc. The movement I would like to start, (in some ways this might have already started), is to encourage all to unleash the fullest extent of our creativity and start envisioning use-cases that can make significant impact in our communities to promote a free, fair, and inclusive society. Leveraging AI to solve some of the burning social problems of our times, improving and touching the lives of countless individuals.

How can our readers further follow your work online?

You can follow me on LinkedIn Bali (Balakrishna) D.

Thank you so much for joining us. This was very inspirational, and we wish you continued success in your important work.

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.