AI To Impact

PODCAST: AI for the Digital Enterprise

Episode 2: New Age Capabilities for Digital Transformation

Listening time: 13 minutes

New Age Capabilities for Digital Transformation

In the latest episode of this series, host Aruna Babu talks to Ashish Sharma – COO, and Co-founder of BRIDGEi2i on “New Age Capabilities for Digital Transformation.’’ Listen to him speak on how Reimagining business needs a strategic view and a different set of capabilities for transformation and how these things tie back ultimately to a culture of diverse teams working together.

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Aruna: Hi! You’re 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 really means and how do you make AI real for an organization. Today, I’m going to be chatting with one of the best analytics minds in India – Ashish Sharma, the COO and a Co-founder of BRIDGEi2i Analytics, one of the fastest-growing AI and data science firms in the country. Ashish has about two decades of rich experience in strategy, consulting, and analytics in the financial services, insurance, and high-tech industries. Hi Ashish, thank you so much for making time.

Ashish: Pleasure. Nice talking to you.

Aruna: Today, enterprises are really having to work hard on gearing up for their AI journey especially in light of the intense focus on digital transformation. Obviously, a lot of things are new and evolving. But can you give us an overview on what an enterprise has to do if they really want to accelerate on this path of the AI driven digital transformation?

Ashish: So, I think one of the big, interesting shifts we’ve seen over the last couple of years is that organizations are starting to become fairly real and AI has immense possibilities. This is not about just transformation. The way we’ve been sort of using this and doing this over the last decade or so. This is not just about digital. This is not just about automation. It’s not RPA. It’s really about thinking hard and saying, can we reimagine? Is there a different way of running our business, engaging with our customers? And can we come together to use AI technology to make that happen. Now, that’s very interesting, because that’s bringing up a lot of nice conversations in boardrooms and in a manner that’s fairly serious and fairly real.

But as you do that, I do think and I do see and that’s largely because of the infancy of where everybody is…and while we’re now more convinced, we only have so many examples of successful transformations. We’ve all seen this in the consumer world. We’ve all started interacting with Alexas of the world. We understand chatbots. We’re starting to hear and see cars being driven autonomously. So, it’s not a fictional movie anymore. It’s real. And we start imagining: Wouldn’t my sales process be far more efficient?

So I think possibilities are there, but it needs a very different set of capabilities. It needs a strategic view. Those are two two key things that I think need to come together for enterprises to see success and be able to reimagine the world in a very different manner.

Aruna: OK, so two different aspects, new age capabilities and strategic view. Can you talk to us a bit more about these?

Ashish: If you think about new age capabilities as we said, this is not about redesigning or automation. This is about thinking decisions, thinking what humans do today. Every single instance – as far as decisions are concerned and thinking about, hey, can we bring an intelligence to our processes so we can focus on the next level of challenges?

So as we do that – there are two things around capabilities that I want to talk about. You’re trying to bring together different kinds of capabilities in the group. When I say a different kind, you’re looking at user experience, decision maker experience. You’re looking at data, a variety of types, be it documents, images, voice, sensor generated data, clickstream data, all of that needs to be processed and harnessed. And all of this is getting generated at different points. So it needs a lot of deep data engineering skills. Then you look at algorithmic skills and say Machine learning, artificial intelligence, optimization, whichever aspect you want to leverage, solutions will require different kinds of these skills in a fairly deep form, and then you need technology because we will make this real. We want to make this something at scale, and something that drives the way business happens going forward.

And then all of this is about users. So you need a good way to understand user experience, but also the ability to drive change. But you’ve to think about blueprints that are actually implementable and adoptable. Now all of this needs to come together in the group that organizations are trying to create around new-age transformation. Second, none of what we talk about here is done and dusted. There is no team or individuals who have done this ten times over. So you’re almost building this grounds up. And, what makes it far more challenging is the possibilities are evolving at a much faster clip, which means a lot of what we thought today was a challenge will not be a challenge in a few months from now because there will be some innovation, there will be technology advances, there will be newer possibilities that come in around how we can solve some of those. So unique themes that are constantly looking at what’s happening, what’s evolving, and how can I make this / how can I leverage this in the context of the solution that we’re building?

So coming back to a question on capabilities, you need two things you need the ability to bring together: Teams with diverse expertise and work effectively.

You need a culture and an environment. And that’s what really what we’ve built with our SCaLA program at BRIDGEi2i – a culture of saying we need to be constantly learning. We need to learn from each other. And it’s not just about me becoming very good. It’s me being able to bring together my expertise for the group. And as we run innovation orbits, we run scalathons where we can sort of harness the best of what each of us bring together as experts and build real solutions.

The second to the point that you sort of asked: Proof of concept, and I think the whole thinking around can we just experiment in many areas and see what works. I think that’s the second big shift. I think we need a lot more conviction, a lot more deep investments to make some of these programs real and effective.

Aruna: Okay. So that sounds really complex, to be honest, especially what you said about staying at the edge of the learning curve and combined with the lack of the scale thinking, which is what you’re talking about with regard to POCs. How do you think enterprises can actually orchestrate this?

Ashish: Yes, so I think for enterprises Aruna, the first thing it starts with is: Are we still skeptical, or are we convinced. And as we engage more and more, CXOs from the vantage point that we have in our interactions, we think more of them being convinced. We see boardroom conversations being far more real in terms of saying, hey, there is an immense possibility in this: Be it AI or Technology and how it comes together. So I think they are more convinced. The question is, if we are convinced, we then need almost lend this the kind of muscle that we would lend to (if imagine we were to do) a new product introduction. If you were to do a new product introduction, you would go to the street and say, you know what, we’re looking at going to the space and we are going to make investments. And this is going to be another few basis points on our margins or a few basis points on our revenue growth. And that’s really where the excitement is. I think we need that conviction coming in for these programs, which means we need to bring together three things: We need to bring together a strategic direction of what are the bets we want to take. We cannot do this in thirty different areas.

We need to evaluate thirty different areas, put them through lenses of what will be successful now, and what needs to wait for us to become more evolved and more effective for us to pick some of those? So I think we need first to build a strategic roadmap, pick two or three big areas that we think are real. This transformation will benefit the enterprise, be it around guided selling, or the way we run our customer interactions or customer service to deliver a very different customer experience. But I think we need to pick those bets? Number 1 – Once we pick them, we need to realize that this won’t happen by just giving this to a team. We need to bring together a couple of teams. Going back to our point, we were talking about capabilities, and today in enterprises there are different teams that represent some of those capabilities, we need to bring them together almost like a new product introduction team would. Wherein you involve marketing and involve product development and legal teams.

You need to bring together your technology teams, data science teams, functional teams and say here is the next 2-year journey and we want you to work together in making this happen. Once you’ve done that, the third big area is governance and governance from a CXO perspective. We need CXOs having a hawk-eye of where this program is going. Provide their strategic direction. Take some of that excitement back to everybody in the company so they start getting real about what’s happening here and how it’ll be transformational for the company and, more importantly, provide cover for the team as it fades. And there will be failures and enough challenges where will almost feel like this is not something that could become real, and that’s where governance comes in when we start dealing with those challenges. Being comfortable with our failures and saying how we will change our game plan to be able to deal with some of that stuff?

So those are three big things that I think are critical for enterprises, and that’s really for the CXOs to be able to come together and provide that perspective.

Aruna: Ashish, it sounds like a lot of components to get right. What do you think successful programs look like or what have you seen in successful programs locally?

Ashish: Yeah, while it’s it certainly sounds challenging and tough ask. The way I look at things, I also feel very optimistic. I think a lot of such problems that we are driving are very energizing. And to me, it’s just the fear of something that we’ve not done enough in the enterprise, and it’s a matter of getting started.

Given the way technology is progressing, there is enough opportunity for these programs to be more successful than failures. But I think one thing that I’ve seen among successful programs is that you don’t have to depend on doing all of this on your own. I think enterprises can make choices to bring partners on board. Certainly those partners need to be more realistic and they should not just bring in capabilities because I think the kind of play and what enterprise we are building here needs partners who are far more broader in terms of different perspectives that they bring in. More importantly, the ability to understand the whole and a culture of being able to work together with your teams to make some of this effective. But I’m far more optimistic, and I really get energized when I see some of these programs in action.

Aruna: All right. Thank you so much, Ashish, it was really interesting. I especially loved your analogy about the rigor that AI programs demand when you come back to new product lines, a fantastic example. Thank you so much for your time.

Thank you so much for listening to this episode of the AI to Impact podcast. It was such a good discussion with Ashish, the COO of Bridgei2i Analytics. There are a lot of valuable insights about how to run a successful AI program starting with strategic direction, new and constantly evolving capabilities, and the need for cross-functional teams with diverse capabilities to collaborate with the right governance. If you found this interesting, please share it forward, especially as we continue the way for the Digital Enterprise conversation with other experts and thought leaders. In fact, in our next episode, I’ll be chatting with an industry leader who’s driven Digital Transformation at several Fortune 500 companies about the importance of AI assets in making consulting-led engagements impactful. So, if that sounds like something you’d like to know more about, do subscribe. Thank you once again 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

Ashish Sharma

Ashish Sharma is the COO and co-founder of BRIDGEi2i and leads service delivery operations and finance. An alma mater of the Indian Statistical Institute (ISI), he brings in over 17 years of strategy and analytics experience supporting financial services, insurance, hi-tech clients in the area of marketing, pricing and risk management. Earlier, he has worked at senior roles at Genpact’s Consumer Analytics and M&A teams. Earlier, he established risk and pricing analytics center of excellence for GE Capital. In his role as Master Black Belt (MBB), he identified ways to leverage Six Sigma concepts in analytics, leading projects to make analytics service delivery robust and driving innovation.