AI led Algorithms can decide on how we need to emote, behave, react, transact or interact with an individual – Sameer with SCIKEY
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In an exclusive interaction with SCIKEY, Sameer Dhanrajani, CEO at AIQRATE Advisory & Consulting, speaks about how the future of work will look like enabled by AI, and it’s contribution in building productive teams and the emerging AI trends to watch out for in Post COVID scenario.
“AI led algorithms can decide on how we need to emote, behave, react, transact or interact with an individual,” Sameer Dhanranjani
Sameer is a globally recognized AI advisor, business builder, evangelist and thought leader known for his deep knowledge, strategic consulting approaches in AI space. Sameer has consulted with several Fortune 500 global enterprises, Indian corporations , GCCs, startups , SMBs, VC/PE firms, Academic Institutions in driving AI led strategic transformation and innovation strategies. Sameer is a renowned author, columnist, blogger and four times Tedx speaker. He is an author of bestselling book – AI and Analytics: accelerating business decisions.
In an exclusive interaction with SCIKEY, Sameer Dhanranjani, CEO at AIQRATE advisory consulting, speaks about how the future of work will look like enabled by AI, and it’s contribution in building productive teams and the emerging AI trends to watch out for in Post COVID scenario.
Mr Dhanranjani, you have consulted with several Fortune 500 enterprises, GCCs also start-ups in driving AI-led strategic transformation strategies. What according to you, are the topmost strategic considerations to weigh for managing accelerating business in Post COVID world for a start-up?
The unprecedented times of COVID-19 have brought the aspect of decision making under consideration. This includes tactical, strategic, and operational decision making that is crucial to make the venture more sustainable. Today the use of artificial intelligence is quite high amongst organizations. It can be used by start-up ventures and other outfits to make decisions irrespective of the area that needs decision making.
Most decisions that need to be made strategically are being passed on to artificial intelligence-enabled interventions. The algorithm makes similar decisions based on the previous decisions taken. Algorithms can decide how we need to emote, behave, react, transact or interact with the opposite individual This advancement in AI brings the challenge for organizations to create products and services specific to each customer through hyper-personalization and micro-segmenting. However, it can also be considered as an opportunity for organizations to emerge from the pandemic with newer business models and experiences for customers. Start-ups, especially, can make use of such advancements to reinvent and rejuvenate the organizational ecosystem.
You are known for your passion for Artificial Intelligence and are an author to the bestselling book – AI and Analytics: Accelerating Business Decisions. Tell us where how can AI be strategically significant while building productive teams.
My experience has led me to deal with engagements in the entire value chain of HR, ranging from hiring to engagement to incentivization that has leveraged using AI. It is phenomenal to see how AI can help build, engage, and sustain productive teams. AI can help in hiring through the detection emotions, facial expressions, tone modulations of the interviewee through computer vision and image classification techniques.
In the creation of productive teams, AI can gauge the engagement levels of an employee. It tries to look at the various interventions made by an employee regarding their attendance, participation in virtual meetings, and propensity to ask and engage themselves in conversations. It also keeps in check the number of pauses, intervals, and breaks taken by an employee. Every aspect of the employee is being marked to see how productive, inclusive, as an individual and in teams.
What are the top 5 AI trends to watch out for in Post COVID the scenario of the next one year?
When it comes to AI, the first trend emerging is that AI is not a tool or a technology, but it is now being touted as a strategic imperative for any organization. This means that AI strategies will become an intrinsic part and feature of every organisation.
The second trend is the democratization of AI. There is a possibility of the emergence of an AI marketplace where virtual exchanges related to business problems, demo runs etc. can be conducted. One would actually be able to figure out which algorithm is best for them in customer experience, supply chain etc.
The third trend being the cloud will act as a catalyst for AI proliferation. The propensity for cloud providers to enable AI companies with possible aspects of microservice API’s, Product Solutions will be created on the go. This means that the cloud enablers will have options to see various possibilities specific to their organisation when it comes to AI-specific use cases.
The fourth trend is linked to skilling. AI today is a part of a lot of course curriculums. But what is missing is the whole aspect of how does it get applied? The new courseware will be focused on how is AI implemented, adopted in the organization.
The last fifth trend is decision-making enabled by AI, which means humans will have no option but to upskill and reskill themselves to take a more rational, pragmatic and sanguine approach. So new models, new emerging realities of decision making will emerge.
How is AI powering the Future of Work, what are critical considerations for business and tech leaders considering the rapidly changing business dynamics due to COVID?
The future of work will be about AI and what we call AI plus a set of exponential technologies. This means that every aspect of our performance interaction and our responses will be gauged very manually through these technologies. This indicates that the level of performances in terms of how we go up-to-date needs to be worked upon. The future of work is an ecosystem where one particular employer cannot do it all.
This means that if learning must occur through an external player, it must come through the ecosystem of co-employees and the employer. In the future, we will not be caged as mere professionals doing our job but will be encouraged to push our boundaries to explore more at work. At the same time, transformation, innovation, and disruption will be a part of the future’s performance metrics. They will become a major parameter for the organization to create a mediocre versus proficient employee or a professional. This is where the onus will fall on the employees to ensure that they are not just doing what is being called out, but are going beyond to create what we call a value creation for the organisation.
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Algorithms will not only drive scores of business processes, but also build other self-intuitive algorithms, much as robots can build other robots. And rather than using apps, future users’ lives will revolve personalized algorithms to drive individual choices and behaviors .
Enterprises will license, trade, sell and even give away non-lynch pin algorithms and single-function software snippets that provide new opportunities for innovation by other enterprises. Enterprises will also partner with cloud-based, automated suppliers with the industry expertise to advice on ways to avoid future risk and adapt to technology trends.
Imaginative thinking ! but it’s no surprise that future value will come from increased density of interactions, relationships and sharing between people, businesses and things ̶ or what I call “ Algorithm Economy “ .The greater the maturity of algorithms , the greater potential value you can reap. We’ve seen interconnection coming of age for a while now and have invested heavily in a platform to empower enterprises with fast, direct and secure interconnections with business partners and network and cloud service providers.
Redefining Business Architecture with Algorithms
The term “algorithm economy” is relatively new, but the practical use of algorithms is already well established in many industries. In my opinion , CXOs must begin designing their algorithmic business models, both to capitalize on their potential for business differentiation, and to mitigate the possible risks involved.
Established businesses need to adopt a “bi modal strategy” and build what I called an algorithmic platform, completely separate from legacy systems, that harnesses repository of algorithms, interconnections, the cloud and the Internet of Things (IoT) to innovate, share value, increase revenues and manage risk.
New platforms based on this bimodal model should be far simpler, more cloud-based and more flexible than in the past, with the ability to add and remove capabilities “like Velcro” to support new short- and long-term projects. At the same time, IT should start divesting itself of older systems and functions that are outliving their usefulness or could be better done by other methods. The significant development and growth of smart machines is a major factor in the way algorithms have emerged from the shadows, and become more easily accessible to every organization. We can already see their impact in today’s world, but there is much work ahead to harness the opportunities and manage the challenges of algorithmic business.
CXOs should examine how algorithms and intelligent machines are already used by competitors and even other enterprises to determine if there is relevance to their own needs. The retail sector has long been at the leading edge of using smart algorithms to improve business outcomes. Today, many retail analysts believe that the algorithms that automate pricing and merchandising may soon become the most valuable asset that a retailer can possess. In HR function, algorithms are already transforming talent acquisition as they are able to rapidly evaluate the suitability of candidates for specific roles, but the same technology could easily be applied within an enterprise to allocate workloads to the right talent. In healthcare, the open availability of advanced clinical algorithms is transforming the efficiency of healthcare delivery organizations and their ability to deliver care. The practice of sharing and co-developing algorithms between enterprises with mutual interests could be relevant to most enterprises.
The Challenges of Algorithm Economy
The advances and benefits of algorithm economy will come hand in hand with obstacles to navigate. Whether the problems are anticipated or unexpected, as quantum computing becomes more pervasive, the implications have the potential to make or break organizations. For example, an extreme point of view is that any beneficial effects of algorithms on humanity may be nullified by algorithmically driven systems that are antithetical to human interests. Or, while an algorithmic business model may be deployed with good intentions, it could be manipulated by malicious humans to achieve undesirable outcomes. Undesirable, at least, from the point of the view of the person or organization that owns or controls the algorithm. Algorithms rely on the data they are fed, and their decisions are only as good as the data they are based on. Moreover, tricky ethical problems that do not necessarily have a “correct” answer will be inevitable, as a greater complexity of decision making is left in the hands of automated systems.
The scale of change that is made possible by smart machines and algorithm economy warrants considerable planning and testing. Enterprises that fail to prepare risk being left behind or facing unexpected outcomes with negative implications.
The Transformation required in Algorithm Economy
Making sense of all the data about how customers behave, and what connected things tell an organization, will require algorithms to define business processes and create a differentiated customer experience. Algorithms will evaluate suppliers, define how our cars operate, and even determine the right mix of drugs for a patient. In the purely digital world, agents will act independently based on our algorithms, in the cloud. In the 2020s, we’ll move away from using apps to rely on virtual assistants – basically, algorithms in the cloud – to guide us through our daily tasks. People will trust personal algorithms that thinks and acts for them. Take this to another level and the algorithms themselves will eventually become smart by learning from experience and producing results their creators never expected.
The Final Frontier
Therefore, we have to get the architecture of algorithms robust and steady to derive meaningful objectives. In essence, algorithms spot the business moments, meaningful connections, and predict ill behaviors and threats. CXOs need to be the strategic voice on the use of information, to build the right set of intelligent insights. Experience the Algorithm Economy and the ensuing strategic value for your enterprise . Are you geared up ?
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A group of CXOs from several enterprises in Bengaluru came together recently at a round table organised by Forbes India in partnership with Microsoft. They discussed the state of AI and its impact on innovation in their businesses. Below are the edited excerpts:
“Whether we like it or not, AI is absolutely all-pervasive. It’s been there for about 50 years as a technology, but the adoption rate has gone up significantly in just the last four to five years due to multiple reasons – capability, visioning algorithms, better underlying infrastructure to make it run and just the sheer drive of the industry to drive more and more ROI.” said Rohit Adlakha, chief digital and information officer and global head, Wipro HOLMES at Wipro. “Human capability is getting pushed to the limits. How do we augment that with a certain technology that can work hand in hand, while not truly replacing them, but more in terms of enhancement? Looking at the size and scale of a seven billion population across the globe, it is clear that mere technology adoption will not get us there. Something as drastic as an Uber to the power of Uber is what we need actually to make this happen.”
“In terms of AI, adoption is really happening now — it’s no longer just theoretical. Some factors that are helping this are first, the ecosystem. Second, the computing power, the actual physical infrastructure for all this that we have today.” said Satyakam Mohanty, founder of Lymbyc, an AI startup, which has been acquired by Larsen & Toubro Infotech. “One of the challenges is that people are looking at technologies instead of problems. This is creating a lot of silos. If instead, one looked at the problem that needs to be solved and then asked how AI can be applied, then you have a better way to solve this. To get to the world hunger solving stage, you have to industrialise AI, which doesn’t exist today.
Right now, all of the conversation we’re having is the mechanics of how do you make these things operational, but for adoption beyond or even within organizations for larger issues, we have to look at the risk factor.” Satyakam explains further. “Because, as with any technology or business process, there is always a risk factor, right? And the larger the organization, the greater the risk, therefore, slower the adoption that’s the standard paradigm, so how do you de-risk it?”
“At Tech Mahindra we always ask – How can I bring AI into it? The use cases that we did initially were more towards leading process automation or IT operations automation and so on. Now, we have also invested in an open-source AI project called Acumos with AT&T, one of our largest customers,” said George Mundassery, senior VP and global head, Automation and AI at Tech Mahindra. Acumos AI is a platform and open source framework that makes it easy to build, share, and deploy AI apps. Acumos standardises the infrastructure stack and components required to run an out-of-the-box general AI environment. This frees data scientists and model trainers to focus on their core competencies and accelerates innovation. “When it comes to applying the AI and making it more and more vibrant and applying it on the ground, I’m sure that that’s when the real benefits will start to be felt,” said George.
“Companies today have no option but to adopt digital. So at every point, they have to redesign their operations, be it their supply chain or the way they connect with various networks or with customer support. So that’s where those possibilities are enormous with AI,” said Prithvijit Roy, CEO and co-founder of BRIDGEi2i, a data analytics startup. “How can we embed AI in terms of creating our customer support without talking to customers, or how do you give the client or the customer what they need without having them articulate it? So there it’s not necessarily just customer experience. How do you train machines to learn on their own and create an application?” Roy said.
“A customer of mine made this statement: ‘Can we go AI with AI?’ What he meant was can we go ‘All In with AI’!” said Sayandeb Banerjee, CEO, and co-founder of a startup The Math Company. “And then we started talking about what is really stopping us from going AI with AI. The point that came out is the democratisation of the thinking is not happening as fast or the democratisation of the ideas is not happening as fast, which in my mind is what is creating a roadblock. Most of the time, my experience is that the roadblock is really the imagination and the visions of what can be done,” Banerjee said. “If you invariably have a good vision, good leader, things are moving, when you don’t have, everybody has access to the same technology, as we have access to the same platform. Why does it finally boils down to vision from a few?”
“When AI becomes more industrial and gets embedded in many places, the question of our biases becomes more important because you’re no longer thinking about them,” said Rohini Srivathsa, National Technology Officer at Microsoft India. “Take the case of an AI driven translator that interprets a doctor as he, and a nurse as she. We are coming to assume that that’s okay. We are not questioning it because it is so much a part of our thinking that the previous data has brought the pronoun to be changed to.”
Rohini continues, “So I think it creates a bigger question as AI becomes pervasive, industrialised and democratised. Are we putting in the right checks and balances? And when I talk to organisations about checks and balances, I think in some ways it is making us think about our own values first.”
“Eventually, what we are saying is that an algorithm is more about reimagining the decision making in your enterprise,” said Sameer Dhanrajani, CEO and co-founder of AIQRATE, an AI consultancy. “Now, if historically, all the decisions in the boards by the CXOs have been taken in the usual manner, in the conventional organisational structure, that may not be relevant anymore. But when you have an algorithm that works for you – embedded let’s say in the value chain of your business and doing a trade for you – it is, therefore, top of the mindshare for boardrooms, senior leaders, CXOs. Eventually, everyone is saying – look we want AI to revolutionise or reimagine our decision making.”
Sameer clarifies further, “if AI is about mimicking the human brain, organisations must have strategies, which are not defined piecemeal, isolated ad-hoc projects, or the Geek Squad. That’s a fundamental challenge.”
“Where AI is going, I think the new systems will be objective basically because you say I just want to increase my visitors to my store by 5 percent and that’s what it should do — help you make the right changes,” said Atul Batra, CTO at Manthan Software Service. “That’s the sophistication one is looking for. So basically, the systems are getting much more contextual for a specific business role like a merchandiser and store operation and so on. And one is seeing a lot of those systems deployed globally by a lot of vendors. I think that’s where it’s going – where there’s continuous feedback because you’re talking to the system and you’re getting feedback, and you’re helping evolve it.”
“We work to impact livelihoods across 14 disabilities. Purpose driven approach will make people do the right AI,” said Shanti Raghavan, founder of Enable India. “With AI, I’m expecting to be able to nudge people in their journey. Can I make them better at crowdsourcing solutions? We’ve done a lot of product management on this, like, how do you get more people to be like your TripAdvisor contributors, right? So we started introducing star users. The next time somebody comes on the program and says, you know what, I’m a star user, you can see that it’s making a difference. So, we have tons of data on how people are behaving on it, how often they log in, what do they actually listen to? We have all of that. We need AI to make sense of it. Now imagine all this data for the entire country; I cannot do this without having AI.”
“The human brain is not tuned towards trust very easily. So when you look at something physical, it’s very easy to understand. But now you come back and say that beyond the computer’s physical screen there is something, which sits on the cloud, which is a bot, which runs intelligence. I’m telling you, close to 100% will disagree.” Says Rohit Adlakha, chief digital and information officer and global head, Wipro HOLMES at Wipro. “The good part is we feel that AI is going to push the limits of the human brain to do much more than what you were able to do.”
“The challenge is that if a human is ultimately going to train a data set, which is going to train data set, you will always have your biases. So given the practical situation in mind, how do you make sure that you have a larger set of people, which will nullify each other’s biases?” says Rohit. “How do you balance it? How do you augment? How do you know humans and bots coexist? How do you make sure that both coexist and build the cast factor? I think we as an industry should push to move it from an enterprise scale to a global scale.”
“There is one more point out there, which is very, very topical today – that AI itself is not enough,” said Ritwik Batabyal, chief of technology and engineering head, Next-gen Business Products at Wipro. “Now we’re talking about these large, complex unresolved documents in office use cases. I mean somewhere algorithms the best of let’s say these kinds of models cannot solve. And in some way, I think there is a facet that is being understood by enterprises, which is can you bring in behavioral science? How do you design for a subconscious mind? You can have an algorithm, but if it’s not adopted, if it’s not implemented? What’s the use there?”
“I was certainly saying when you look at the most applied systems today, it’s getting better and better in terms of cognitive, but all said and done it is coming from some pattern,” said George Mundassery, senior VP and global head, Automation and AI at Tech Mahindra. “Today, I don’t think, it’s able to tell you that decision you made is the right one,” he said.
“There is no going back in this game; once the genie is out of the bottle we can’t put it back. So it’s like any other revolution, I think it’s going to happen,” says Prithvijit Roy. “The truth is that AI is going to take care of certain kinds of jobs that are repetitive. And that’s going to have an impact because mundane work is people’s livelihood in many parts.”
“So it’s not about replacing the human with other parts; it is making humans do certain things, which they were not able to do, which is the bigger part of the story, but this is going to be an impact in the short-term, which we all know how we will face it. So, it will work with enough time to balance out and will hopefully have better augmentation with it.”