Women are increasingly breaking barriers across various organizations and industries, including artificial intelligence (AI). Many women AI leaders serve as role models for others, inspiring countless women to pursue careers in this rapidly advancing field. One such influential figure is Poornima Ramaswamy, who has over 25 years of experience in the data and AI space. She has witnessed the evolution of this field, from its earlier days as Decision Support Systems to the current GenAI era.
Throughout her career, Poornima has observed transformations in data technology, from data warehouses and data lakes to big data and the emergence of large and small language models, BI, AI, and augmented BI. Despite initially entering the field fresh out of business school without knowing what to expect, she has been captivated by the possibilities of data and AI from the very beginning and has remained committed to this space ever since.
After more than two decades of consulting and advising clients and experiencing the data space from various perspectives, including consultant, business leader, channel leader, and customer, Poornima decided to launch PivotX Advisors (PXA), a boutique Data and GenAI strategy and consulting services firm. Her goal with PivotX Advisors as its Founder and CEO is to leverage her and her teams’ extensive knowledge and experiences to directly assist clients. PXA takes a unique approach to data to unlock its full potential in individualizing experiences and creating data-centric businesses.
Data’s transformative period has grown exponentially over the past 2–3 years due to Generative AI (GenAI). PXA and Poornima believe that, with a responsible approach, one can create solutions that empower humanity.
In this article, Poornima shares her thoughts on the current market, why organizations need to embrace a data-centric approach, and how the power of data has never been greater.
As the founder and CEO, what inspired you to focus on AI, data, and digital solutions?
Progressively over the years, we have embraced the power of data to unlock our ability to make decisions based on facts and figures combined with context and experience. Now more than ever, we can realize this potential while also embedding data and GenAI-powered insights into every interface, service, and product, be it digital or physical.
We’ve always imagined the possibility of creating intuitive and personalized experiences through data. That has yet to be realized at an individual level. We have been creating solutions that are data-driven and standardized templates at a role or persona level and not individualized. With GenAI, it’s easy to envision a world where we can reimagine businesses and business models to be data-centric at scale while creating experiences that are unique and realizing the potential of individualization.
I believe we truly are at a tipping point in leveraging data, which is more complex and complicated than ever, to combine context and experience and drive individualization. PivotX was born to help our customers navigate this complexity and get to the next era of individualization in the world of contextual insights and data decisions.
What motivates you the most in your role, and how do you stay innovative in the rapidly evolving field of AI and data?
The rapid evolution has always kept me motivated to give it my best every day over the last 25 years. Since the time I’ve been in this space, it’s always been one of the top 5 priorities for the CIO, and now it’s among the top 5 priorities for the board.
While I always keep up with market movements and innovations in the industry, it just doesn’t feel right if I’m not speaking to customers every day to understand the implications of the new and the old for them and their businesses.
It’s one thing to be fascinated by technology and its possibilities, but I’ve seen firsthand that the thin line between ambition, aspiration, and realization is the human factor. While businesses are entities, the success of any solution is when we are able to make it work for the people in those businesses for their roles in the value chains and day-to-day decisions. It’s the intersection between people, technology, and value that I’m trying to form my own opinions and approaches on. That’s how I keep myself updated, relevant, and valuable to my customers and teams.
How do you cope with the data deluge to determine which data will create insights and generate value and which is just noise?
When customers are faced with a data deluge, which is basically every customer, we advise them to align with business priorities and corporate objectives before they embark on any data-centric solutions. At PXA, we believe in an approach called Data as a Product, which aims to create data and AI products that can be embedded into business value chains, interfaces, and decision-making platforms. We have a clear, three-step process to help align and focus efforts.
- We identify business value chains that can be transformed by embedding data and generating AI-driven insights.
- We design the business outcome of each business value chain and align with a corporate objectives framework (OKR framework) to prioritize the opportunities with the biggest ROI.
- We then lay out the data needs that impact the most valuable identified opportunities.
This framework marries data-centric solution demand with an OKR framework and a business scorecard framework. Once prioritization is done, it is critical to map out the user journey and user experience for the prioritized business value chains.
This is different from the “grab and store all the data that comes your way” model that many organizations follow today. Instead, it focuses on putting precious resources—people, technical, and investment—against measurable and valuable business needs.
This is also backed by a very structured business-IT operating model and alignment process framework, along with a value measurement framework that we have defined. Following this process includes adoption and change management elements, which are designed along with the prioritization process. The result is an approach that brings product management discipline, design thinking practices, and agile principles to the world of data and AI.
What strategies do you employ to identify the most valuable categories of data and glean real-time insights for your clients?
We need to realize that the world of decisions is fluid and not divided into mutually exclusive categories: transactional data and decisions, operational data and decisions, and analytical data and decisions. We, as humans, don’t compartmentalize our decisions that way. We are always living in multiple realms of data within the same decision context.
So as data and AI professionals, we need to change our thinking in terms of block diagrams of left-to-right, top-to-bottom linear solutions. We need more non-linear approaches and applications of data to solve business needs. If real-time is needed in these contexts, today’s technologies can definitely help enable them.
How do you ensure that the capabilities you develop are effectively integrated into operational systems and accessible to decision-makers across various sectors?
It starts with understanding what the people in business value chains do every day, every month, and every quarter. We can then identify the role that data and GenAI can play in these value chains to automate, augment, and assist in reimagining roles to focus on higher-value tasks.
Today’s solutions are too focused on doing projects to solve use cases. The result is point solutions without considering the overall context of the user journey. These solutions lack the crucial context and experience that the humans in the loop deserve. When we start with humans first, business value chain next, and data opportunity third, we naturally create data-centric solutions where data and GenAI are invisible in the solution. For the user, this experience leads to a new and natural way of doing their day-to-day role more intuitively and easily.
It’s like how my 78-year-old mother, who is into mobile games, can very easily figure out these games without even going through a training module. Or my 2-year-old nephew, who just watches us tap the phone, and in two days he knows how to search on the phone and where to tap to watch wheels on the bus—especially the “yeyyow” bus version!
What are some of the key trends or advancements we can expect to see in AI and data technologies in the coming years?
GenAI is going to be a great equalizer and normalizer. Yes, there are 10 or so larger tech firms and enterprise institutions that are creating the foundational tech platforms, or domain-centric platforms. However, beyond that, we do believe we are going to see a race to democratize GenAI and embed it everywhere.
It’s going to be embedded in solutions in such a way that a continuum of data—BI, ML, and GenAI—will all power a given user journey. It’s important to note that, although I believe it’s going to reshape businesses and business models, we must figure out the governance and improve trust in the solutions to ensure widespread adoption.
Data is going to be reshaped to break down silos across transactional data, operational data, analytical data, and real-time data. There is going to come a time when we can create trust and privacy scores for data as it is created by the source. Data will travel with a data signature, which will help us avoid doing these massive one-time clean-ups. This will provide the opportunity for the data creators to improve trust during the creation process and as close to real-time as possible.
I imagine it being like having a Roomba for data that will follow you everywhere and clean up after you without you having to disrupt your day. I do think there will be a time when that’s possible because of GenAI.
How do you balance the need for innovation with the practical considerations of implementing AI and data solutions in real-world business environments?
It’s a mindset question, not a technology question. We need to think about creating human-empowering solutions and not just faster horse-drawn carriages. It needs to be so simple and intuitive that we empower humans to do what we do best—think responsibly and act responsibly in context, armed with the insights and information needed for the moment.
We also need to expand our framework from just Build vs. Buy to Build, Buy, and Assemble. We need to create solutions that will either solve a business need or help businesses reframe and reimagine their business, role, or function. Business can’t always be thinking about the next shiny new technology. They are looking for technology to be an accelerator to grow their business.
How do you foster a culture of collaboration and innovation within your organization?
My personal belief is that we are in a knowledge world. In such a world, titles and positions are just meant for assigning accountability.
Another belief I have is that just because it’s always been done that way doesn’t mean it’s the right way to do it. We must foster a culture of challenging our own thinking and our assumptions.
While challenging thinking and assumptions are critical, I am also a strong believer that while making decisions on anything (solutions, operational decisions), we can debate, discuss, and deliberate up to the point where we’ve made the decision. Once we’ve decided, we are not going to double-guess ourselves or keep debating it.
We jump into it as one team, regardless of whether we agree with the decision or not. We drive forward with the mindset of learning from any failures in case the decision is wrong. No decision or action is wrong as long as we learn from our mistakes. Fail fast, and learn fast.
How do you approach leadership, and what values do you prioritize in your team?
The main philosophy driving all our decisions will be, “Make it Better Than We Found It.”
In every interaction and engagement—whether with customers, the community, or our colleagues—we aim to leave things better than we started. Our focus is to create an organization that focuses on doing right by our customers, our teams, and the business in that order. I honestly think about it in terms of creating long term solutions with an amazing team of people for problems that are important for my clients.
We have a clear list of values we prioritize:
- Lead from the front while also being in the trenches with my teams.
- Walk in our customers’ shoes. Think about not just the technical solution, but everything required to drive the outcome from the solution.
- Never compromising on quality.
- Be agile in action and thinking.
- Stay hungry—never get complacent about our expertise and learning.
- Be open to all ideas while working as one unit.
- Last and most important, have fun with whatever we undertake!
What advice would you give to aspiring entrepreneurs or professionals looking to enter the AI and data industries?
Whether you know it or not, everyone is using data and AI in their lives. My good friend James says that data is what makes the world go from analog to digital.
So I don’t really think it’s about “getting into data and AI,” but more about how we embrace data and AI to be a force multiplier in our daily personal lives and our business worlds. We shouldn’t think about it as training people on data and AI to become technology specialists in it (unless that’s your chosen profession!). Instead, be aware of the possibilities for reimagining your businesses, business models, and creating competitive markets through data and GenAI.
In terms of entrepreneurs, ask me that question in two years! I have just started my entrepreneurial journey and have loads to learn about myself before I can dole out any meaningful advice.
