Alright. Good morning, everyone. My name is Deepika Chopra, and, good afternoon, good evening from wherever you are joining.I'm joining here from New York City, founder and CEO of Alpha UAI. And, today, for next twenty minutes, I will be talking about why majority of the AI transformation fails, what leaders are doing differently, to make it a success. And, the title of the talk is beyond adoption because I believe that adoption was a wrong metric to start with, for measuring AI measurements. And, end of the day, I will also give you tools that you could use to build human centered AI cultures that can actually scale. So excited to be here and, look forward to how the conversation goes, and feel free to ping me if there is anything, any questions that you have.

So, where we are today, every leader of the organization are talking about shifting their company towards a AI native organization. And I love this quote from Satya Nadella. He says, companies will have to do the hard work of culturally changing how they adopt technology. Now everyone agrees, and I think every leader in the room today agrees that, this is true. But when it comes to operationalizing something on at a cultural level, it's hard. And let's do a ten second audit. If you are a leader running AI transformation, I'm sure you would resonate this, but let's answer these three questions. The first one is, in your AI use cases that you are running within the organization, can your top team name the business outcomes from your flagship AI use cases that are that you feel or you're proud of?

Do you know what's your override rate? What is the percentage of people that are overriding the AI recommendation that has been provided? When the AI disagrees with your best operator, who takes the win? So if you are if you are hesitating in any of these three or questions, I think you are in the right room because we will together delve into each of these areas, understanding, you know, what the data is saying, what the report is saying, what the patterns that we are seeing today.

Can we look at it from a different perspective of, measuring it from a more quantified scale rather than, you know, the soft skills like adoption, trainings, and others? And I would love to hear, you know, what your organization is currently doing in the same space, and, you know, happy to take that forward. So let's look at some of the reports, and the numbers that are being, you know, not put on the board deck. But, take a look at, you know, the reports that were released from MIT, from, you know, some of the leading McKinseys. And I just picked a few which was from the latest reports. It says 10 to 12% of the companies report seeing our, they are not able they are seeing that there are measurable AI benefits.

So that means about 87% of the organizations are still not getting the benefits, that they are expecting from from the from the from the AI transformation that's currently going on. About 56% of the reports are getting nothing from the AI investments that are being made, And, about 42% of the enterprises have stopped, majority of the AI projects in 2025. And prior to that year, it was about 17%. So if you look at this data, you know, and we look at AI, the AI is evolving at a lightning speed. The technology is getting more and more advanced. And still, if the numbers are not correlating, there is something that's missing. There is something that is missing from the from the perspective of, you know, reaping the benefits that we are gaining.

And if I were to reframe this whole number in the deltas that we are seeing, the organizations that are running AI as a repetitive measured investment are getting the best benefit of the 55% of the ROI that they are getting versus, you know, about 5.9% of the organization, which are still taking it as an ad hoc way of, you know, running the transformation.

So it gives you a sense of, you know, at least a very high level of, you know, the data, the report, and, you know, the hesitation that's coming up from, you you know, the transformation programs that we are running. So why am I telling you all this? A little background about me. I, have run I've spent about more than fifteen years within the financial industry, running large scale digital transformation programs, across some of the most complex and regulated organizations, scaling the program across 26 countries. I've seen what how organizations approach change and what works and what does not work from the technology perspective, from the people perspective, from the, you know, the product perspective. Right now, I am, running Alpha UI. It's a AI native decision infrastructure, primarily focused within the investment vertical. And we are helping investors and boats to make, faster decision with more clarity and have explainable AI results that they can take forward.

I'm also an author of a book. It's move first, align fast, that has the frameworks and the scorecards. It's basically the leadership playbook behind the the tools that we will be talking about. It was published last year around Wiley and, was a foundation of the work that has been done in past, fifteen years and, you know, something that we are implementing as part of, the decision governance and how you can as AI grows over and over, how you can make sure there is governance in place, there is, you know, a more structured, way of execution that we can take it forward.

So we talked about, we talked about strategy. We talked about execution. We understood, there is a this difference between, you know, what AI can deliver and where your organization is ready to act on. So I named that gap as the alignment gap. Right? And that becomes one of the key predictor for you when you are running a transformation, when you see the pilots are not scaling to production, why there are you know, why it is not giving you the the outcome. I think it is most important piece to understand, whether, you know, there is really where you stand today. And, I'm a big believer of, you know, what gets measured gets managed.

So, if you want to and there are two, big patterns that I can and they are that you could use when you are assessing whether you are in into the phase of, you know, hey. Are we in the same trap of not moving from pilot? So the first one I coined it as the execution theater. That's the first risk that you would see, and the dashboards are green when you are reporting the matrix in terms of the adoption, in terms of the training, in terms of the skills. Everything looks perfect on paper, but, when when it is you know, when the project goes to production, here, there is still the gap in terms of the expected ROI that we were we were looking at. So, very important, most of the organizations that I have worked and seen this theater, was a big prominent, pattern that I could I could relate to and, you know, something that you also see in terms of, the reports that are coming out from, you know, majority of the organizations in terms of, you know, the the percentage of, benefits that they are getting from, from their programs.

The other pattern that I would call out is the misalignment spiral, and that is the compounding effect from the execution theater. When you run the transformation multiple times within the organization, there is a unaddressed compounding effect of, you know, the trust, the clarity, and, you know, whether, and and from the people side of it and something that, you know, the workforce needs to be to be, considered about.

So, I call it very dangerous because, you know, when you start seeing patterns around the organization in terms of, hey. Your people don't trust the the the, the initiative that is currently going on, majority of the time, adoption or, you know, people take believing into the system would fail. So very important. I just wanted to make sure I bring these two patterns in into the into the light because we all know we where we want to go. It is very important for us to even understand where we stand today. And, also, it is most important, when you are running a transformation, how quickly you can use these tools as a a signals that can help you easily pivot into the direction that you want to go. So I feel that, you know, these were the most important, piece when you are running into the transformation to assess, you know, hey.

Are you into the trap of, you know, into the 87% of the organizations that are failing? Or it is, you know, moving in the in in a more, structured way which can eventually turn into something which is more beneficial for the organization. Right. So how do we close this gap? So I call this there are three integrated tools that I provide, and, I call this as a complete leadership alignment system that works, together. And, you know, the first one is called act. It's the methodology that needs to be adopted by the leaders within the organization. And what I mean by act is align, cultivate, and transform, and it all works in a sequential.

Aligning is the most important piece wherein you tell or the leaders tell why we are doing what we are doing today, aligning the mindset, aligning the vision, the mission at at all levels within the organization. Once they understand why we are bringing in a technology, once why what value it is going to bring in within the processes, it's easier to move faster. That's a very first and most important step that we get in. Cultivate. Cultivate the skills, the literacy. Majority of the times, it's not the hesitation of not using the AI, but it is more around, not knowing. And people majority of the time, it is, the hesitation is from not understanding, the right skills in place, how you can cultivate what your workforce bottoms up in terms of, you know, using the technology. Do they understand the data that they are seeing? Why do they even go back to the old system?

Is the reason behind that is because, you know, the right skills needs to be brought in. And at the same time, you need to under understand that, you know, they are comfortable using the tools. And finally, transform the workforce. Transform the workflows. So embedding it into the DNA of the organization. So it becomes a repeatable methodology that every leader within the organization needs to inherit to be to be even even able to start talking about, you know, the AI transformation. So I feel this is the most important foundation that any leader at any level within the organization needs to be to to layout, as as part of, you know, running, the transformation work across, and that does not become one person's responsibility. I'm sure at every level, at the board level, at the c suite level, at any level that you would see, this becomes one of the most important, area, that matters, before any rollout that needs to happen.

So, the next one that so the next one is act plus m, and I use that as a diagnostic tool. This is a the act plus m is align, cultivate, and transform methodology, but have a measurement, a maturity level tied to it. And I scale it from, a scale of zero to so one to five. One being ad hoc wherein we are just introducing AI as an IT project. I'm sure majority of the organization are over with it. And five being the most optimized wherein, you know, you're functioning as a fully AI native organization. But the steps from one to five is where your methodology comes into the picture. And as I said, what gets measured gets managed. If you know out of a scale of one to five where you stand today, you have a more practical way and steps listed out, to be able to get to where you want.

And, if you look at, you know, from the from a leader's perspective, this diagnostic tool becomes an assessment for you, a regular pulse check-in terms of, how ready your leadership is in terms of, you know, running the transformation. And funny part is when I did this diagnostic with majority of the organizations, I realized, you know, majority of the, organizations feels and if the that they are at scale at a scale of four. But when we that's the self evaluated to, report. But when we ran the diagnostic tool, they were actually operating at two. So it was, I an eye opener and, you know, and it once you assess that, you know, this is where we stand, it it becomes more practical and it becomes more clear in terms of where you are heading. So I do encourage, you know, first, get adopt the methodology, and it could be any methodology. It doesn't need to be this this one, but it it it aligning, cultivating, and transforming your organization, your teams in terms of, you know, awareness, in terms of upscaling, in terms of making it a recurring pattern, and then using a diagnostic tool that that's able to measure, you know, where do you stand today and where you wanna go, in next three years or four years so everybody is marching towards the same North Star.

And, finally, the most important for, is the task, which is called human AI alignment score. And what I mean by that is, that becomes your, predictor, just like a net promoter score that measures the loyalty of the organize, of the customers to the organization. Pass becomes one of the, measurement of how, you know, how how your, people are trusting into the the vision that you have put in. So this becomes a shared metric across the organizations for the boards, for the, you know, c suites, for the for the leaders that are running the, transformation program, or the product managers. Everybody has one score to look into, and that tells you whether you are going to be successful or not. This measures whether your people are able to trust the AI enough to act on it or, you know, or are they still going back to the old system?

So very important in terms of looking at end to end. I call this, you know, a, three instruments, but it's it's one operating discipline. And this is, we've tried it for a fewer organizations, and it's, it's giving the results. It's giving the clarity. It's it it seems very positive in terms of, you know, getting to to to where you want to be in terms of the ROI and have a language that can be used across the organization and, most important, bringing people along with you in the journey. We have their technology in place. We have everything, every right tool that can be used. But if your people are not onboarded, chances are, it's not gonna fly. So let me take a look at so if if I were to give you a, in practice, how this would work, as I said, the first and most important thing is to run the diagnostic tool. When we ran the tool, majority of the time when you it's a self reported readiness, the score was four.

But, when we use the act plus m framework, the delta tells the story. The delta tells you exactly what's failing. Within, we have the, seven dimensions that you could look at from the maturity matrix, and that will help you, you know, identify the friction points on why there is a hesitation from from the people's perspective. There was no change in the technology. There was no change in the there are new new vendors brought in. It was purely, purely the human system that was changed around. The result, about 38% reduction in the override rate, and that's huge. When you see that people are trusting the system that is being built, the the adoption automatically increases. So this becomes one of the key metric and also a a a an area that you could say as, ROI multiplier because now you will see the adoption increases, the multiplier because now you will see the adoption increases, the outcome increases, and that ties to the analyzed value of, say, right now that the project that I worked was it was around 46,000,000, But, that tells you, you know, that the same model, it's the same data, but it's the workforce that's finally trusting the the, program enough to act on it.

So I hope that this this gives you a little bit big picture of how that can be applied in terms of, running a transformation, and it doesn't have to be any of the financial industries. I I feel this can be applied into any of the organization because, it has, the right tools in place. It has the right metrics in there, and, you know, it gives you a lens of early warning indicators in terms of, you know, how you can pivot if there is a, a friction in in the workloads. So in, last twenty minutes, if, there was anything that I could get if you've the three things that you could take away from from today. First, stop measuring the adoption. Start measuring the work. If your workflow and the PNL didn't move, I think there is no progress that's making. So first and most important piece is try to look at, you know, the diagnostics, try to look at the workflows, inherit that methodology, and try and, you know, give that perspective within your team.

Score your readiness honestly. There are self reported readiness, and there is a tool that can be used across as a standard way. So I believe that would be, you know, help that will help your team, you know, in terms of getting that clarity and getting that readiness in terms of where you want to function. And, most important, track the override rate, on a weekly basis. That becomes your signal. So if you are seeing you know, majority of the time, if you're seeing that there is a reduction in terms of, adoption of technology, that that tells me something is, you know, needs to be fixed. Maybe it could be the weekly meetings that you bring in in terms of assessments. Make that part of a discipline is is what I would recommend. Finally, whenever I've been asked a question around, you know, what leaders needs to do differently, I and I always say this.

The leaders who win the AI decade are not the ones with the best models. They are the ones whose people trust the model enough to act on it. So ensure that your people are, you know, along with you in this journey. That's the only way you can you can drive and engineer for value and not just, for the adoption.