Tuesday, December 31, 2019

Happy New Year 2020

I just wanted to wish all my readers, collaborators and others a "Happy New Year" from the edge of  "lake Sinur". I wish you the best of new years and hope for the promise of technology making all of our lives better. I expect those involved with digital activities in 2019 to make a shift in the use of those technologies more strategically. If you continue reading my blog, you will see my take on how business and technology will take advantage of AI everywhere, Automation on fire and Customer Excellence advancing beyond simple interfacing and channels to true customer journeys  :)

Here are my early takes in 2020 with more to come in January on Process and Customer Excellence. 

Top Digital Trends
Top AI Trends
Top RPA Trends 

Wednesday, December 25, 2019

Art for 4Q 2019

The big delivery for me this quarter was the portrait of my late daughter Beth. While it was hard to complete, there was a healing effect that has helped me to move on to a near-normal life. I will always miss her and her brother Andy. I also did a fun piece that is of a stellar origin along with some fun fractals. If you would like to see more of my portfolio click here 

                                                    Elizabeth Jean Sinur 

                                                       Space Dot Mania 

                                                             Color Explosion 

                                                          Bright Wisp 

Tuesday, December 17, 2019

How an AI-powered Digital Assistant Increases Productivity in Business

Powered by artificial intelligence, digital assistants have emerged as groundbreaking tools that transform the way business professionals work. From translating documents and converting files to provide research data and benchmarks, digital assistants are playing an important part in increasing productivity. In the following case study, we show how an AI-powered digital assistant makes a difference in a goodly number of consultancies and large corporations. Let’s see how human augmentation is a “win-win”.
The translation of documents is a frequent, annoying and time-consuming task in business. Translating contracts, project presentations or training materials is costly when performed by external agencies and a waste of talent if done internally... and simply taking too much time. 
 In high-paced business environments, “wasting time” with translations prevents team members from focusing on the creative and analytical part of their work. Sure, you can copy-paste text elements to Google Translate, but the time necessary to put everything into a document in the right format and review it still takes significant time—too often leading to late working hours.
 Translating Microsoft Office documents was the triggering use case for the company’s founder when he decided to build a smart digital assistant—later named Brian. This assistant communicates via email, understands natural language, integrates multiple AI and digital services as well as selected data sources. He selects the best available translation service depending on the language pair. The integration with an OCR engine allows Brian to translate (native & scanned) PDF files as well as pictures. He is also able to translate files using client-specific terminology. 

Is the translation perfect, though? Of course not (yet), but it definitely saves a lot of time! The user experience is as simple as that: you write Brian an email saying, “Hi, please convert this file to Word and translate it from Chinese to English”. Within 3 minutes, the translated document is delivered while keeping the original formatting. Brian is an example of a tool that would not be feasible without AI technology and shows how helpful applied AI can be. With work delivered in just a few minutes that otherwise would take hours, and the assistant available 24/7, it seems to be the perfect complement to today’s business professionals. Language translation is just the tip of the iceberg for sure, but it demonstrates productivity gains.
Consultancies and corporations with thousands of employees are testing and using Brian already. The advantages of using this technology are quite obvious: saving employees’ time, reducing agency costs, accelerating processes and even making the workforce happier! For many staff members, the digital assistant is the first digital co-worker they work with—providing a glimpse of how amazing applied AI can be but also what the current limitations are.
 The lesson learned here is that human augmentation really works and leads to more cooperative digital assistants. Starting small with tedious tasks is a great strategy to test the benefits of smart digital assistants that leverage AI.
This case study was provided by www.askbrian.ai

Tuesday, December 10, 2019

Top 10 AI Trends for 2020

2020 promises to be a tipping point year for automation benefits and an experimental year for customer or employee experiences. AI is initiating a change in the way both automation and experiences are constituted and delivered. The end result will change the way people interact with technology and organizations. Work and workforces will be changing starting in 2020 and continuing for the next five years. The future looks promising after several years of experimenting with AI.

It's not all fantastic and there will be fakes and failures. In fact, there will be high profile fails, but they are unlikely to cause another AI Winter. Even if the fails can be avoided there are significant challenges with explainability and ethical issues. Guidance will have to be applied with wisdom through goal-driven approaches that have sensible guardrails. It's not a cakewalk, but it will be an emerging careful AI journey for many. Here are my top ten AI trends for 2020

Data Will Continue to Sharpen AI

New data methodologies and algorithmic challenges will be a major factor in getting AI to be more on point in more contexts than ever. The challenges for getting the amount and proper kinds of data to train AI will continue, but organizations will find ways to leverage already synthesized data. They will build on and extend existing data sources while cleaning up some of their own legacy sources. Data will continue to be mined and leveraged with and for AI.

AI Will Shape Customer and Employee Experiences

AI will be leveraged to create the customer and employee experiences of the future. Organizations will morph away or augment chatbots to become real digital assistants. AI will help understand and interpret the real-data based customer and employee journeys. The vision of really helpful customer journeys that span departmental and company boundaries will be turned into a reality with the help of AI. AI will leverage machine learning and deep learning to identify improvement opportunities to act on or consider. Every touchpoint can be gainfully watched and mined.

Full Life Cycle Iteration Will be the Target

Improvement cycles require sensing, orienting, deciding and acting in an interactive or iterative fashion. Pipelines of learning will be funneled into AI discovered opportunities and threats for organizations to consider and eventually anticipate. Workload balances can be influenced by the learnings from AI in a speedy fashion. Iterations of improvements can be watched and compared for even more enhanced learnings.

Sense & Understand Will Progress Quickly

Voice command will be commonplace and combined with more sophisticated Natural Language Processing (NLP). AI will understand and respond more intelligently over time and make some big leaps in 2020. This will improve the lives of individuals in various roles. AI will be baked into chips allowing for the better recognition of objects, objects in motion and objects in context for smarter production lines, cities, and organizational processes.

Conversational "Bot Buddies" Will Emerge

AI will start to tackle harder problems faster than people can. As workers, customers, and people in various roles become comfortable in the reliability of these AI bots, they will become coworkers and even trusted advisors. These trustworthy bots might even become reliable allies for creating desirable outcomes. Visible success stories and examples will start to emerge in 2020.

AI Will Be Integrated in Everything

Not only AI is baked into chips, but it will also be integrated into every software category that exits today. AI will integrate or cooperate with algorithms often, so they will no longer be siloed away from each other. AI will be integrated into platforms to perform security functions and tasks early and often. Many software categories will exhibit ad growing IQs starting in 2020 becoming ubiquitous in five years down the road.

AI Will Be Entering Industry 4.0, Supply and Value Chains

We will see more modern supply and value chains emerge in 2020. AI will help create the ever-elusive management cockpit for organizations or individuals engaged in supply or value chains.  AI will provide valuable insights to ease previously tedious tasks like product redirects. Eventually, AI will help configure and create products dynamically and manage them to completion and eventual destination. 

Smart Super Infrastructures Will Gain Momentum

These Digitial Business Platforms(DBP) can either be business-focused or technically focused, but few are both. These super infrastructures are built to securely combine various aspects of digital business or technology streams. They often include a significant set of AI or analytic feature, they seamlessly integrate multiple data types and speeds, manage work to completion, and support monitoring for improvements. Examples of business DBPs include Salesforce, SAP, and Oracle. Examples of technical DBPs include Amazon, Microsoft, IBM, and Google.

AI Will Engender More Predictive Behaviors

As the next decade rolls out, a real-time reaction will not be good enough. Organizations will have to grow to anticipate putting a premium on predictive capabilities and behaviors. AI will participate in monitoring existing channels and integrating the sensing of events and patterns to the predictive models and algorithms. Savvy organizations will have identified key triggers and have responses can be pulled off the shelf. Of course, there are always "black swan: situations, but the combination of AI and algorithms can speed the coping mechanisms for even those situations.

AI Will Supercharge Knowledge Management

AI with the help of NLP and data ontologies, content can be turned into knowledge. This knowledge, in turn, can be leveraged through the presentation at the right time of notifications, advice, videos, and t bot buddies that can interpret conditions to pull the proper knowledge resource.

Net; Net: 

2020 will be a make or break year for AI delivering more automation results. Smarter RPA bots, straight-through processing, and helpful smart assistants will accelerate automation benefits. This will allow organizations to weather any downturn. 2020 is also a year for applying AI to customer and excellence funded by some of the automation benefits that AI brings. Smart organizations will take a portion of the savings and use it as a smart investment fund.

Tuesday, December 3, 2019

Top 5 Digital Trends for 2020

2020 is a tipping point year for digital. The executives have tasted digital benefits in a tactical fashion, for the most part, and see the promise. Now top management is looking to use digital strategically to look for opportunities or threats in a more proactive manner. In some cases, executives will want their organization to be the disruptor rather than being reactively disrupted. This is my best shot at predicting the likely trends based on business and technical predictions enumerated below.

Business World

The world of business is in a state of flux and flex like it has never been before. We can see it all around us with threats of economic and real war. Stability is a concept that seems to be fading at an ever-increasing rate of speed. Organizations will be moving at high speed and yet ready for a variety of conditional changes that can be enabled by leveraging more digital listening posts and making decision opportunities from big, fast and dark data. The agility provided by digital capabilities will be faster to respond to directional turning and tuning. Digital practice becomes digital momentum in 2020 by leveraging digital's ability to intercept, expect and react to change.

Technical World 

Digital technologies have been used tactically to increase automation, speed, and agility in an ever-increasing manner over the past few years in an isolated fashion for the most part. New combinations of complementary digital technologies will be leveraged to keep pace with increasing demands from the need for better business outcomes. A stronger, more secure, and faster internet will enable a good portion of the 50% of the unserved world to join the internet and for more business to be completed securely there. Maybe "OK Boomer" will fix this one problem :)

Top Digital Trends

1.  Anticipation will be the crown jewel of digital desire by putting a premium on intelligent sensing, pattern recognition, decisions, and appropriate actions. This means that autonomous outposts will be feeding in their observations to match strategic plans that outline expected and unexpected opportunities or threats. Digital plays well here with advanced predictive analytics, decision models, AI, data mining, citizen development, corporate performance, and bots.

2.  Since 70% of customers will now leave you if they are not treated properly, an emerging balance between customer goals and organizational goals will have to be established and tuned frequently. While the elusive personalization goal will not be attained anytime soon, customer excellence will now be a major theme for organizations going forward. This excellence will go beyond simple channel customization and ease of use efforts to identifying the real customer journey that breaks down your functional silos and how your organization can contribute it's part to the journey even if other organizations are involved. Digital plays here too with customer journey mapping, customer journey mining, NLP, emotive AI, smart digital assistants, and knowledge accelerators for employees interacting with customers. Maybe customers will believe that organizations have their best interests at heart.

3.  Automation has been and will still be a major deliverable of digital to make the lives of customers, employees, and managers better. While the elusive straight-through processing ideal may be closer, the collaboration and cooperation of automation, machines, autonomous bots, and people will be a major challenge and benefit of digital in the future. The digital play here is RPA, low code, citizen development, AI, mining, processes, and analytics.

4.  There is and will continue to be a huge mismatch on jobs, skills, and locations. The markets, let alone organizations, can't keep up with the level of skills needed to become and stay on top of digital opportunities. Digital can lend a hand in capturing knowledge, expertise and effective practices. By leveraging NLP, knowledge ontologies, AI, data/process mining, video, digital assistants, and knowledge accelerators, organizations can narrow the skills gaps over time.

5.  The aggregation of these many digital technologies poses a challenge for all organizations otherwise new technology silos will emerge. As all of these digital technologies will need to allow organizations to complete businesses securely across clouds, new digital platforms are emerging with smart security plus built-in digital combinations that enable the trends aforementioned. There will also be the emergence of specialty digital business platforms by vertical industry plus horizontal business functions like sales and field management. There will also be bottom-up technology combinations that will serve business needs like digital platforms for intelligent automation, collaboration, and content capture/management.

Net; Net:

Digital is gaining speed and momentum and is likely to continue to even in established organizations with or without new business models. 2020 will be a key year for digital to be tested in more strategic ways. From unified decision making to human augmentation with anticipation, digital will be assisting us more and more. Heck, it is even helping us with our legacy portfolios by surrounding, extending them and rewriting them fast with agility. The challenge for us is to think strategically and not grab tactical benefits which are real indeed.

Monday, November 25, 2019

Everything Thankful

Sometimes being thankful isn't easy, but you know you will be a better person for it. This year has had its challenges for me and my family. We lost our youngest daughter to a fentanyl-laced sleeping pill that a friend gave her and we lost our loving dog, Maggie Mae. Still, God is good to us by introducing a new grandson to our world. We welcomed Jackson Thomas Sinur to our family. Yet there are so many things to be thankful for these days. Just let me highlight a few that are meaningful to me.

The Special Years We Had with Beth Sinur Who Had the Biggest Heart

The Newest Love of Our Family Jackson Thomas Sinur

Our Loving Maggie Mae Who Loved Unconditionally 

I am so thankful for:

Life and health that allows us to still be active and vibrant

My ever-patient wife, Sherry. Great adult children in Andy(RIP), Melissa, Bryon, Dave, Emily, Steve & Beth(RIP). Fantastic grandkids in Keegan, Karson, Xander, Gabriella, Jackson, Hope, Kale, Nolan & Amanda. Finally, a mom who keeps it going at 92 living in northern Wisconsin. 

The local music community that allows us to hang. Especially Susan Alexander, Greg Chaison, Ethan Foxx, Rick Greenly, Moe Mustafa, Heath Underwood, Bob Desiderio, 
Jimi Taft, Donnie Crist, Dan Seethaler, James Graves & Jim Nugent

My friends all over the world that stay in contact and keep me up to date with their adventures. Especially Adrian Bowles, Mark McGregor, Ed Peters, Jim Duggan, Ken Kleinberg, Benoit Lheureux, Toby Bell, Bob Weerts, and Mike West

My customers, work associates and followers that keep me honest

The gifts that God gave me and continues to allow me to grow

Freedom to worship and to choose. Faith Bible Church & great leadership in Dan Lind. 

Family and friends in glory today especially Dad, Andy and Beth Sinur. 

Net; Net:

We all have so much to be thankful for these days if we just take a moment to meditate on thankfulness awhile. A habit I'm trying to employ daily. 

Monday, November 18, 2019

Combining Image, AI & Analytics For Safety and Cost Reasons

The steel teeth on mining excavation equipment like rope shovels and front end loaders are wear items that must be replaced as part of regular maintenance. During normal operation, the connection that affixes a tooth to the shovel or loader bucket occasionally fails, causing tooth detachment. A detached tooth presents a serious hazard if it enters the haulage cycle and makes its way into a crushing unit, where it may become stuck and require the dangerous task of manual removal. Furthermore, wayward teeth cause substantial lost time and production due to jammed crushers and damage to downstream processing equipment. Therefore, it is critical to detect when a shovel tooth goes missing as soon as possible so that preventative action may be taken.

The Problem:

Current methods use equipment mounted cameras and computer vision techniques to generate real-time automated alerts in the event of a missing tooth. While these methods can identify missing teeth with good sensitivity, they produce an unacceptable number of false alarms, which causes equipment operators to ignore the alerts entirely. In some cases, a false positive rate (FPR) of 25% has been observed. Due to the relative infrequency of broken shovel teeth, the false discovery rate (FPR) may be greater than 99%.

There are several challenges associated with the real-time detection of broken shovel teeth. For example, the quality of captured images is compromised by a variety of factors. Dusty operating conditions and variations in lighting, location, and orientation of the shovel bucket, and background composition can make the shovel teeth difficult to distinguish from the material behind it. Furthermore, the biting edge of the shovel bucket is often partially or completely obscured by mined material during operation, which can cause a failure detection algorithm to produce undesirable results. In addition to image quality challenges, the problem itself does not fall neatly into the paradigm of traditional object detection because the target object is an anomalous nuance of the image subject.

The Solution:

A 2-stage approach was selected to address these challenges: 1) row-of-teeth detection and 2) equipment status classification. The location and orientation of the shovel teeth within the images captured by shovel-mounted cameras are highly variable. The purpose of stage 1 in the approach is to isolate relevant information from the image and disregard the rest. This step both normalizes and reduces the size of the images for downstream processing. This technique has been used extensively in real-time facial detection. Stage 2 of the approach performs a binary classification on the detected region from a stage 1. An optimization procedure was applied that aligns sequences by warping them in temporal space such that the distance between signals is minimized. This alignment enables matching of time series based on underlying patterns, irrespective of non-linear temporal variations.

The Result:

This methodology could be used to improve current industry methods, which produce false alarms for 25% of image captures. There are, however, some important points of consideration in the direction of developing a robust, deployable implementation of this methodology.

Net; Net:

New combinations of machine learning methods, even borrowed from different domains, can be leveraged for impressive results. This is not likely without cross-pollination of data science techniques that are likely to come from outside your organization. 

This case study was provided by World Wide Technology (WWT); a leading provider of system integration and global supply chain solutions  https://www.wwt.com/

Monday, November 11, 2019

What Are Folks Reading These Days?

People barely have time to read these days, so it's important to understand what they are spending their precious time on for sure. In order to help with that task, here are some useful charts and links to help others set some reading priorities. I would appreciate any ideas for new post topics if you have a hot button or two. A bit of background here for you, if you have the time or otherwise skip to the charts.

Since I left Gartner in 2013, I have written over 500 blogs that were about the digital world we are interacting with, developing or planning to develop. I have a pie chart showing those posts that are most popular over that period of time. I also have a chart showing where in the world most of the activity comes from other than the U.S. that dominates the numbers with 70 percent of the activity (defined as "hit count"). In addition to my own blog, I have been a writer, presenter, and researcher for hundreds of organizations after my Gartner life. Starting in 2019, I have also become a Forbes contributor on the topic of AI and Big Data. I have also included a chart for the hottest activity.

                                        LINKS TO THE GREATEST HITS


                      LINKS TO RECENT TOP HITS




Again, if you have any hot button ideas for blog posts, please reach out.


Tuesday, November 5, 2019

A Digital Assist for Active Shooter Incidents

If you have not heard of active shooter incidents recently, you have been living under a rock. Imagine what 2D floor plans and 3D models can do to assist these situations. Even without intelligent digital assistants, law enforcement can get a better handle on the structure involved with any particular incident. While these digital models are helpful, they are difficult and time consuming to create. This case study is about the evolving scanning, creation, and leverage of visual digital models on a large scale.

The Problem:

Usually, we think of scanning on a small scale in and around smaller sized products. Imagine a much larger scale like all the K-12 schools in the US? According to scanning professionals, to map just the K-12   schools in the U.S., it would take a scanning team, scanning 100,000 square feet per day, seven days a week, a total of 188 years to complete. This estimate addresses only the public schools and does not address any of the many private schools, let alone the post-secondary school facilities.
Robert W. Meyers J.D. from the Entropy Group LLC says ““Active shooter incidents are a growing concerns in the United States, with death tolls, most predominantly in schools, rapidly rising and law enforcement resources stretched beyond breaking point. With the unpredictability of these incidents, both in scale and location, the team at Entropy Group LLC has been working alongside law enforcement and the US attorneys nationwide in order to compress response times, by utilizing 2D floor plans and 3D models.

The Solution:

When confronted with the magnitude of the effort it was immediately obvious to Entropy Group   that we needed to join forces with 3D mobile mapping and monitoring technology specialists, GeoSLAM because their ZEB REVO line of scanners provide the necessary accuracy and are much more time-efficient than other laser scanner technologies. To finalize the proof of the efficacy of the patent filing, Entropy Group LLC recently completed a simulated active shooter incident where six law enforcement officers were tested by responding to a fictitious scenario. Officers were provided a detailed floorplan of the two-building which is currently used as a church and parochial school facility. The structure is quite complex with many classrooms, counseling rooms, worship sanctuary, multi-media studios, cafĂ© area, and church offices.

The Results:

The results of the exercise indicate that officers which have access to the 2D floor plans ahead of time, improve their situational awareness, their confidence in responding to a facility that they have never been to previously, by gaining “facility familiarity” thorough review of floor plans and other data prior to their response. Additionally, response times were documented to decrease by up to 21%. This improvement in response will directly result in fewer deaths and casualties. GeoSlam claims to deliver at least a 10X time reduction in the scanning process.

Net; Net:

The ability to scan large spaces and facilities effectively and efficiently will start to deliver more successful digital implementations including city planning, real estate inventory and another large scale geo problems.

Entropy Group LLC https://entropygroup.net/

Entropy Group LLC is a full-service Forensics and Security Consultancy firm providing services for Executive Protection, Accident Reconstruction, Security Threat Assessments, Building Information Modelling, Security Design Reviews, Security Program Reviews / Audits, Litigation Support, Pre-Travel Security Front Team Assessments, and Access Control Assessments.

Designed for surveyors, engineers and geospatial professionals, and serving the surveying, engineering, mining, forestry, facilities, and asset management sectors, GeoSLAM technology is used globally by anyone needing to create the digital twin of their world, quickly and accurately. GeoSLAM provides geospatial hardware and software solutions provide rapid and easy mapping and highly-accurate monitoring solutions. 

Thursday, October 17, 2019

Fujitsu Bolsters It’s (OCA) Partner Alliance with Strong Digital Vision

Fujitsu relaunched its OCA conference with a new digital vision, strong new products and a commitment for strong partner support. The digital vision was outlined with defining an intelligent content journey starting with powerful new scanners sending the highest quality content to the cloud for categorization, preparation tasks and onto legacy applications or processes thus completing the content journey. This is over and above the typical enterprise content management archiving capabilities available for decades.

The intelligent Journey Is now being bolstered by two new powerful scanners that help the OCA partners reach into the mid-market to add to their Fujitsu’s powerful presence in the enterprise market with a 53% market share worldwide. I observed some of the heavy-duty scanners in action with incredible rates of accurate scanning speeds and the ability to categorize and capture key data elements for further processing options. The first product introduction was fi-7300NX. The second was the fi-800R which supports thick documents in a one-handed push-push mode that has a miniature footprint. 

Fujitsu sees that the future is not just hardware, so it’s linking up to the cloud to allow a content push approach or a process / application pull support. This means that the content of all kinds will be leveraged with smart cloud platforms. Fujitsu provides a super-secure channel for content entry with a one-touch approach, combined with RPA and process vendors, to support straight-through processing. To that end, Fujitsu invited content management, RPA, and process vendors to set up at the OCA conference. Fujitsu is stepping up its support of partners to reach new markets and supporting new digital uses to demonstrate that data capture is still relevant.

Microsoft, a long-time partner, was invited to describe their boost to structured content and unstructured forms of big data by adding an Azure platform growing more intelligent all the time. Ian Story explained the progress Microsoft was attaining to add more intelligence to the point of replicating human function including the senses.

Fujitsu also thinks that RPA will be essential on the content journey and gathered a panel of RPA/Process vendors to contribute their real-world experience with the combination of content and RPA. I was fortunate t moderate the panel and pull stories about speedy ROI and bot momentum. The partners were also encouraged to link up with RPA to extend the content journey beyond just the capture moment. 

Additional Reading on RPA:

Process n RPA
Future of RPA
Top 5 RPA On Ramps

Net; Net:

Capture is the first step in the journey of content. Fujitsu is dominating the enterprise capture market, but will extend its lead by RPA, AI and process to support the extension of that journey. At the same time the OCA partners will be equipped with new midmarket opportunities and support from Fujitsu.   

Friday, October 4, 2019

AI & Big Data: a Lethal Combo

Big data, unstructured or structured, fast or slow, in multiple contexts or one is a beast to manage. Big data is growing fast fueled by the democratization of data and the IoT environment. Often organizations simply control what they know they get results from and then store the rest for future leverage. In fact, most organizations use less than 20% of their data, leaving the remaining 80%, and the insights it contains, to be left outside to the operational and decision-making Processes.  Imagine if you used only 20% of any service, you paid for every month and ignored the other 80%!  This is exactly what we are doing with data.  Fortunately, there is hope as this is where Big Data can start to rely on AI and engage in a “cycle of leverage”. Presently, the interaction between AI and Big Data is in the early stages, and organizations are discovering helpful methods, techniques, and technologies to achieve meaningful results. Typically these efforts are neither architected nor managed holistically. Our work has shown there is an emerging “Cycle of Big Data” that we and would like to describe and share with you where we see AI can help. 

Big Data Cycle

The “Big Data Cycle” is the typical set of functional activities that surround the capture, storage, and consumption of big data. Big data is defined as a field that treats ways to manage, analyze and systematically extract information from, or otherwise deal with, data sets that are too large and complex to be managed with traditional software.  The “Cycle” is, in short, the process of leveraging big data into desired outcomes. Typically the cycle flows in a left to right fashion with iteration.

(Data-> Trigger->Pattern->Context->Decision-> Action-> Outcome->Feedback->Adjustments).

Data Management

Data management is a process that includes acquiring, validating, storing, protecting, and processing the required data to ensure the accessibility, reliability, and timeliness of the data for various users. Today this is a more complicated process due to the increase of speed of data (near real-time) and the increased complexity of the data resources (text, voice, images, and videos).  This situation has had the effect of outstripping the processing capabilities of both humans and traditional computing systems.

AI can assist here in several ways, including assisting with hyper-personalization by leveraging machine learning and profiles that can learn and adapt. AI can also help in the recognition of knowledge from streams of data through NLP categorization and relationship capture. AI can watch static or in motion images to find and manage like knowledge. Not only can AI help recognize and learn by watching human system or machine interactions, but it can also do it in less than an instant. This can be performed either at the edge of the cloud or through an IoT Network.  AI combined with other algorithms can help in finding “black swan events” that can be used to update strategies.

Pattern Management

Organizations need to keep their pulse on incoming signals and events to stay in tune with the current state of the world, industries, markets, customers, and other constituents while sifting out distracting noise events. While savvy organizations that employ strategy planning to actively look for specific patterns of threat and opportunity, unfortunately, most organizations are reactive suffering at the whims of events. Both types of organizations should be continually looking for “patterns of interest” from which to make decisions or to initiate actions that are already defined and stored for execution.

AI can help by recognizing both expected and unexpected signals, events, and patterns to recognize anomalies that might warrant attention potentially.  When combined with analytics, AI can learn and expose the potential for additional responses.  AI also recognizes and learns adaptations for patterns, decision opportunities, and the need for further actions. In some cases, automation opportunities can be identified to deliver faster and higher quality results.  

Context Management

The understanding of data can often change with the context from which it is viewed and the outcome for which it can be leveraged. The “subject” of data can mean something slightly or significantly different in one context versus another.
Understanding the context is as important as understanding the data itself. Information about the context and the interaction of its contents (aka worlds) is essential to capture and maintain.  This allows for a classification of data in context and especially in relation to other contexts as big data sources may contain many contexts and relationships within it.

AI can assist the dynamic computer processes that use “subjects” of data in one context (industry, market, process or application) to point to data resident in a separate (industry, market, process or application) that also contains the same subject.  AI can learn the subtle differences and context-specific nuances to track the evolution of the data’s meaning in multiple contexts, whether it is “interacting” or not. This is particularly useful in understanding conversations and human interactions with NLP as interpretation grids often differ.

Decision Management

Decision management (aka, EDM) has all the aspects of designing, building and managing the automated decision-making systems that an organization uses to manage its decision making processes both internally as well as any interactions with outside parties such as customers, suppliers, vendors, and communities. The impact of decision management is felt in how organizations run their business for the goals of efficiency and effectiveness. Organizations depend on descriptive, prescriptive, and predictive analytics leveraging big data to provide the fuel that drives this environment.

AI can play a crucial role in supercharging knowledge and expertise utilization in a continually evolving and changing world. AI can also help scale key resources by leveraging an ever-growing base of big data at the speed of business that is ever-increasing while supporting today's operational requirements and ensuring its application to the ever-growing user expectations. Specifically, increasing the use of AI in human interactions will be a significant contribution to improving customer experiences and increasing the speed of resolution regarding customer issues.  AI can also suggest where to look for decision opportunities, model decisions, and their outcomes, and actively monitor performance against key performance indicators. 

Action Management

Action management involves planning and organizing the desired proactive or reactive actions and work activities of all humans, processes, bots applications, and devices employed by the organization. It includes managing, coordinating, and orchestrating tasks, developing project plans, monitoring performance, and achieving desired outcomes represented by goals in accordance with approved principles and agreed parameters. The logging of these actions also feeds the big data pools for further analysis and potential optimizations or increased freedom levels through goal adjustments.

AI can help by associating proper actions in the direction of the previous decision steps. It may mean selecting an inventoried action, changing some of the rules/parameters of an inventoried action or suggest the creation of new actions not available in the current inventory. AI can be embedded in any of the steps or detailed tasks that are performed in the selected actions. AI can monitor the actions and report the outcomes to management.  AI, along with algorithms, can pre-test and suggested changed action before deployment, thus ensuring the desired outcome with be achieved.

Goal Management

Goal management is the process of defining and tracking goals to provide guidance and direction, help evaluate performance and give feedback to all resources (humans, processes, applications, bots, and managers) for performance improvement. This also includes the “people-pleasing” and optimization arenas.  As organizations move to implement increased employee empowerment, edge computing, and dynamic bots, the importance of self-directed goal attainment increases. New freedom levels that ratchet-up up autonomy include a heightened focus on goal attainment and monitoring..

AI can help guide autonomous humans, bots, process snippets, apps, and flexible infrastructures through the automatic adjustment of goals that take advantage of edge conditions or “just in time learning” within the guardrails of constraints and rules. All of these resources can receive new guidance from real-time learning AI capabilities either built-in or “externally called” depending on the feedback loops and logs contributing to the big data pools.

Risk Management

Risk management is the identification, evaluation, and prioritization of risks mitigated by the coordinated and intelligent application of resources to minimize, monitor, mitigate, and control the impact of threats.  This will require tapping into the big data pool to continually monitor events and identify emerging threats and opportunities.

AI can help organizations recognize the emergence of situations that might require a response and enable mitigation responses.  Key patterns and anomalies can be recognized in events, patterns, logs of systems, and human feedback (including social networks) for potential or emerging risks. Additionally, any attacks or issues that exist within the perimeter, such as, cultural behavior, can be detected early and the development of necessary defenses enabled.

Net; Net:

Big Data development and management is a core capability that an organization needs to master in order to either become or remain competitive. It is clear to us that AI is the engine that will create value from the ever-increasing Big Data resource.   Big Data has a critical role to play over time as we journey deeper into the new digital world.  AI can handle speed, volume, and change much better than any technology that we have worked with, and this is just what Big Data needs!

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This post is a collaboration with Dr. Edward Peters 

Edward M.L. Peters, Ph.D. is an award-winning technology entrepreneur and executive. He is the founder and CEO of Data Discovery Sciences, an intelligent automation services firm located in Dallas, TX.   As an author and media commentator,  Dr. Peters is a frequent contributor on Fox Business Radio and has published articles in  The Financial Times, Forbes, IDB,  and  The Hill. Contact- epeters@datadiscoverysciences.com