Group items tagged AI - Blog & Blogging..!!

The Long & Short Of An AI Strategy - The AI Company - 0 views

www.autolearn.ai/...ort-term-vs-long-term-strategy

auto learn disital strategy term AI company artificial intelligence

shared by pintadachica on 11 Nov 18 - No Cached

pintadachica on 11 Nov 18

Much has and needs to be said about an enterprise's AI strategy. Artificial Intelligence or AI is considered a fundamentally disruptive technology similar to the steam engine, electricity etc, a technology that will be pervasive and absolute in its impact on the world and its inhabitants. The ability to find hidden patterns to predict the future or detect a behavior has massive implications across the world, in every industry, sector, and domain. When faced with this realization, enterprise's can find themselves stuck, paralyzed and unsure about how to proceed. The field of AI is decades old already and the early success stories have been practicing AI for multiple years already with the tech industry leading the way. How can an enterprise that has no experience and competency in this area let alone lead the technology or even leverage it appropriately to drive business value? When developing the AI strategy, two ideas are paramount. First, this a fundamentally disruptive technology and the enterprise will need to establish it as a core competency for the foreseeable future. Not doing so will not be an option. Second, a long-term plan to success is superseded by the need to drive quick wins and small successes not only to build confidence but use real-world experience to develop and hone that skill. The Short-Term AI Strategy The short-term AI strategy should focus on driving immediate business value through enhanced customer experiences that leverage any field of AI be it machine learning, deep learning, natural language processing etc. Driving the usage and deployment of AI in front of an end user making them smarter, productive and better informed can pay rich dividends by not only helping the enterprise can real-world experience, but it can also give a perception boost to the company as being innovative and cutting edge. However, most importantly, this can highlight and promote the success and potential of AI in the enterprise and encourage a snowball eff

<div class="cArrow"> </div><div class="cContentInner">Much has and needs to be said about an enterprise's AI strategy. Artificial Intelligence or AI is considered a fundamentally disruptive technology similar to the steam engine, electricity etc, a technology that will be pervasive and absolute in its impact on the world and its inhabitants. The ability to find hidden patterns to predict the future or detect a behavior has massive implications across the world, in every industry, sector, and domain. When faced with this realization, enterprise's can find themselves stuck, paralyzed and unsure about how to proceed. The field of AI is decades old already and the early success stories have been practicing AI for multiple years already with the tech industry leading the way. How can an enterprise that has no experience and competency in this area let alone lead the technology or even leverage it appropriately to drive business value? When developing the AI strategy, two ideas are paramount. First, this a fundamentally disruptive technology and the enterprise will need to establish it as a core competency for the foreseeable future. Not doing so will not be an option. Second, a long-term plan to success is superseded by the need to drive quick wins and small successes not only to build confidence but use real-world experience to develop and hone that skill. The Short-Term AI Strategy The short-term AI strategy should focus on driving immediate business value through enhanced customer experiences that leverage any field of AI be it machine learning, deep learning, natural language processing etc. Driving the usage and deployment of AI in front of an end user making them smarter, productive and better informed can pay rich dividends by not only helping the enterprise can real-world experience, but it can also give a perception boost to the company as being innovative and cutting edge. However, most importantly, this can highlight and promote the success and potential of AI in the enterprise and encourage a snowball eff</div>

...

Cancel

Are you AI-First? - The AI Company - 0 views

www.autolearn.ai/...2017-8-16-are-you-ai-first

autolearn first artificial intelligence Ai company digital strategy

shared by pintadachica on 11 Nov 18 - No Cached

pintadachica on 11 Nov 18

Are you AI-First? By editor Posted October 13, 2018 In Artificial Intelligence, Digital Strategy, Technology & Design 0 An AI-First company is an enterprise that has transformed to believe and understand the incredible and disruptive potential of Artificial Intelligence. Such an enterprise not only sees the value but can see the destructive impact of being left behind. An AI-First Company understands that it might not know all the answers but realizes that it needs to seek out a path forward with AI or risk being marginalized. Key Characteristics of an AI-First Company A-First companies might not be any different from their previous form but think and act differently. Here are some key characteristics of such companies. Approach to Problems and Planning An AI-First company evolves its approach to problems. AI-First companies realize that determining the existence of a problem and selecting the most consequential problems is a function of data and analytics. An AI-First company invests in building predictive mechanisms that can signal current or upcoming problems including the severity and priority of these problems. Building these predictive mechanisms becomes the first step in determining how and when to prepare for problems or upcoming issues. In addition, these companies leverage news and information that is generated inside and outside the enterprise as it is generated and ensure that their employees and customers have access to the insights embedded in the news and information. Approach to Products and Product Development An AI-First company understands how a prediction or classification could help them deliver a better solution to a problem faced by their customers and how their existing products can be adapted or new products created that change behavior based on the predictions and classifications. Enterprises that understand the power of AI ensure that data scientists come part of the core product ideation and development team with a heavy infl

<div class="cArrow"> </div><div class="cContentInner">Are you AI-First? By editor Posted October 13, 2018 In Artificial Intelligence, Digital Strategy, Technology & Design 0 An AI-First company is an enterprise that has transformed to believe and understand the incredible and disruptive potential of Artificial Intelligence. Such an enterprise not only sees the value but can see the destructive impact of being left behind. An AI-First Company understands that it might not know all the answers but realizes that it needs to seek out a path forward with AI or risk being marginalized. Key Characteristics of an AI-First Company A-First companies might not be any different from their previous form but think and act differently. Here are some key characteristics of such companies. Approach to Problems and Planning An AI-First company evolves its approach to problems. AI-First companies realize that determining the existence of a problem and selecting the most consequential problems is a function of data and analytics. An AI-First company invests in building predictive mechanisms that can signal current or upcoming problems including the severity and priority of these problems. Building these predictive mechanisms becomes the first step in determining how and when to prepare for problems or upcoming issues. In addition, these companies leverage news and information that is generated inside and outside the enterprise as it is generated and ensure that their employees and customers have access to the insights embedded in the news and information. Approach to Products and Product Development An AI-First company understands how a prediction or classification could help them deliver a better solution to a problem faced by their customers and how their existing products can be adapted or new products created that change behavior based on the predictions and classifications. Enterprises that understand the power of AI ensure that data scientists come part of the core product ideation and development team with a heavy infl</div>

...

Cancel

Skateboarding, The AI Company and the Autolearn Boost - The AI Company - 0 views

www.autolearn.ai/...en-skateboarding-autolearns-ai

artificial intelligence innovation technology digital strategy AI company

shared by pintadachica on 09 Jan 19 - No Cached

What is common between skateboarding and learning to skateboarding & autolearn.ai’s AI platform. Lots, turns out. Consider the process of learning to skateboard. One repeatedly tries a move with the skateboard. You look at if you can land the move. If you do, you try a different move. if you don’t, you slightly vary something in your technique; maybe you try a different center of gravity or angle your legs slightly differently or move your arms differently. Rinse. Repeat. As the skateboarder tries different variations, the “learn” the intricacies of every move and slowly improve. The more time, the more variations and the more analysis they do, the faster they learn and get better. Over time, one can go from a novice to an expert, having built a massive repository of insights and training that help the brain leverage the learning to control the brain that in turn controls the muscles, bones and body weight to effortlessly skateboard. The AI Company’s platform is designed to mimic the process of learning to skateboard. However, instead of sequentially repeating the learning task, the AI platform enables automatically parallelizes the learning process by simultaneously trying out each possible variation for each move and then parallelizing learning multiple moves at the same time. This massive parallelization is accentuated by the automatic selection of the most optimal and accurate insights (AI models) that learn the best in the context of the problem at hand. The best AI models are automatically deployed to production, stored in a very secure form and can be leveraged in traditional app development or in the development of intelligent smart contracts (AutoLearn’s SmartChain). Imagine learning a skill instantly by parallelizing your learning so that you can try out the millions of variations, learn from them and ingest the learnings instantly. This is the AutoLearn boost.  With The AI Company’s AI, you are able to reduce what traditionally in data science would take upwards of a year and multiple data scientists to mere days through the automated training, selection and deployment of the best AI models out of 1000s of variations generated in parallel by AutoLearn. Not only do you reduce the time taken to go live with AI, because of the automation and the efficiency maximizer in AutoLearn’s AutoAI, you are guaranteed the best possible AI model. This is not guaranteed in a manually driven data science practice!
...

Cancel

pintadachica on 09 Jan 19

What is common between skateboarding and learning to skateboarding & autolearn.ai's AI platform. Lots, turns out. Consider the process of learning to skateboard. One repeatedly tries a move with the skateboard. You look at if you can land the move. If you do, you try a different move. if you don't, you slightly vary something in your technique; maybe you try a different center of gravity or angle your legs slightly differently or move your arms differently. Rinse. Repeat. As the skateboarder tries different variations, the "learn" the intricacies of every move and slowly improve. The more time, the more variations and the more analysis they do, the faster they learn and get better. Over time, one can go from a novice to an expert, having built a massive repository of insights and training that help the brain leverage the learning to control the brain that in turn controls the muscles, bones and body weight to effortlessly skateboard. The AI Company's platform is designed to mimic the process of learning to skateboard. However, instead of sequentially repeating the learning task, the AI platform enables automatically parallelizes the learning process by simultaneously trying out each possible variation for each move and then parallelizing learning multiple moves at the same time. This massive parallelization is accentuated by the automatic selection of the most optimal and accurate insights (AI models) that learn the best in the context of the problem at hand. The best AI models are automatically deployed to production, stored in a very secure form and can be leveraged in traditional app development or in the development of intelligent smart contracts (AutoLearn's SmartChain). Imagine learning a skill instantly by parallelizing your learning so that you can try out the millions of variations, learn from them and ingest the learnings instantly. This is the AutoLearn boost. With The AI Company's AI, you are able to reduce what traditionally in data

<div class="cArrow"> </div><div class="cContentInner">What is common between skateboarding and learning to skateboarding & autolearn.ai's AI platform. Lots, turns out. Consider the process of learning to skateboard. One repeatedly tries a move with the skateboard. You look at if you can land the move. If you do, you try a different move. if you don't, you slightly vary something in your technique; maybe you try a different center of gravity or angle your legs slightly differently or move your arms differently. Rinse. Repeat. As the skateboarder tries different variations, the "learn" the intricacies of every move and slowly improve. The more time, the more variations and the more analysis they do, the faster they learn and get better. Over time, one can go from a novice to an expert, having built a massive repository of insights and training that help the brain leverage the learning to control the brain that in turn controls the muscles, bones and body weight to effortlessly skateboard. The AI Company's platform is designed to mimic the process of learning to skateboard. However, instead of sequentially repeating the learning task, the AI platform enables automatically parallelizes the learning process by simultaneously trying out each possible variation for each move and then parallelizing learning multiple moves at the same time. This massive parallelization is accentuated by the automatic selection of the most optimal and accurate insights (AI models) that learn the best in the context of the problem at hand. The best AI models are automatically deployed to production, stored in a very secure form and can be leveraged in traditional app development or in the development of intelligent smart contracts (AutoLearn's SmartChain). Imagine learning a skill instantly by parallelizing your learning so that you can try out the millions of variations, learn from them and ingest the learnings instantly. This is the AutoLearn boost. With The AI Company's AI, you are able to reduce what traditionally in data</div>

...

Cancel

Why Is Sentiment Such A Big Deal? - The AI Company - 0 views

www.autolearn.ai/...2017-8-3-sentiment

autolearn artificial intelligence AI company sentiment digital strategy technology

shared by pintadachica on 07 Jan 19 - No Cached

pintadachica on 07 Jan 19

Sentiment, Sentiment Analysis, Sentiment Tracking have become a hot topic with multiple 'AI' startups focussing on providing sentiment driven insights to enterprises. The number of such startups points to the potential that enterprises see in Sentiment analysis and the impact it has on how the enterprise plans, operates, executes and delivers value. Sentiment Analysis is process of extracting sentiment (emotion or feelings) captured in signals that are embedded in various types of media such as print, text, audio, video, images etc. For example, if a reporter submits a report on a particular enterprise, the sentiment embedded in the article can point to how excited, worried, upbeat or impassive they might are about the enterprise. This sentiment can be then used by the enterprise to understand the perception about the enterprise that the external market carries and whether that perception is improving, degrading or staying unchanged. This insight can be used by the enterprise to improve their go to market plans, change their PR strategy or even go deeper and change their product strategy. Sentiment Analysis Is Not New The tracking, measurement and use of Sentiment is not a new scenario. Enterprises have been leveraging the output of sentiment analysis for a long time. User surveys, focus groups, market research, customer interviews etc. are all examples of generating data to perform and track sentiment. Similarly, influencer marketing through association with influencers or events or organizations with a certain perception or sentiment associated with them is a common technique to improve the enterprise's own sentiment. Sentiment Analysis and strategizing based on the analysis is a common and required function for any enterprise. Sentiment Analysis Using Artificial Intelligence With the advent of Artificial Intelligence (AI), enterprises now have another technique in their kitty to understand how they are perceived in the market and how that perception i

<div class="cArrow"> </div><div class="cContentInner">Sentiment, Sentiment Analysis, Sentiment Tracking have become a hot topic with multiple 'AI' startups focussing on providing sentiment driven insights to enterprises. The number of such startups points to the potential that enterprises see in Sentiment analysis and the impact it has on how the enterprise plans, operates, executes and delivers value. Sentiment Analysis is process of extracting sentiment (emotion or feelings) captured in signals that are embedded in various types of media such as print, text, audio, video, images etc. For example, if a reporter submits a report on a particular enterprise, the sentiment embedded in the article can point to how excited, worried, upbeat or impassive they might are about the enterprise. This sentiment can be then used by the enterprise to understand the perception about the enterprise that the external market carries and whether that perception is improving, degrading or staying unchanged. This insight can be used by the enterprise to improve their go to market plans, change their PR strategy or even go deeper and change their product strategy. Sentiment Analysis Is Not New The tracking, measurement and use of Sentiment is not a new scenario. Enterprises have been leveraging the output of sentiment analysis for a long time. User surveys, focus groups, market research, customer interviews etc. are all examples of generating data to perform and track sentiment. Similarly, influencer marketing through association with influencers or events or organizations with a certain perception or sentiment associated with them is a common technique to improve the enterprise's own sentiment. Sentiment Analysis and strategizing based on the analysis is a common and required function for any enterprise. Sentiment Analysis Using Artificial Intelligence With the advent of Artificial Intelligence (AI), enterprises now have another technique in their kitty to understand how they are perceived in the market and how that perception i</div>

...

Cancel

5 signs why your digital transformation might be in trouble - The AI Company - 0 views

www.autolearn.ai/...sformation-might-be-in-trouble

AI Company digital transformation learn cloud artificial intelligence

shared by pintadachica on 10 Nov 18 - No Cached

pintadachica on 10 Nov 18

Digital Transformation is tough, even for seasoned technologists. This is because it is a transformation of an organization at its core. Everything from culture, technology, ideation, development, integration, delivery, and support needs to fundamentally shift to be more customer-centric, service driven, automation first and experimental in nature. No wonder that a lot of organizations take a long time and a lot of investment to see ROI from their digital transformations. Here are 5 signs that your digital transformation might be in trouble. Culture mistrusts the core digital transformation team You are spawning new initiatives before completing previous ones Decisions are top down with low accountability at the leaf nodes You tend to focus on technology stacks with little focus on customer value Inter-organization politics stifles cross-organization scenarios Culture mistrusts the core digital transformation team It is almost impossible to make an entire organization aware and participate in digital transformation at the same time. There are exceptions but in our experience, starting out with a core digital transformation team is a much better strategy than otherwise. This team should be enabled to attack a limited set of important and business relevant problems, build cutting-edge solutions and use them as examples to train and evangelize digital transformation strategies to the rest of the organization. However, the more entrenched an organization in the old way of doing things, the harder they might this central team. Resistance can be active and passive such as refusal to share data or provide the relevant context of the problem. An organization that does not set up the early crusaders for success almost always has a much harder time showing value from their digital transformation activities. You are spawning new initiatives before completing previous ones Executing on a digital transformation strategy is much harder than defining the strategy especially fo

<div class="cArrow"> </div><div class="cContentInner">Digital Transformation is tough, even for seasoned technologists. This is because it is a transformation of an organization at its core. Everything from culture, technology, ideation, development, integration, delivery, and support needs to fundamentally shift to be more customer-centric, service driven, automation first and experimental in nature. No wonder that a lot of organizations take a long time and a lot of investment to see ROI from their digital transformations. Here are 5 signs that your digital transformation might be in trouble. Culture mistrusts the core digital transformation team You are spawning new initiatives before completing previous ones Decisions are top down with low accountability at the leaf nodes You tend to focus on technology stacks with little focus on customer value Inter-organization politics stifles cross-organization scenarios Culture mistrusts the core digital transformation team It is almost impossible to make an entire organization aware and participate in digital transformation at the same time. There are exceptions but in our experience, starting out with a core digital transformation team is a much better strategy than otherwise. This team should be enabled to attack a limited set of important and business relevant problems, build cutting-edge solutions and use them as examples to train and evangelize digital transformation strategies to the rest of the organization. However, the more entrenched an organization in the old way of doing things, the harder they might this central team. Resistance can be active and passive such as refusal to share data or provide the relevant context of the problem. An organization that does not set up the early crusaders for success almost always has a much harder time showing value from their digital transformation activities. You are spawning new initiatives before completing previous ones Executing on a digital transformation strategy is much harder than defining the strategy especially fo</div>

...

Cancel

To be AI-first, move beyond managing data infrastructure - The AI Company - 0 views

www.autolearn.ai/...d-managing-data-infrastructure

Auto Learn Artificial Intelligence Ai Company First

shared by pintadachica on 10 Nov 18 - No Cached

Unfortunately, the past few years, driven by the big data hype, have encouraged enterpris
...

Cancel

pintadachica on 10 Nov 18

Success with AI is heavily influenced by the data maturity of an organization i.e. their ability to procure, clean, curate, store and analyze data to power value generating applications. A data-mature enterprise know what data it has, knows what the data means and can ensure that the data is accessible to whoever needs it. Unfortunately, the past few years, driven by the big data hype, have encouraged enterprises to focus on updating their data infrastructure to leverage new big data technologies. With a lot more data now available, enterprises already stuck with massive data storage costs, are being forced to choose between storing data that might eventually be useful for stabilizing, if not reducing their storage costs.

<div class="cArrow"> </div><div class="cContentInner">Success with AI is heavily influenced by the data maturity of an organization i.e. their ability to procure, clean, curate, store and analyze data to power value generating applications. A data-mature enterprise know what data it has, knows what the data means and can ensure that the data is accessible to whoever needs it. Unfortunately, the past few years, driven by the big data hype, have encouraged enterprises to focus on updating their data infrastructure to leverage new big data technologies. With a lot more data now available, enterprises already stuck with massive data storage costs, are being forced to choose between storing data that might eventually be useful for stabilizing, if not reducing their storage costs.</div>

...

Cancel

Service Ticket AI - The AI Company - 0 views

www.autolearn.ai/...ticket-ai

Artificial intelligence AI Autolearn technology innovation. company software

shared by pintadachica on 01 Mar 19 - No Cached

pintadachica on 01 Mar 19

Reduce the frustration for your customers Detect, diagnose & address customer & employees faster with 20+ deep learning trained AI models that classify, categorize & identify ticket causes & resolution.

<div class="cArrow"> </div><div class="cContentInner">Reduce the frustration for your customers Detect, diagnose & address customer & employees faster with 20+ deep learning trained AI models that classify, categorize & identify ticket causes & resolution.</div>

...

Cancel

Don't Reinvent The Wheel - The AI Company - 0 views

www.autolearn.ai/...7-8-29-dont-reinvent-the-wheel

AI autolearn Artificial intelligence technology innovation enterprises

shared by pintadachica on 18 Jan 19 - No Cached

pintadachica on 18 Jan 19

One of the top reasons for digital innovation and transformation failures can be summarized as the enterprise trying to reinvent the wheel. This is the tendency of the enterprise to attempt to create technology, platforms, and applications that have already been implemented, scaled, optimized and almost perfected. This tendency almost always ends up a failed one as it does not create any net new value for the enterprise but comes with a massive opportunity cost as the enterprise spends crucial resources on reinventing the wheel than innovating for the customer. How The Wheel Is Reinvented Nontechnology enterprises can get trapped in a reinvent state where they conclude that homegrown technology is the only path towards customer and business value. This in itself is not entirely false however the type of enterprise and their decision-making process along with the capabilities they have in house have a very large impact on the success of the strategy.eRaaadada Reinventing the wheel happens when a non-tech enterprise discovers a technology trend towards much later in the hype cycle almost towards the end when the technology is hitting the mass market and decides to recreate or reinvent its own version of the technology. This is often done with the assumption that with some investment, the enterprise can have a home grown version of technology or platform that is designed specifically for its needs and is thus a better fit. However, enterprises assume that the state of the technology will remain constant and while they are attempting to home grow a version that can match the current state of the art. In reality, the state of the art shifts and the enterprise is not able to bridge the gap. Who Reinvents The Wheel Typically, technology teams often decide to go down the path of reinvention when they are allowed to make technology upgrade or technology creation decisions without business KPIs and cost constraints i.e. clear success criteria with fixed cost and clear ti

<div class="cArrow"> </div><div class="cContentInner">One of the top reasons for digital innovation and transformation failures can be summarized as the enterprise trying to reinvent the wheel. This is the tendency of the enterprise to attempt to create technology, platforms, and applications that have already been implemented, scaled, optimized and almost perfected. This tendency almost always ends up a failed one as it does not create any net new value for the enterprise but comes with a massive opportunity cost as the enterprise spends crucial resources on reinventing the wheel than innovating for the customer. How The Wheel Is Reinvented Nontechnology enterprises can get trapped in a reinvent state where they conclude that homegrown technology is the only path towards customer and business value. This in itself is not entirely false however the type of enterprise and their decision-making process along with the capabilities they have in house have a very large impact on the success of the strategy.eRaaadada Reinventing the wheel happens when a non-tech enterprise discovers a technology trend towards much later in the hype cycle almost towards the end when the technology is hitting the mass market and decides to recreate or reinvent its own version of the technology. This is often done with the assumption that with some investment, the enterprise can have a home grown version of technology or platform that is designed specifically for its needs and is thus a better fit. However, enterprises assume that the state of the technology will remain constant and while they are attempting to home grow a version that can match the current state of the art. In reality, the state of the art shifts and the enterprise is not able to bridge the gap. Who Reinvents The Wheel Typically, technology teams often decide to go down the path of reinvention when they are allowed to make technology upgrade or technology creation decisions without business KPIs and cost constraints i.e. clear success criteria with fixed cost and clear ti</div>

...

Cancel

The LearnCloud Experience - The AI Company - 0 views

www.autolearn.ai/the-learncloud-experience

AI Artificial Intelligence Auto Learn Cloud Experience

shared by pintadachica on 10 Nov 18 - No Cached

pintadachica on 10 Nov 18

We are a different AI company. See how our LearnCloud brings together your entire enterprise to operate on the same "information plane" towards an exponential increase in efficiency. Jenny is responsible for customers at Acme Corp Jenny feels she is driving blind. She realizes the ground truth but often it is too late. The information is spread across multiple applications & systems. Even when available, it does not help her look into the future so that she can act & save the day Sarah is a Support professional at Acme Corp Sarah feels she has her hands tied behind her back. She has to manually process each & every issue. Her job is tedious and inconsistent. She is not able to leverage patterns across issues & across support professionals. John is a salesperson at Acme Corp John is frustrated with antiquated tools & late arriving insights He has to manually scour the internet for information about his prospects & their changing strategies. He has to talk to many people to understand the state of the customer. By the time he understands the current state, it is often too late to prevent abandonment or drive the expansion People like them encounter these problems all the time which causes frustration and attrition for them and their customers. How does this happen?

<div class="cArrow"> </div><div class="cContentInner">We are a different AI company. See how our LearnCloud brings together your entire enterprise to operate on the same "information plane" towards an exponential increase in efficiency. Jenny is responsible for customers at Acme Corp Jenny feels she is driving blind. She realizes the ground truth but often it is too late. The information is spread across multiple applications & systems. Even when available, it does not help her look into the future so that she can act & save the day Sarah is a Support professional at Acme Corp Sarah feels she has her hands tied behind her back. She has to manually process each & every issue. Her job is tedious and inconsistent. She is not able to leverage patterns across issues & across support professionals. John is a salesperson at Acme Corp John is frustrated with antiquated tools & late arriving insights He has to manually scour the internet for information about his prospects & their changing strategies. He has to talk to many people to understand the state of the customer. By the time he understands the current state, it is often too late to prevent abandonment or drive the expansion People like them encounter these problems all the time which causes frustration and attrition for them and their customers. How does this happen?</div>

...

Cancel

Our Products - The AI Company - 0 views

www.autolearn.ai/products

AI Company Auto Learn Products customer

shared by pintadachica on 10 Nov 18 - No Cached

pintadachica on 10 Nov 18

A comprehensive set of auto-learning, AI-driven applications.

<div class="cArrow"> </div><div class="cContentInner">A comprehensive set of auto-learning, AI-driven applications. </div>

...

Cancel

Future Proofing for Agility - The AI Company - 0 views

www.autolearn.ai/...2017-8-30-thoughts-on-agility

Proofing agility Ai Company autolearn artificial intelligence strategy digital

shared by pintadachica on 11 Nov 18 - No Cached

pintadachica on 11 Nov 18

A lot has been said about agility and the need for enterprises looking to innovate and disrupt to build agility. Agility, at the same time, also gets confused with the process of scrum. Small and large teams get enamored with the idea of scrum and mistake the process with the state of being agile. This is often more detrimental to the enterprise and can often create more process and not enough real agility. What is Agility Agility is the efficiency with which an enterprise executes and delivers on its objectives and goals. Agility is the ability to react to changes in goals, feedback from customers and shifts in strategy. Agility, from the outside, looks like a predictable stream of value delivered by the enterprise that matches and exceeds the needs of the customer. Organizational agility requires agility at multiple levels within the enterprise to drive the insights that can channel and align the efforts of the entire organization by leveraging data and information to make quick and informed decisions. Business Agility Business and customer-facing employees need to achieve "Business Agility". This is the ability of these employees to react to business critical in real time if needed and have access to the latest information at any decision point. Business Agility enables users to reduce the latency or lag between a need in the market or of the customers and when they are able to service the need. Decision Agility Analysts and data scientists creating the insights to drive decisions require "Decision Agility" i.e the ability to easily discover, leverage and use data for analytics and insights through any and multiple tools and channels. Analysts and data scientists need to produce insights that reduce the time and effort required to convert data into information and insights that are required to drive key decisions and actions. Development Agility Application developers and data engineers need the ability to easily generate, collect, access and deli

<div class="cArrow"> </div><div class="cContentInner">A lot has been said about agility and the need for enterprises looking to innovate and disrupt to build agility. Agility, at the same time, also gets confused with the process of scrum. Small and large teams get enamored with the idea of scrum and mistake the process with the state of being agile. This is often more detrimental to the enterprise and can often create more process and not enough real agility. What is Agility Agility is the efficiency with which an enterprise executes and delivers on its objectives and goals. Agility is the ability to react to changes in goals, feedback from customers and shifts in strategy. Agility, from the outside, looks like a predictable stream of value delivered by the enterprise that matches and exceeds the needs of the customer. Organizational agility requires agility at multiple levels within the enterprise to drive the insights that can channel and align the efforts of the entire organization by leveraging data and information to make quick and informed decisions. Business Agility Business and customer-facing employees need to achieve "Business Agility". This is the ability of these employees to react to business critical in real time if needed and have access to the latest information at any decision point. Business Agility enables users to reduce the latency or lag between a need in the market or of the customers and when they are able to service the need. Decision Agility Analysts and data scientists creating the insights to drive decisions require "Decision Agility" i.e the ability to easily discover, leverage and use data for analytics and insights through any and multiple tools and channels. Analysts and data scientists need to produce insights that reduce the time and effort required to convert data into information and insights that are required to drive key decisions and actions. Development Agility Application developers and data engineers need the ability to easily generate, collect, access and deli</div>

...

Cancel

Going Through Digital Transformation. What's next? - The AI Company - 0 views

www.autolearn.ai/...ital-transformation-whats-next

autolearn artificial intelligence digital transformation technology innovation AI strategy software company

shared by pintadachica on 13 Dec 18 - No Cached

pintadachica on 13 Dec 18

Digital Transformation is a huge topic now. Most software vendors have adapted their products to include the Digital Transformation message. Transforming into a digital company is no longer a choice and it is clear that the companies that transform faster can develop a competitive advantage that will serve them for years while the companies that do not will slowly fade into irrelevance. Digital Transformation is the change in an enterprise that makes it acquire and deploy the best in class technology assets and systematically removing analog or manual touch points, handoffs, processes and decision making. It is the ability of the enterprise to understand, assimilate and leverage the latest technology trends such as cloud, mobile, APIs, AI, Blockchain, ChatBots, Analytics, IoT etc.

<div class="cArrow"> </div><div class="cContentInner">Digital Transformation is a huge topic now. Most software vendors have adapted their products to include the Digital Transformation message. Transforming into a digital company is no longer a choice and it is clear that the companies that transform faster can develop a competitive advantage that will serve them for years while the companies that do not will slowly fade into irrelevance. Digital Transformation is the change in an enterprise that makes it acquire and deploy the best in class technology assets and systematically removing analog or manual touch points, handoffs, processes and decision making. It is the ability of the enterprise to understand, assimilate and leverage the latest technology trends such as cloud, mobile, APIs, AI, Blockchain, ChatBots, Analytics, IoT etc.</div>

...

Cancel

Not too late to jump on Blockchains - The AI Company - 0 views

www.autolearn.ai/...oo-late-to-jump-on-blockchains

autolearn technology digital strategy data business AI company design blockhains

shared by pintadachica on 20 Dec 18 - No Cached

pintadachica on 20 Dec 18

It's not too late to jump on to the Blockchains trend. We often hear from customers whether it is too late to get behind blockchain. The number of startups in this space is growing rapidly and the number of large ISVs and SIs providing blockchain capability and expertise is also increasing. However, the market and the technology space for blockchains is far from saturated, settled or stable. Here are three reasons why now is a good time to get into blockchains Early Mover Advantage Blockchains are bound to disrupt fundamentally how business is done. By enabling trust in an otherwise trust-deficient environment, blockchains enable transactions between two or more enterprises who otherwise might not know about each other. Blockchains offer solutions to several common problems faced by the enterprise such as Digital Identity, Secure Data Storage, Secure Data Sharing, Distributed Ledger, Distributed Databases etc. Blockchains are based on strong cryptographic standards based in mathematics, cryptography, and encryption. Building blockchains as a core competency requires a deep understanding of the mathematics behind it and an internal process for deploying, managing and developing on top of the blockchain. Early mover advantage can be generated by taking small steps in this area and targeting simpler scenarios initially. Nascent Technology It is going to take another few iterations of the blockchain technology before it can truly be enterprise-ready. There is a lot of ongoing work to make blockchains more secure, scalable and performant. Innovations are constantly being made and added to the core blockchain technology that is constantly increasing the type and complexity of applications that it can support. As the technology matures, enterprises can be well suited and ready to leverage the advancements by building a core competency in not only the blockchain technology but by becoming a member of the blockchain community, standards and keeping up to date with th

<div class="cArrow"> </div><div class="cContentInner">It's not too late to jump on to the Blockchains trend. We often hear from customers whether it is too late to get behind blockchain. The number of startups in this space is growing rapidly and the number of large ISVs and SIs providing blockchain capability and expertise is also increasing. However, the market and the technology space for blockchains is far from saturated, settled or stable. Here are three reasons why now is a good time to get into blockchains Early Mover Advantage Blockchains are bound to disrupt fundamentally how business is done. By enabling trust in an otherwise trust-deficient environment, blockchains enable transactions between two or more enterprises who otherwise might not know about each other. Blockchains offer solutions to several common problems faced by the enterprise such as Digital Identity, Secure Data Storage, Secure Data Sharing, Distributed Ledger, Distributed Databases etc. Blockchains are based on strong cryptographic standards based in mathematics, cryptography, and encryption. Building blockchains as a core competency requires a deep understanding of the mathematics behind it and an internal process for deploying, managing and developing on top of the blockchain. Early mover advantage can be generated by taking small steps in this area and targeting simpler scenarios initially. Nascent Technology It is going to take another few iterations of the blockchain technology before it can truly be enterprise-ready. There is a lot of ongoing work to make blockchains more secure, scalable and performant. Innovations are constantly being made and added to the core blockchain technology that is constantly increasing the type and complexity of applications that it can support. As the technology matures, enterprises can be well suited and ready to leverage the advancements by building a core competency in not only the blockchain technology but by becoming a member of the blockchain community, standards and keeping up to date with th</div>

...

Cancel

Are you worried about the quality of your data? - The AI Company - 0 views

www.autolearn.ai/...about-the-quality-of-your-data

AI company autolearn Business innovation technology digital journey strategy data transformations

shared by pintadachica on 20 Dec 18 - No Cached

pintadachica on 20 Dec 18

The quality or the lack thereof can be a huge contributing factor to a fractured and sluggish digital journey where ROI is hard to achieve and results come in short supply. The quality of data has a direct impact on the ability of the enterprise to be aware of relevant events, its reaction time, the decision time and its action time. A clear and concerted effort is required to measure and improve the data quality to drive better decisions and actions. Common Quality Issues The following are the most common quality issues Comprehensiveness Comprehensiveness quality issues refer to key attributes or data points missing from the data collected by the enterprise. This can occur when the data producing systems or the data delivery networks have glitches or malfunction or are incorrectly configured to miss entire rows of data or attributes of the data. Integrity Integrity quality issues refer to the corruption of the values of key attributes to contain unidentifiable or unreadable data. When key attributes are empty or null when they are by design, not allowed to be empty/null or when an attribute contains a value that does not meet the specifications of the type of the attribute for example, a string column contains an integer or a timestamp column contains a string not parse-able into a timestamp. Integrity of data is important before data can be included in the data set to drive analysis, decisions and actions. Sampling Sampling quality issues refer to the inclusion or exclusion of a certain percentage of the records in a data set with the assumption that the remainder records are good, representative sample of the original data set. Bad or inaccurate sampling can lead to a distorted view of reality and that can lead to bad decisions. In addition, sampling itself can make the data set inappropriate for certain types of analysis that require the entire dat set to be utilized for training. Filtering An upstream filtering scheme can end up removing too many or

<div class="cArrow"> </div><div class="cContentInner">The quality or the lack thereof can be a huge contributing factor to a fractured and sluggish digital journey where ROI is hard to achieve and results come in short supply. The quality of data has a direct impact on the ability of the enterprise to be aware of relevant events, its reaction time, the decision time and its action time. A clear and concerted effort is required to measure and improve the data quality to drive better decisions and actions. Common Quality Issues The following are the most common quality issues Comprehensiveness Comprehensiveness quality issues refer to key attributes or data points missing from the data collected by the enterprise. This can occur when the data producing systems or the data delivery networks have glitches or malfunction or are incorrectly configured to miss entire rows of data or attributes of the data. Integrity Integrity quality issues refer to the corruption of the values of key attributes to contain unidentifiable or unreadable data. When key attributes are empty or null when they are by design, not allowed to be empty/null or when an attribute contains a value that does not meet the specifications of the type of the attribute for example, a string column contains an integer or a timestamp column contains a string not parse-able into a timestamp. Integrity of data is important before data can be included in the data set to drive analysis, decisions and actions. Sampling Sampling quality issues refer to the inclusion or exclusion of a certain percentage of the records in a data set with the assumption that the remainder records are good, representative sample of the original data set. Bad or inaccurate sampling can lead to a distorted view of reality and that can lead to bad decisions. In addition, sampling itself can make the data set inappropriate for certain types of analysis that require the entire dat set to be utilized for training. Filtering An upstream filtering scheme can end up removing too many or </div>

...

Cancel

Can you transform into a tech company? - The AI Company - 0 views

www.autolearn.ai/...-transform-into-a-tech-company

autolearn AI artificial intelligence digital strategy Company auto learn

shared by pintadachica on 11 Nov 18 - No Cached

pintadachica on 11 Nov 18

Transforming into a tech company has become top of mind for executives in all major industries. It is clear that modern technology will fundamentally alter what and how business is done in every domain, sector, and industry. This has led to a call to arms in every enterprise to understand how they can transform into a tech company. The Tech Company Magic Tech companies have fine-tuned the art of bring new digital products and services to the market, quickly, efficiently and effectively and understanding customer feedback to iterate and improve. This capability makes them incredibly agile and leads to faster experimentation that is cheaper and involves less risk. In turn, this enables them to bring new capabilities to the market and even if all do not succeed or get traction, a few do and that drives innovation, customer satisfaction, and growth. From the outside, tech companies appear to be massive juggernauts that are unstoppable and able to crush everything in their path. The 'Non-Tech' Technology has been leveraged in every sector and industry, however, it has almost always been treated as a means to an end, something that is required but never the real value driver for the customer. This has led to the typical organizational structure in enterprises into "Business", "Operations" and "Information Technology". The "Business" arm generates value for customers, the "Operations" team carries out the requirements of the Business team and the "Information Technology" team provides the systems (databases, network and compute) required to "keep the lights on" for the Operations and Business Teams" This structure served enterprises well in the last decades as customers did not have an alternative to directly working with the enterprise and this fortified the value supply chain and also established a hierarchy of sorts within the enterprise where the business looked down upon operations who looked down upon technology. The purpose of

<div class="cArrow"> </div><div class="cContentInner">Transforming into a tech company has become top of mind for executives in all major industries. It is clear that modern technology will fundamentally alter what and how business is done in every domain, sector, and industry. This has led to a call to arms in every enterprise to understand how they can transform into a tech company. The Tech Company Magic Tech companies have fine-tuned the art of bring new digital products and services to the market, quickly, efficiently and effectively and understanding customer feedback to iterate and improve. This capability makes them incredibly agile and leads to faster experimentation that is cheaper and involves less risk. In turn, this enables them to bring new capabilities to the market and even if all do not succeed or get traction, a few do and that drives innovation, customer satisfaction, and growth. From the outside, tech companies appear to be massive juggernauts that are unstoppable and able to crush everything in their path. The 'Non-Tech' Technology has been leveraged in every sector and industry, however, it has almost always been treated as a means to an end, something that is required but never the real value driver for the customer. This has led to the typical organizational structure in enterprises into "Business", "Operations" and "Information Technology". The "Business" arm generates value for customers, the "Operations" team carries out the requirements of the Business team and the "Information Technology" team provides the systems (databases, network and compute) required to "keep the lights on" for the Operations and Business Teams" This structure served enterprises well in the last decades as customers did not have an alternative to directly working with the enterprise and this fortified the value supply chain and also established a hierarchy of sorts within the enterprise where the business looked down upon operations who looked down upon technology. The purpose of </div>

...

Cancel

Self Preservation: The Number One Hurdle To Innovation - The AI Company - 0 views

www.autolearn.ai/...umber-one-hurdle-to-innovation

innovation technology digital strategy tech AI artificial intelligence autolearn

shared by pintadachica on 07 Jan 19 - No Cached

pintadachica on 07 Jan 19

One of the biggest hurdles to Digital Transformation and Digital Innovation is the organization's inertia and tendency to optimize for self-preservation. Self-preservation can exist in the enterprise at the individual, team, divisional or the organizational level and can have a devastating impact on the organization's ability to innovate and grow. Self-preservation is not a new phenomenon however, it is more deadly for an enterprise now than ever. This is because the speed of technology change has increased geometrically. In the past, self-preservation would automatically get corrected as the technology was generally learned and adopted slowly with enough time for the enterprise to become aware of the change and implement it. However, the rate of technology change has magnified tremendously and the enterprises no longer have the luxury to take their time with the change. Inaction risks getting left behind and other competitors who leverage and change faster stand to capture the largest market shares and customer mind share. Self preservation is the tendency of the enterprise to ignore, undermine or postpone the adoption and integration of new technology in the enterprise to avoid a change in the status quo across technology, products, services and most importantly, day to day operations and organizational structure. Self-preservation can lead to what is termed as "politics" in an org, it can stifle innovation and innovative individuals & teams and it can favor business driver stagnation over risk taking. 5 Signs of Self-Preservation The following are signs of self-preservation Highlighting the Journey of Innovation as Failure Adversarial teams and individuals within an enterprise who are interested in self-preservation often go out of their way to highlight the tough, risky journey of true innovation as a failure citing the cost and the time being taken to address the real problems in a truly innovative manner. While the individuals and teams trying to

<div class="cArrow"> </div><div class="cContentInner">One of the biggest hurdles to Digital Transformation and Digital Innovation is the organization's inertia and tendency to optimize for self-preservation. Self-preservation can exist in the enterprise at the individual, team, divisional or the organizational level and can have a devastating impact on the organization's ability to innovate and grow. Self-preservation is not a new phenomenon however, it is more deadly for an enterprise now than ever. This is because the speed of technology change has increased geometrically. In the past, self-preservation would automatically get corrected as the technology was generally learned and adopted slowly with enough time for the enterprise to become aware of the change and implement it. However, the rate of technology change has magnified tremendously and the enterprises no longer have the luxury to take their time with the change. Inaction risks getting left behind and other competitors who leverage and change faster stand to capture the largest market shares and customer mind share. Self preservation is the tendency of the enterprise to ignore, undermine or postpone the adoption and integration of new technology in the enterprise to avoid a change in the status quo across technology, products, services and most importantly, day to day operations and organizational structure. Self-preservation can lead to what is termed as "politics" in an org, it can stifle innovation and innovative individuals & teams and it can favor business driver stagnation over risk taking. 5 Signs of Self-Preservation The following are signs of self-preservation Highlighting the Journey of Innovation as Failure Adversarial teams and individuals within an enterprise who are interested in self-preservation often go out of their way to highlight the tough, risky journey of true innovation as a failure citing the cost and the time being taken to address the real problems in a truly innovative manner. While the individuals and teams trying to</div>

...

Cancel

Are You Prepared To Be A Digital Organization - The AI Company - 0 views

www.autolearn.ai/...d-to-be-a-digital-organization

digital company autolearn AI Artificial intelligence

shared by pintadachica on 18 Jan 19 - No Cached

pintadachica on 18 Jan 19

For many enterprises, transforming into a digital organization is a very big priority. Digitization is more than a passing fad; instead it almost is a precursor to survival in the next decade. Analog mechanisms of running businesses are no longer sustainable nor likely to give confidence to customers, employees, stakeholders and shareholders. Measuring Digital A digital organization is characterized by the following Time to Customer Insight The Time to Customer Insight in a digital organization is the time it takes to collect, process, analyze information to determine the health of a customer, their satisfaction with current products and services, their unmet, possibly unstated needs and the impact that external market events might have on the customer. Time to Reaction Time to Reaction is the time taken to react to a customer insight through the introduction of a new product/service to solve an existing or a new problem or through better packaging of existing solutions to address otherwise existing problems. Time to Market Time to Market is the time taken to bring a new capability, product or service to market often as reaction to a customer or market insight or feedback Time to Iteration Time to Iteration is the time taken to solicit, gather, process, analyze customer feedback and effect a change in existing products or services or bring new products and services to market to address the customer feedback. Digital Organizations Digital organizations are characterized with minimal Time to Customer Insight, Time to Reaction, Time to Market, Time to Iteration and a constant effort and investment into further optimizing and minimizing these metrics. Digital organizations focus on the flow of information through the organization and use of the information to generate and deliver more value for the customers. Key Characteristics of Digital Organizations Instrumentation of Interfaces, Products, Systems, Applications, Processes A digital organization ensures

<div class="cArrow"> </div><div class="cContentInner">For many enterprises, transforming into a digital organization is a very big priority. Digitization is more than a passing fad; instead it almost is a precursor to survival in the next decade. Analog mechanisms of running businesses are no longer sustainable nor likely to give confidence to customers, employees, stakeholders and shareholders. Measuring Digital A digital organization is characterized by the following Time to Customer Insight The Time to Customer Insight in a digital organization is the time it takes to collect, process, analyze information to determine the health of a customer, their satisfaction with current products and services, their unmet, possibly unstated needs and the impact that external market events might have on the customer. Time to Reaction Time to Reaction is the time taken to react to a customer insight through the introduction of a new product/service to solve an existing or a new problem or through better packaging of existing solutions to address otherwise existing problems. Time to Market Time to Market is the time taken to bring a new capability, product or service to market often as reaction to a customer or market insight or feedback Time to Iteration Time to Iteration is the time taken to solicit, gather, process, analyze customer feedback and effect a change in existing products or services or bring new products and services to market to address the customer feedback. Digital Organizations Digital organizations are characterized with minimal Time to Customer Insight, Time to Reaction, Time to Market, Time to Iteration and a constant effort and investment into further optimizing and minimizing these metrics. Digital organizations focus on the flow of information through the organization and use of the information to generate and deliver more value for the customers. Key Characteristics of Digital Organizations Instrumentation of Interfaces, Products, Systems, Applications, Processes A digital organization ensures</div>

...

Cancel

To Create Is Not Enough: How to Focus on Consumption - The AI Company - 0 views

www.autolearn.ai/...gh-how-to-focus-on-consumption

Artificial intelligence AI autolearn technology innovation digital strategy

shared by pintadachica on 18 Jan 19 - No Cached

pintadachica on 18 Jan 19

A pitfall in the path to innovation and disruption is the lop sided focus on "creation" and not enough focus on "consumption". Creation is the process of creating platforms, products, and solutions where as consumption focusses on ensuring that the created artifacts deliver the intended value. Too often enterprises get caught up in "creation" or enabling "creation" and lose sight of the fact that without consumption, anything they create is bound to be a failure. Creation & Consumption can not be Sequenced A misconception that often exists is that "if we build it, they will come" i.e creating the product and solution is enough and its existence will automatically lead to consumption and value generation for the customer. However, creation and consumption cannot be sequenced i.e. made a focus sequentially. Creation and consumption only succeed when they go hand in hand where tight, iterative loops ensure that the creation is informed by consumption trends and feedback and that consumption is also leveraging the latest creations. What Does A Lop-Sided Focus Look Like The top 3 signs of this lop-sided focus are as follows Focus on Building Platforms When the focus of the enterprise is building platforms and when customer value is only created when a developer leverages the platform to build a customer facing application, it often means that the effort invested in the platform has no ROI. When the focus is on platforms, application investment suffers and the platform builders get sidetracked with platform KPIs as opposed to business value KPIs. The platform builders might only focus on "Developer" satisfaction when ultimately, customer satisfaction matters for the business. Focus on Tools, Not on Solutions Another sign of lop-sided investment is a focus on tooling at the expense of solutions. Enterprise teams can often go overboard with building large libraries of tools and using the adoption of the tool as a metric of success. However, simil

<div class="cArrow"> </div><div class="cContentInner">A pitfall in the path to innovation and disruption is the lop sided focus on "creation" and not enough focus on "consumption". Creation is the process of creating platforms, products, and solutions where as consumption focusses on ensuring that the created artifacts deliver the intended value. Too often enterprises get caught up in "creation" or enabling "creation" and lose sight of the fact that without consumption, anything they create is bound to be a failure. Creation & Consumption can not be Sequenced A misconception that often exists is that "if we build it, they will come" i.e creating the product and solution is enough and its existence will automatically lead to consumption and value generation for the customer. However, creation and consumption cannot be sequenced i.e. made a focus sequentially. Creation and consumption only succeed when they go hand in hand where tight, iterative loops ensure that the creation is informed by consumption trends and feedback and that consumption is also leveraging the latest creations. What Does A Lop-Sided Focus Look Like The top 3 signs of this lop-sided focus are as follows Focus on Building Platforms When the focus of the enterprise is building platforms and when customer value is only created when a developer leverages the platform to build a customer facing application, it often means that the effort invested in the platform has no ROI. When the focus is on platforms, application investment suffers and the platform builders get sidetracked with platform KPIs as opposed to business value KPIs. The platform builders might only focus on "Developer" satisfaction when ultimately, customer satisfaction matters for the business. Focus on Tools, Not on Solutions Another sign of lop-sided investment is a focus on tooling at the expense of solutions. Enterprise teams can often go overboard with building large libraries of tools and using the adoption of the tool as a metric of success. However, simil</div>

...

Cancel

Seven Types of Artificial Intelligence Use In Dubai - Best UAE Digital Agency - 0 views

bestuaedigitalagency.com/-artificial-intelligence-dubai

blog blogging creative Marketing safety seo company digital wordpress AI

shared by bcm456 on 19 Jul 19 - No Cached

bcm456 on 19 Jul 19

Artificial Intelligence is presumably the most perplexing and astonishing manifestations of humankind yet. What's more, that is dismissing the way that the field remains to a great extent unexplored, which implies that each astonishing AI application that we see today speaks to only the tip of the AI chunk of ice, so to speak. While this reality may have been expressed and repeated on various occasions, it is still difficult to thoroughly gain viewpoint on the potential effect of AI later on. The purpose behind this is the progressive effect that AI is having on society, even at such a generally beginning period in its advancement.

<div class="cArrow"> </div><div class="cContentInner">Artificial Intelligence is presumably the most perplexing and astonishing manifestations of humankind yet. What's more, that is dismissing the way that the field remains to a great extent unexplored, which implies that each astonishing AI application that we see today speaks to only the tip of the AI chunk of ice, so to speak. While this reality may have been expressed and repeated on various occasions, it is still difficult to thoroughly gain viewpoint on the potential effect of AI later on. The purpose behind this is the progressive effect that AI is having on society, even at such a generally beginning period in its advancement.</div>

...

Cancel

Do you have a complete, comprehensive, single version of the truth about your business?... - 0 views

www.autolearn.ai/...-the-truth-about-your-business

autolearn business technology innovation tech digital strategy blockhain data

shared by pintadachica on 20 Dec 18 - No Cached

pintadachica on 20 Dec 18

One of the key milestones on the Digital Journey starting with a Digital Strategy, Digital Transformation and then sustaining on Digital Innovation is the point where the enterprise reaches a point of data maturity powered by a single, organization wide, consistent version of the truth including the state of the customers and the state of the business and the state of the employees. This point is critical as it becomes the launchpad for several, forward looking initiatives including Artificial Intelligence, ChatBots, Blockchain etc. "Complete" A Complete version of the truth ensures that the following criteria is met: Entity Pivot The key entities that need to be tracked to generate a complete, comprehensive version of the truth are the following Employee Employees, regardless of customer facing or not, need to be understood including where they excel vs. struggle and where their struggle impact the customer experience. Key information about employees that should be tracked is what the employees are working on, how productive they are and how often they introduce delay and errors in business processes. Business Business visibility requires that the enterprise be able to track key metrics such as customer lifetime value, customer attribution, customer acquisition cost and customer satisfaction. In addition, the stage of the customer ranging from prospect to commit to paying customer to abandoned needs to be tracked. In addition, the customer's quality of service and experience needs to be tracked and understood. Customer The most critical of the three is the understanding of the customer. Customer KPIs have a direct impact on and are completely impacted by the Business and Employee KPIs. It is extremely important to understand how customers are searching for, discovering, learning, understanding, using and continuing to use the product and services delivered by the enterprise. In addition, it is important to understand what capabilities drive what kin

<div class="cArrow"> </div><div class="cContentInner">One of the key milestones on the Digital Journey starting with a Digital Strategy, Digital Transformation and then sustaining on Digital Innovation is the point where the enterprise reaches a point of data maturity powered by a single, organization wide, consistent version of the truth including the state of the customers and the state of the business and the state of the employees. This point is critical as it becomes the launchpad for several, forward looking initiatives including Artificial Intelligence, ChatBots, Blockchain etc. "Complete" A Complete version of the truth ensures that the following criteria is met: Entity Pivot The key entities that need to be tracked to generate a complete, comprehensive version of the truth are the following Employee Employees, regardless of customer facing or not, need to be understood including where they excel vs. struggle and where their struggle impact the customer experience. Key information about employees that should be tracked is what the employees are working on, how productive they are and how often they introduce delay and errors in business processes. Business Business visibility requires that the enterprise be able to track key metrics such as customer lifetime value, customer attribution, customer acquisition cost and customer satisfaction. In addition, the stage of the customer ranging from prospect to commit to paying customer to abandoned needs to be tracked. In addition, the customer's quality of service and experience needs to be tracked and understood. Customer The most critical of the three is the understanding of the customer. Customer KPIs have a direct impact on and are completely impacted by the Business and Employee KPIs. It is extremely important to understand how customers are searching for, discovering, learning, understanding, using and continuing to use the product and services delivered by the enterprise. In addition, it is important to understand what capabilities drive what kin</div>

...

Cancel

Group items tagged

The Long & Short Of An AI Strategy - The AI Company - 0 views

Are you AI-First? - The AI Company - 0 views

Skateboarding, The AI Company and the Autolearn Boost - The AI Company - 0 views

Why Is Sentiment Such A Big Deal? - The AI Company - 0 views

5 signs why your digital transformation might be in trouble - The AI Company - 0 views

To be AI-first, move beyond managing data infrastructure - The AI Company - 0 views

Service Ticket AI - The AI Company - 0 views

Don't Reinvent The Wheel - The AI Company - 0 views

The LearnCloud Experience - The AI Company - 0 views

Our Products - The AI Company - 0 views

Future Proofing for Agility - The AI Company - 0 views

Going Through Digital Transformation. What's next? - The AI Company - 0 views

Not too late to jump on Blockchains - The AI Company - 0 views

Are you worried about the quality of your data? - The AI Company - 0 views

Can you transform into a tech company? - The AI Company - 0 views

Self Preservation: The Number One Hurdle To Innovation - The AI Company - 0 views

Are You Prepared To Be A Digital Organization - The AI Company - 0 views

To Create Is Not Enough: How to Focus on Consumption - The AI Company - 0 views

Seven Types of Artificial Intelligence Use In Dubai - Best UAE Digital Agency - 0 views

Do you have a complete, comprehensive, single version of the truth about your business?... - 0 views

Related searches