Emerging Technologies

As if competition was not challenging enough, now we are competing within and throughout our organizations. All must exercise caution given the increasingly high level of internal competition that many organizations have begun to experience.  The information technology (IT) part of the organization no longer owns technology.  Today, they may not even be called upon to support it!  Some internal business components of the organization have begun to research and analyze emerging technologies and build their business case for action, funds it and implements it.  Much of the time the implementation is on an external cloud by a technology vendor.  More often then not, that vendor introduced the emerging technology to that internal business component and shows the value in a case study or white paper.

INSIGHT: In a report, Accenture stated that, “Leading in this new decade means working to redefine the intersection between people and technology.”  Clearly every part of today’s organizations must do this internally as well as for their external customers as well as other stakeholders.

Internal competition around the use of emerging technologies given their potential implications both positive and negative will likely continue to grow rapidly at least through 2025. With that, management at all levels need to keep this in mind as the challenges for growth between now and 2025 are not likely to decrease.  They will more than likely increase and an accelerating path ahead. The best approach for management going forward is to seek an objective source of information about the technologies that hold the most promise to their organization. Being cognizant of these and their potential implications is half the battle that we are all most likely to experience.  We should repeatedly answer a few questions over the next few years. Are you competing internally? What is your personal strategy to win the technology race that we have entered? How prepared are we with the necessary knowledge about the emerging technology? These are three very important questions we must all consider and had better have answers to!

Autonomous systems (AS) are another accelerating segment of the emerging technology marketplace in the next few years. The majority of the information under this heading relates to vehicles, but has expanded beyond that! Estimates of the autonomous vehicle (sometimes referred to as self-driving vehicle) market is projected to grow to between 30% and 35% compound annual growth rate (CAGR) from 2019 to 2025.  This would put the 2025 global market value of between $10 and $13 billion USD.

The overall autonomous vehicle market takes advantage of multiple emerging technologies and heavily relies on GPS, artificial intelligence, 3D imaging, LIDAR and RADAR, and advanced sensor technology to properly operate and guide the vehicles. Consider the increased complexity of programs and projects that have to integrate all those technologies and has life and safety at risk!

It should also be considered that this subject matter also includes an interesting development around digital communications networks. Autonomous Networks is considered by many as the ‘Future of Networking.’ It is the combination and integration of software-defined networks and automated network management capabilities. These capabilities completely integrate and automate self-operating digital communications networks.  Autonomous Networks (AN) is a group of networks under mutual administration that share/coordinate the same routing methodologies, techniques and other functional aspects to produce a seamless operating environment.  AN uses an internal gateway protocol and common metrics to properly and efficiently route packets within the AN and typically uses an external gateway protocol to interoperate with and route packets to other networks and or systems.

 It is also worth mentioning that another AS segment exists.  It is autonomous buildings sometimes referred to as SMART buildings.  This specific segment is expected to grow with a CAGR of between 30% and 35% and top $20 billion by 2025. There are some estimates that put this market value over $100 billion by that year. One has to wonder where we will get all the construction workers and technical staff for this much activity. This will likely create more projects with a shortage of properly skilled resources!

Once again, another emerging technology, Autonomous Systems (et-all), has a huge potential that is now dawning and rapidly becoming a much larger part of today’s environment with significant impact on nearly all multiple parts of the daily lives of all of us.  Like the other emerging technologies covered under this blog, it deserves regular monitoring from now until it becomes common throughout the world.

The relationship between the topics of machine learning (ML) and artificial intelligence (AI) is highly discussed as of late and for good reason.  If you examine the research, whitepapers and articles, the applications space for these two emerging technology areas seem nearly limitless. Some applications seek to turn silicon into experts while other simply want to eliminate the common mistakes all of us make from time to time. Two years ago, technology analysts at Gartner published a piece titled, “How to build a business case for Artificial Intelligence.”  If you are working on an AI or ML project, the article is well worth reading.

LINK: https://www.gartner.com/smarterwithgartner/how-to-build-a-business-case-for-artificial-intelligence/

Recently a rather innocent and quite interesting question was posed to a group of AI/ML practitioners. Or so I thought!  Is ML just a subset of AI or is it a separate and distinct area of technology, all though related? A rather spirited debate ensued and no mutually agreed upon answer was reached. So, at this point since there are separate market research reports, we should probably follow their lead.  A study conducted by multiple industry analysts concluded that the global artificial intelligence market has a projected compound annual growth rate of slightly over 35% to 46% from 2019 to 2025.  That growth rate would create a global market worth over $390 billion USD by 2025 at the high-end.  In a separate estimate, the global machine learning market was projected to have a CAGR between 30% and 43% from 2019 to 2025.  That growth rate would create a ML global market worth around $126 billion USD by their 2025 time-estimate-box.  Once again keeping with the common theme of emerging technologies, those are clearly a robust market growths resulting in a large amount of money.

The value of an intelligent system (IS=ML+AI) that learns on its own and can eliminate even a fraction of common errors would be significant. However, along with all the potential value there is a dark-side.  There seems to be a growing amount of fear circling AI and ML.  So call it the fear of the unknown around machine learning and artificial intelligence.  In my recent PMI webinar on “Addressing the Tech Savvy Board” one slide covered: Protesters demonstrated against dangers in development of artificial intelligence and robots. They chanted ‘HUMANS are the FUTURE’ and had signs that said ‘the future is us – STOP ROBOTS!’  There have been reports of protests around the AI and ML subject matter. There are a number of concerns and risks about the growing capabilities of AI and ML as well as many other emerging technologies that we should all monitor and keep ourselves as professionals up-to-date!

Technology is continuously in motion and that Is indeed the case when it comes to the Internet of Things (IoT) or as some have called it, the Internet of Everything!  There is good reason for their massaging the title.  A recent study suggested that this year, 2020, the global IoT market value is projected to reach over $915 billion USD. Yes, just shy of a trillion $$$. With a double-digit compound annual growth rate, the IoT market is projected to reach $1.9 trillion in 2028. That is a huge amount of money.

When you think about all the work involved in the design, development, marketing, sales, installation, integration, and service involved in the global IoT market today, and in the next few years there is an abundance of work involving IoT.  Now we must add to that work, all the efforts to add security to protect all those IoT devices and the data they produce.  There are projections that the global use of IoT devices will likely top 40 billion units worldwide and all those devices will be generating nearly 80 zettabytes (or 80 times 1,000,000,000,000,000,000,000 bytes) of data in 2025.  Since we are talking about data, we must consider last week’s blog about the collection, storage and analysis of all that data, as well as the effort to take actions based on the results of that data analysis.

Here are a few weird IoT devises that I thought might be good or at least humorous to mention to illustrate just how broad of a range the devices have.  First and perhaps my favorite is a ‘Touch-screen Wine Bottle.’ When activated, it provides a wide range of information about the contents of that bottle. Think about applying that to pharmaceuticals! Secondly, is a ‘Dog Alert’ that contacts your smartwatch/smartphone and tells you your dog is barking.  Once alerted, you can go to your home-cams and look inside your home and see what is going on and talk to your dog if you would like.  One individual told me they were working to determine if the dog’s bark suggested if the dog was happy or upset. So here is the third of my top three.  An IoT toilet, plays music, has a soft light, opens when you approach the toilet, has a heated seat and you ASK it to flush. Ok, now one has to wonder, what data that collects, where it goes and in the United States if that is covered by HIPAA regulations.

I am wondering what is next? What are the hot areas of IoT applications in our specific domain(s) or our domains of interest? As we all move into the connected future of the world, innovation and creativity is the limiting factor in the products and services around the IoT explosion and all the data they produce and how that will be used.

Today, an organization’s data assets are in continuous motion. It has been that way for decades with no end in sight.  The size of their data asset inventory is increasing as is their volume and value! As data increases in importance and value, it has caught the attention of many organizations. Some seek to maximize this asset and have appointed a Chief Data Officer (CDO) who is charged with that task.

INSIGHT: The IDC’s study titled, “The Digital Universe in 2020” estimated that in 2020, there will be an estimated 40 trillion gigabytes of data on that equals 40 zettabytes of data.

It is interesting to see metrics like in 2020, data is expected to grow at a rate of 1.7 megabytes per second for every person. Web users are expected to generate a whopping 2.5 quintillion bytes of data each and every day!  It is no wonder that industry analysts believe that the big data analytics market will grow around 20%, another double-digit compound annual growth rate (CAGR), topping $100 billion in 2023 by one estimate. One of the hotter areas is the combination of big data, analytics and artificial intelligence (AI).  Survey results published in 2019 stated that slightly over 97% of organizations are beginning to invest in the combination of big data analytics and AI. – Another example of a common theme of this blog and the vast majority of the research, analysis and briefings I am involved with as of late.

INSIGHT:  Many believe that overall cyber defenses as well as data specific security measures have added complexity and decreased visibility into the expanding world of organizational data analytics!

It is no wonder that data analyst is a hot profession now days.  Recently, the World Economic Forum (WEF) estimated that by 2020 data analysts will be in high demand in companies around the world.  A recent search of Jobs on LinkedIn specifically for ‘data analysts’ brought back over 33,000 results in the United States alone. Consider the amount of work collecting and storing all that data.  Now consider all the work analyzing all that data not to mention publishing the results.