Transforming Enterprises through Artificial Intelligence
Rogayeh Tabrizi, Co-Founder, CEO, Theory+Practice, a company offering a large bouquet of services including data analysis and strategies, automated and integrated AI, and behavioral economics is an enthusiastic entrepreneur. She has worked with several non-profit agencies and social networks, including Engineers Without Borders and believes in fostering social good. Big data is all in a day’s work for a physicist, according to this technology enthusiast who believes in the unique marriage of skills and every corporation’s need to understand their data. She speaks on an array of topics in an interview. Excerpts:
Conception of Theory+Practice
Noting that influx of data has led to ignorance among industries as to how to use those data, Rogayeh says that most of the solutions for these industries start with data-first strategy coupled with digital transformation projects. “There is a real opportunity to actually unlock much more value by starting with use cases, asking questions, and understanding the problems we are trying to solve. Therefore, the approach we take at Theory+Practice is sought after by Fortune 500 companies- an approach that is result-oriented. “Theory+Practice was born from the desire to build a team that could approach data science differently. I knew that intellectual diversity, in addition to cultural and gender diversity – is not only a key differentiating factor in tackling complex problems but is also an absolute necessity.”
Integration of AI
To Integrate and automate AI is the same concept as being able to scale AI, according to this tech enthusiast. “So, one piece is discovering AI and really thinking about bringing these capabilities in-house. The other piece is about building prototypes, and then if you want to deploy AI, there is a whole bunch of automation and integration required.” She recommends that while integrating and automating, you need to have the KPIs, and strategic direction in mind to truly unleash the value and potential of AI.” So, when deploying AI, Rogayeh asks companies to pay close attention to the actual prediction and how the Machine Learning algorithm is being used. The automation component, the UX component, the customer experience component, all of that is critical. Our work determined a multi-million-dollar opportunity for our client, she adds.
AI has been transforming enterprises like never before. McKinsey cites that AI offers enterprises potential economic value of $9 trillion to $15 trillion. Customer-centric industries, like retail and finance, are inherently suited to adopt AI solutions fast and in meaningful ways. For example, they are highly competitive and prone to disruption, allowing new players and innovative thinking into the landscapes. Observes Rogayeh that most importantly, they create a lot of data, generated in real-time. Years of historical data is the fuel needed for AI. “AI can help enterprises unlock a deeper understanding of their data (and customers) by mapping out a whole ecosystem of use cases instead of treating each problem as individual use cases.” AI use cases are related to one another and investment in one use case can benefit business for multiple other use cases. “We’ve also found that solutions in the retail scale, the lessons and methods developed can be applied to more than one retailer, and the fundamental solutions for retail can be applied to other industries.”
One risk involved is the ability to scale AI effectively. “When discussing scaling AI, it’s essential to acknowledge the common roadblocks and how to avoid them. Roadblocks may include a lack of clarity on the ROI and feasibility of use cases, foundational issues with data capabilities, governance and risk management, employee adoption, and bias.” Rogayeh recommends developing an ecosystem of use cases, ensuring the data is up to date, in scope, standardized, verified, and accessible and to start small and safe.
“It all starts with people. Believing in people and investing in them is crucial. Striving for humility is very important to me, as is working hard and dreaming big. When it comes to leadership, I have incredible convection in my heart that what we do is extremely important.”
The Success Mantras
Rogayeh urges young entrepreneurs to invest in people, in your own team, and with partners and clients and to experiment. “We are built internally on a culture of experimentation, and this extends to our clients as well – we push them towards experimentation. And this is one of the ways we bridge the gap between theory and practice.” She also urges to carefully consider one’s approach to the adoption of AI. “If you don’t think about some of the roadblocks for the people on the ground to implement, use, and create value, you are going to struggle to maximize the value created.” When working in AI, intellectual diversity in the team really matters. You maximize value and unlock potential when you add behavioral economics, sociology, and psychology skills to your team, she signs off.