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You can dream, create, design, and build the most beautiful place in the world, but it requires people to make it a reality – Walt Disney

The evolution and functional application of artificial intelligence (AI) is on the rise in many different ways and forms. The technology is going to impact the role of the project manager substantially in the next decade. We are shifting towards an era where intelligent machines work on our behalf rather than work on our command.

The enthusiasm for the emerging technology is outranking the scepticism by far. A recent poll held during the Microsoft Emerging Tech Virtual Summit showed that 59% of the participants find AI supercool, 36%  take a more conservative position, and 5% is deeply worried. The outcome is encouraging and indicating that people’s readiness to adopt the technology in their life and work is bright.

Driving forces like growth of computing power, maturity of cloud technologies, and enhancements in algorithms boost the evolution of AI in the last 5 – 10 years. Tractica, a market intelligence company that focuses on human interaction with technology, predicts a steep curve in AI revenue. They forecast that annual worldwide AI revenue will grow from $643.7 million in 2016 to $36.8 billion by 2025.

AI as technology exists for decades, but we may not have realized that as much as we do today. Imagine that the postal industry world wide is processing billions of documents and parcels using AI since the seventies. They automatically sort items and trigger distribution events based on text recognition software.

It is widely expected that AI is going to replace routine tasks that are highly predictable. In this case, the spectrum of change holds all possible colours. It means that all jobs will be impacted, some more than others. Evidence-based decision making enabled by AI will become a standard for many jobs. It is already happening in the health care industry.

Non-routine tasks that have a high degree of uncertainty, require creativity and social interaction, will continue to be performed by humans. AI will struggle with recognizing patterns in the available data set and is therefore unable to understand and process a transaction. For these none-routine tasks, AI will enhance and scale the role of humans by acting as an advisor instead of a worker. The following diagram illustrates that.

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The role of the project manager is going to change with the infusion of AI into the work environment. I wrote the oeder robaxin on line  ‘The augmented project manager’ about it. The document speaks about artificial intelligence or cognitive computing in more detail and how it can be applied to the role of the project manager.

The value of AI for project management is immense. It is a matter of time that AI roots itself deeper and deeper in the role of the project manager. We know that AI as technology is making rapid progress. We also know that the application  is the hardest part. To channel and expedite a meaningful adoption in the role of the PM, I am working with business partners to found a Think Tank. I will keep you informed about the progress we make in this blog on CIO.com.

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“The future of business process improvement is on making them intelligent. Machine learning is the driving force”

Machine learning is on a steep adoption curve and making its inroads in our daily lives and work. The application of the technology won’t be an issue at all. There’s an abundance of meaningful value propositions for many functional areas, business processes and roles across multiple industries.

Software vendors of enterprise business solutions are focusing their product development on machine learning and other related artificial intelligence technologies. CEO buy robaxin no prescription of SAP said that intelligent applications will fundamentally change the way you do work in the enterprise in the next decade. He mentioned that we need the system to tell us what to do.

In many publications about machine learning we read about IBM Watson beating humans at Jeopardy, or Google’s AlphaGo beating a Go world champion. There are predictions, for example from robaxin no prescription canada,  that indicate that singularity, or the moment in time when a computer will be as intelligent as a human, is going to happen around 2040.

We also know that machine learning solutions work with structured and unstructured data. Data is growing at a fast pace and doubles every 2 years. 80% of the data is unstructured and 20% is structured. The technological advancements of the last 5 – 10 years removed barriers that artificial intelligence has been struggling with for many decades. Computing power being the most important one. As an indication, IBM Watson can read 200 million pages in 3 seconds and understand the content.

Machine learning solutions are coming our way. A fundamental principle is that they predict based on past behaviour.

Think about weather predictions. IBM acquired the digital assets of can a senior buy robaxin in 2016 and is leveraging IBM Watson platform to provide meaningful services to businesses and consumers. The weather notifications you can receive on your smart phone are coming from IBM Watson, a machine learning solution.

Machine learning solutions aren’t always perfect and there are ways to go. Facebook is using machine learning to recognize and understand photos, video and audio that are posted by its users. Content that is not meeting Facebook’s standards is removed. An example of this is the recent removal of a 1973 world press winning get robaxin online no prescription of the Vietnam war. After a public outcry Facebook reversed its decision.

A few weeks ago I had a personal experience with Facebook’s machine learning solutions and how it influenced a post. I was using an iPhone app to splice a few videos and thought it would be great to add audio to it. I selected the tune from the app library. When I posted the video, Facebook rejected it, because it believed that I did not have the rights to use the audio. Facebook’s interpretation was wrong, because the tune was general available to the app users. It’s an indication that machine learning solutions can learn on their own, but need human intervention to train them.

Machine learning is going to change the way we design and optimize business processes and functional roles. Automation will shift the role of humans more to exception based interactions and real-time, evidence-based decision making. The level of people, process, technology and data integration will further increase. Standardization of end-to-end processes in the supply chain will further manifest.

My expectation is that the software vendors of enterprise business solutions like SAP, Oracle and Salesforce will put their focus on functional areas where there is a high volume of routine transactions first. Think about the order-to-cash process where recurring orders flow through the order entry, fulfillment and delivery processes with limited human intervention. Think about the customer service process where the scheduling of work orders is further automated. Through internet of things technologies, real-time data becomes available that enable machine learning solutions to schedule service orders at the right time with the right spare parts ordered and skilled technician assigned.

There will be niche solutions too where machine learning is augmenting the human capability in a specific area. Think about travel and expense management solutions, where the processing of entries is for the greater part done without human intervention. Another example is recruitment. Machine learning solutions will take over the steps of identifying and screening candidates. Recruiters will receive a short list of qualified candidates and can focus more on the softer aspects that do require human interaction, for example determining if the candidate is a good fit with the organization.

Interaction with customers through call centres and other channels like email, apps or internet is another example. Machine learning solutions can understand text and speech and process simple transactions. Audible from Amazon does that to process refunds for audio books that the customer does not like.

Machine learning and other artificial intelligence solutions are at the top of robaxin without rx Hype Cycle for Emerging Technologies, 2016. The evolution of the technology in the next decades will be fascinating, because it is coming so close to our existence as human beings. The potential to apply it in a meaningful way to our live and work will be enormous.

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You aren’t going to stop it. The trend is going to keep moving – Ginni Rometty

Cognitive computing is rapidly making inroads into the professional services workspace. The emerging technology will have a lasting impact on all jobs across all industries, with health care, finance and legal as early adopters. As much as it changes current jobs, it will also create new jobs.

For many years, IBM is the leader in the field of cognitive computing with robaxin 500.  According to IBM, the purpose of robaxin online no prescription  is to enhance and scale human expertise, rather than an attempt to replicate human intelligence. IBM prefers to call it augmented intelligence (AI) instead of artificial intelligence.

The underlying thought is that cognitive computing functions in an assisting, sub-ordinate relationship to humans. This is an interesting point of view and positioning of the technology, because many experts believe that cognitive computing has the potential to advance in a superior relationship to humans.

There are a number of technologies that are related to cognitive computing like machine learning, text to speech recognition, natural language processing, image detection, sentiment analysis, and others. All of these technologies have the intention to improve human productivity and decision making.

Cognitive computing will have a material impact on the way we manage technology-driven-change projects. It is a fantastic opportunity to bring the role of the project manager to the next level. The emerging technology shall operate as an assistant and expert in many PM disciplines. It will change the execution of tasks and shift the focus of the PM to more creative and analytical activities. It will provide better information to make decisions.

Here are 5 examples of where I think cognitive computing will have a material impact on project management in the future:

Methods, Tools and Best Practices – The AI assistant is knowledgeable of all the relevant methods, tools and best practices for the project, because it can read and understand speech. The PM can ask specific questions and gets accurate feedback from the AI assistant in real-time. The information can be used for any PM task. As the project progresses and the AI assistant learns about the project deliverables, it can give recommendations to the PM, based on what could be versus what’s actually being delivered. It’s basically a quality check on deliverables that helps the PM to manage expectations. At the conclusion of the project, the AI assistant conducts lessons-learned sessions with the project team and updates the knowledgebase for use in other engagements

Scope management – The challenge with managing scope is not only the change management aspect. It is also the verification of the scope that is being delivered. Something we are not necessarily good at once we are getting close to the finish line. The AI assistant is capable of understanding the planned scope, based on the statement and detailed definitions in design documents. With that knowledge it can verify the scope based on data from status reports and test systems. The AI assistant can make a recommendation to the PM where the project is at risk close to a go live

Time management – Project scheduling can be a daunting task, because of its complexity. The AI assistant can not only provide a baseline schedule that the PM can adjust and refine, it can also make predications based on historical and empirical data. This improves the productivity of the PM and the entire project team. The AI assistant can plan and forecast the required resources based on an estimation model that it maintains with data from the project itself and other projects. The AI assistant can determine if the project is on track and if there are tasks at risk that are on the critical path. A prerequisite to many of the functions that the AI assistant can provide is the access to data. For example, project team members must record time at the task and deliverable level

Cost management – Based on the scope definition, baseline schedule, resource plan, approach and risk tolerance, the AI assistant can calculate a cost baseline that the PM can adjust and refine. As the project progresses, the AI assistant can make an ETC and EAC forecasts based on earned value parameters that the PM has set. Based on the approach the AI assistant can calculate the cost impact of alternative delivery scenarios. As example, it can determine the cost and schedule impact of using more off-shore resources

Organizational Change Management – This is an area where the PM can provide more value with the arrival of the AI assistant. When a majority of the routine tasks have been delegated to the AI assistant, the PM can apply his creative and social skills on driving organizational change. The AI assistant and PM can work collaboratively in this field. As example, the AI assistant can provide a baseline of questions to conduct change impact assessments and training needs analysis. Based on the analytical outcome of the response, the PM can optimize the change management plan and properly engage with the key stakeholders. Furthermore, it can determine what course are required to train the project team and end-users. Another example is stakeholder management. Based on buy generic robaxin canada, the AI assistant is capable of understanding the key characteristics of the main stakeholders and provide recommendations on how to best engage with them. The analysis is also benefiting the PM in aligning and committing the stakeholders to the project goals

The evolution of augmented intelligence or cognitive computing in the professional services workspace is fascinating and should be welcomed with open arms. I strongly believe that an AI assistant can further strengthen the role of the PM and increase the value of services to the client. The majority of the examples that I have used have yet to be developed as applications for practical use. The technology is there. It is a matter of when, not if.

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The future ain’t what it used to be – Yogi Berra

Is Ikenga, your Project Manager Robot, going to be your best friend because it completes your project initiatives on time, budget and quality over and over again? Time will tell what ultimately happens, but make up your mind and get ready for the next technology evolution that can significantly change the ground rules of the way we do business today. The application of artificial intelligence and robot technology in day-to-day business operations is rapidly moving ahead and already changing the DNA of certain industries. Don’t let it get ahead of you, but instead understand the possible implications, benefits and opportunities for personal development and growth.

The main reason why artificial intelligence and robot technology are evolving rapidly is because computation power has reached a level where it is cost effective and able to deal near real-time with massive amounts of data. A front-runner in this area is IBM with Watson, a cognitive computing solution that is able to answer questions and therefore assist humans in making informed decisions.

In their book Second Machine Age (2014), Andrew McAfee and Erik Brynjolfsson explain the characteristics of and differences between the First and Second Machine Age. Over 200 years ago in the First Machine Age, muscle power was gradually being replaced by machines, starting with the steam engine, followed by electricity and other inventions. In the Second Machine Age, wherein we live today and are just at the beginning, knowledge power is gradually being replaced by machines.

There are three forces behind the Second Machine Age: exponential, digital, and combinatorial. Moore’s law enabled the exponential growth, meaning the doubling of computing power every 18 months. This constant doubling has delivered the advances we see today of which many appeared after 2006. The digital force brought us to the big data model that allows us to collect, process, store and utilize structured and unstructured content in massive volumes. The combinatorial force is the innovative power of humans to combine technologies in a way that was not possible before, because of limitations for example in computation power. The driver-less car, Siri, 3D printing, robots are examples of key technological advances of the recent past that are a result of the combinatorial force.

According to Carl Benedikt Frey and Micheal A. Osborne (Oxford University, 2013), routine intensive occupations could be susceptible to computerization over the next two decades. That in itself is not new, because for example in the automotive industry robots have been used for more than a decade. But what is new is the exposure to the services industry. Routine service tasks that are being done by humans today, may be done by robots or other forms of artificial intelligence tomorrow. The researchers speak about jobs in transportation, logistics, as well as office and administrative support. They estimated that 47% of total US employment is at risk. Occupations that require a high level of creative and social intelligence have relatively low risk of being impacted.

What this means is that artificial intelligence and robotics will also enter the professional service industry. Law Times (2014) wrote about the implications for law firms. They mention that Law firms will see nearly all their routine process work undertaken by artificial intelligence, completely changing the traditional associate leverage model. It is primarily the work being done by paralegals and junior lawyers who perform a lot of work that’s fairly tedious.

Pessimists would likely think that the continued evolution of artificial intelligence could end human life as we know it. Optimists would embrace the evolution as an opportunity and see a shift of focus by humans to the more analytical, conceptual and value add tasks, where a high level of creativity, pattern recognition and collaboration is required.

From an optimistic perspective, what can the evolution mean for the Project Manager? Or in other words, what can be some of the tasks that Ikenga can take on?

As I am trying to answer these questions, I realize that a substantial part of project management is non-routine. In many of the process areas of the PMBOK – Project Management Body of Knowledge (PMI), a high level of creativity, pattern recognition and collaboration is required. Perhaps it is because projects, contrary to business operations, are temporary and unique endeavors focused on accomplishing a singular goal . Having said that, projects do create deliverables, lessons learned and other historical content that can be leveraged in similar projects in the future. So projects are creating an enormous amount of big data that can be utilized by using artificial intelligence and robots. With that notion I think that Ikenga can assist the Project Manager as an Expert with the more routine activities like cost estimation, scheduling, and risk planning, but also once there is an approved, detailed plan and schedule available do the greater part of status reporting. Don’t you see Ikenga walking around the project floor seeking input from team leads on deliverable status?

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