AI To Impact

PODCAST: AI for the Digital Enterprise

Episode 3: AI at the Heart of Digital Transformation

Listening time: 10 minutes

AI at the Heart of Digital Transformation

In the 3rd episode of this series, host Aruna Babu talks to Anand Sri Ganesh – VP, Digital Practice, BRIDGEi2i on “AI at the Heart of Digital Transformation”. Tune in to hear his outlook on how new-age consulting has enabled corporates to look through the lens of AI and allow them to reimagine their Customer Experience, Operational Effectiveness, Product/Service design, and delivery. Ganesh also feels the transformation also calls for certain behavioral/systemic changes that might cause slower adoption among clients. Don’t forget to subscribe to our podcast!

Aruna: Hi there. You listening to AI to Impact by BRIDGEi2i, a podcast on AI for the digital enterprise. My name is Aruna Babu, and I’m a transformation consultant who spent a good part of the last decade crafting strategy that marries business, technology, and user needs. In this series, I’m going to be sitting down with business leaders and AI and analytics experts who’ll share their views on what AI for the digital enterprise means and how do you make AI real for an organization.

Today, I’m going to be chatting with a thought leader who’s passionate about the intersections of marketing, analytics, and technology – Anand Ganesh. He has over two decades of experience in leadership positions across technology and consumer markets. He leads the consulting team and is responsible for several strategic growth initiatives at BRIDGEi2i Analytics, one of the fastest-growing AI and data science firms in India.

Aruna: Hi Ganesh, thank you so much for making the time.

Ganesh: Always a pleasure.

Aruna: So, industries seem almost obsessively focused on digital transformation. We keep hearing this word digital more often today than ever. What do you think digital really means today?

Ganesh: Digital. I see digital as a triangulation of three phenomena that has evolved in a fairly accelerated manner over the past three years: Digital processes, digital technologies, and digital data. Let me unpack these three for you.

Increasingly, corporates, networks are engaging with one another through a network of digitized processes. This itself is sitting on a large scale, secure digital infrastructure that is allowing for seamless interaction across the network. This interaction is generating, of course, a ton of digital data that flows between these nodes and networks and allows seamless visibility across players between these networks. This paradigm of digital processes, digital technology, and digital data is driving the digital transformation that we are seeing within corporates and large global enterprises. And you know what, AI is at the heart of this transformation. AI is leading the charge, bringing these three paradigms together in ways that we wouldn’t have imagined even a couple of years ago.

Aruna: Since you said that, how do you think CXOs are really viewing the role of AI in digital transformation? Are there more skeptics than believers today?

Ganesh: So, when I speak with CXOs, there’s an increased awareness that consumerization of technology is pervading enterprises and enterprise interactions. We, as consumers, engage with AI, ML, scale digital technologies every day. The same experience is being expected when corporates and enterprises interact with one another and when they provide products and services to their consumers. So when I engage with CXOs, that is this huge sense of excitement, enthusiasm and if I may, a sort of restless energy that all of this AI-enabled digital capability needs to come to the party in their functions, through their leadership, in the domains that they manage, the functional and organization-wide priorities that they own and drive. And this scaled execution of AI-enabled capability is something that CXOs are expecting today.

Aruna: You mentioned scale. What kind of infrastructure do enterprises need to actually scale?

Ganesh: That’s an interesting one. So, when we look at AI-enabled digital transformation. At the core of these AI systems are a set of AI assets. Let me deconstruct this a little differently. When corporates design AI systems, they’re fundamentally looking at the problem: consumption inwards. Which is, how do consumers, operators, managers engage with these AI systems? How do these AI systems allow two machines to interact with one another in real-time in a secure manner, or seamlessly? This consumption layer is sitting on a framework of AI accelerators. Think of these AI accelerators as a combination of Large scale pattern ern detection, an abstraction of anomalies, and root causes. The ability to extract prescriptive next best action. The ability to execute large scale optimization or a combination of these two or three accelerators. What makes these accelerators successful is the foundation of data that they breathe out of. These data streams could be structured, unstructured, rich, increasingly dark data from which we’re able to extract all features, interestingly, that allow these AI systems to scale across the organization as systems to be able to meet multiple functional and architectural demands that the enterprise systems place on them. Now for these systems to scale, they required two dimensions to come together. One is the AI systems in and of themselves need to have a roadmap of sophistication. Sophistication on their algorithmic capability, of course. And secondly, the sophistication of increasingly being able to take on more and more data types, more and more data sources, more and more data streams as the organization and the interaction patterns evolve. The second dimension is a translation to context, which is these AI systems need to be relevant for the context within which they’re going to be used and deployed. Now context comes from a marriage of industry relevance, functional specificity, and relevance to the market dynamics within which those systems are designed. And being able to piece together these solution frameworks is the responsibility of my consulting team.

Aruna: OK. So in the context of these AI accelerators and AI-enabled assets, how does consulting look different?

Ganesh: The consulting industry itself, at least in my opinion, is going through some fundamental changes. We always used to look at consulting from an objective of incremental improvement. Improvement of customer service, improvement in customer retention, or being able to take advantage of specific policy changes or unique market opportunities or changes of that kind. What AI-enabled technologies are doing is a step-change intervention in both product and service design and product and service delivery, which is through the lens of AI, I can completely reimagine the way customer experience is delivered. I can redesign operational systems for operational effectiveness and systemic interventions, and we talked of completely new design of products and services.

The consulting capability is allowing organizations to take advantage of a very continuous, evolving, ever-changing intervention, which is driven by AI and digital technologies in a methodical, frictionless, and impactful manner. So, the role of consulting is increasingly becoming the ability to work with, co-create, capabilities with client systems and organizations in an evolving manner that is predictable and more methodical and planned. That’s the role of consulting as I see it and as it evolves. An interesting dimension in all of this, of course, is behavioral change. What AI systems are doing are they are demanding certain transactional interaction patterns and changes. Within the consumers and managers that engage within these AI systems, they’re also demanding changes in ways in which two machines engage with each other and interact with one another. Of course, there is a legacy of behavior that we inherit within which corporates have grown and fragmented. Now this difference between legacy behavior and systemic change that our AI systems are demanding is creating an interesting attention. And in the clients and some corporates that I engage with, the difference between the ability to quickly embrace this change and welcome the shift that has been within the corporates or, if I may, the road map evolution within how this change management and adoption journey take shape within different constituencies, within different stakeholders, determines how quickly the transformation journey is impactful within client organizations.

Aruna: That was interesting, the bit about behavioral change was a very interesting observation, and I think with that it’s a wrap. Thank you so much Ganesh for taking the time.

Ganesh: My pleasure again.

Aruna: Thank you so much for listening to this episode of the AI to Impact podcast. That was such an interesting conversation with Anand Ganesh, Consulting Practice Head at BRIDGEi2i Analytics. There were a lot of valuable observations he had about what digital means, the evolution of any AI-enabled asset infrastructure. And of course, how consultants will need to be agents of behavioral change for successful AI programs. If you found this interesting, please share it forward, especially as we continue the AI for the digital enterprise conversation with other experts and thought leaders. In our next episode I’ll be chatting with the CTO, who’s been a flag bearer for innovation throughout his career about the changing innovation landscape for AI-driven programs. So do subscribe, if that sounds like something you’d like to know about. Once again, thank you so much for tuning in. I’ll catch you next time. Bye.

The upswing in AI adoption and the impact of Digital initiatives in enterprise transformation have reached staggering heights, but there is still a lot of skepticism around the value realization of AI. BRIDGEi2i, a transformation partner to several large enterprises, has been spearheading an enterprise-wide movement on “Making AI Real.” In this series, we bring together reputed thought leaders, practitioners, and influencers of the industry as they discuss trends, predictions, and best practices on extracting tangible value from AI to embark on transformational journeys.

Meet the Speaker

Anand Sri Ganesh

Anand Sri Ganesh, Chief Digital Officer, BRIDGEi2i, is an alumnus of IIT Madras and IIM Ahmedabad, has over 20 years of experience in leadership positions across technology and consumer markets, working with organizations like Manthan, HP, and PepsiCo. He is passionate about the intersections of marketing, analytics, and technology. At BRIDGEi2i, he leads BRIDGEi2i’s AI-enabled product portfolio – conceptualizing and building out the product roadmap and taking the products to market; apart from owning some of the strategic growth initiatives for the company.