Monica Bhardwaj leads the GTM area for Data Platform Modernization and serves as a seasoned SME for Data and AI Governance for client consultations.

Monica has been recognized as a Delegate at Harvard University, Boston, USA, for the Corporate Strategy Panel during HPAIR 2016.

INDIAai interviewed Monica to get her perspective on AI.

First, tell us about your experience as a Business and Integration Architecture specialist.

I have been working as a Business and Integration Architecture specialist at Accenture since 2017, and the journey has strongly inculcated the company ethos in my approach to measuring success with sustainable value delivered in all directions. It includes working with multiple clients across geographies on cutting-edge technology and supporting them in achieving their Data and AI Transformation goals. During my projects, I have worked in varying industries such as Banking and Investment, Consumer Goods and Services, Telecom, Hospitality, Lifesciences, etc.

At the intersection of business problems and technology solutions, I learned that data is at the core of the new technology revolution, and data-adept digital-native companies are capitalizing on data and AI to unlock new consumer experiences and new product offerings with efficiency at scale. Within the vast field, I have gained expertise supporting clients over the years around Data and AI Governance, a niche area to define frameworks to help work with data and AI technology solutions with responsible ownership. In the current scenario, this holds immense value as we are in the midst of the AI revolution, where the guardrails to ensure ethical use of innovations are being identified and defined as we progress.             

How did you get started in Data and Analytics?

My journey in the technology field, which led to Data and Analytics, started young when I got recognized by the Govt of India among the "Top 200 Programmers" in the country through an Informatics Olympiad at the age of 17. It encouraged and motivated me to pursue a BTech in Computer Science, and I joined Tata Consultancy Services in 2012 as a Business Data Analyst through campus placement. I gained valuable technology experience in the projects but was keen to understand the business perspective. Hence, I worked in the role for three years and pursued an MBA from Dubai. I challenged myself to explore a new country as this would enrich my academic and professional knowledge via work experiences in organizations in the UAE. 

During my MBA, I consciously chose courses and internships to supplement my technology background, such as statistics, digital transformations, etc. I joined Accenture upon returning to India in 2017 and started working on projects around data and analytics. During that time, I upskilled myself in Data Governance and AI through training and hands-on experience in client projects. I developed a unique perspective on organizations' challenges during their data and AI transformation journeys. With each engagement, I learned and understood more about extracting data's intrinsic value through analytics.    

What are your duties and responsibilities at Accenture as a BIAS?

My responsibilities in the role are a combination of technical and business-oriented tasks. 

I am initially involved in data landscape assessments and strategy creation during the client project lifecycle. It involves senior stakeholder management and understanding the pain points of the clients. In an Agile approach, I work with multi-functional teams, which means that the output of the business analysis phase is taken back to technical teams where we deliberate on the solution at a functional level and then, based on deep data evaluations, we work with technologies around GenAI, Knowledge Graphs, Data Governance suites etc. to bring to the client most optimized solutions. 

Additionally, I contribute to thought leadership by curating POVs (Points of View) on different industries, Data and AI Governance, GenAI, LLMs, etc., which help democratize knowledge among our colleagues and friends. Accenture also provides a great platform to work on cutting-edge technologies through accelerators and Centers of Excellence, which has always excited me about my role. Mentorship is again a key ethos in the company, and I have always received great career/knowledge-building guidance. Hence, I consistently mentor folks interested in Data and AI.    

What were the initial challenges you faced in the field? How did you overcome them?

The initial challenge while I was trying to rotate to Data and AI was twofold – to learn AI tech while belonging to another technology area and to get hands-on experience to showcase my knowledge and build it further. 

The first one was easier to tackle, especially with the myriad of company training and online courses now available via Coursera, LinkedIn Learning, Khan Academy, and even something as simple as YouTube or Instagram channels. I learnt more practical knowledge from accessible avenues such as YouTube channels and Instagram groups because the motivation of the content creator is simple – Get More Views, and the way they achieve that is by creating knowledge-rich, concentrated content. A 30-minute video summarized 8-hour courses for me with all the essential topics highlighted, and a video of a hands-on experience on a new AI tool as icing on the cake (Think about Midjourney, Jasper, QuestAI, Leonardo, etc.).

Second, it was time to find myself a formal role in AI. I needed focused effort and planning. As a professional in a big technology company – I started seeking out positions of my interest in AI based on proper certifications in relevant areas and practical understanding of concepts. It took some time, but I was relentless, folks! I offered to support teams working in the area as a shadow resource and was willing to go back to basics to be like an INTERN. It allowed me to view practical applications and helped me network and trust building with project managers. Hence, my biggest takeaway was one must be open to dropping any misconceptions about the vast scope of our current knowledge and START learning as a student with a fresh set of eyes and an inquisitive passion.

What is the one attribute that each AI expert must possess?

To understand AI technology, one needs to have an insight into data and human behaviour, which is the basis of this technology. Hence, every AI expert must be willing to look at every problem and possible solutions without the natural bias of past knowledge and experiences. A problem-solving approach while ensuring effectiveness and ethics is paramount.   

What advice would you give to students and professionals interested in pursuing a vocation in artificial intelligence?

Let me share my approach to learning Artificial Intelligence through key actions:

1. Become a Lifelong Learner and Expand Your Knowledge about AI via experience: START ASKING QUESTIONS TODAY ON Try Bard, an AI experiment by Google 

2. Identify and complete academic, company-sponsored or professional courses that provide initial support to understand the technology and award credibility to your skillset.

3. Find Your Role Model: Everyone can build their networks and find mentors to help them navigate the AI field. Some of my mentors and role models include people whom I have connected with over LinkedIn. The knowledge sharing on such platforms is immense, and I encourage you to be a mentee and a thought leader for others.  

4. Find the Role you aspire to, prepare for it and get it!

What are some of the most intriguing research articles and publications you have encountered while researching AI? 

I am aware of exciting work being done in our company in the field of Responsible AI, an area of great interest to me. This article by Accenture, in particular, discusses the ethical impacts of processing vast amounts of real-time streaming data by companies worldwide. One can read more here: From AI Compliance to Competitive Advantage | Accenture