Digital Transformation and Future Workforce

Digital transformation is upon us, and every industry and every business is part of it. Change is happening fast and many, if not all, industries are being redefined. Manufacturing, especially, has huge gains to realize from this disruption, as advanced technologies like IoT, artificial intelligence (AI), machine learning, mixed reality, digital twins, and blockchain empower manufacturers to improve efficiency, flexibility, and productivity through new levels of intelligence.

Of all the technologies reshaping our industry, I would say that AI plays one of the biggest roles here in terms of the disruption—and resulting opportunity—for both our industry and our workforce. AI has made large strides in recent years and is poised to open up new types of employment opportunities. The transformational possibilities of AI for manufacturers, employees and the industry-at-large are enormous.

However, as we look to a future powered by a partnership between computers and humans, it is important that we work to democratize AI for every person and every organization – something Microsoft is deeply focused on.

Two critical data points, from recent research, to establish the enormity of change:

  • Machines complete 29% of tasks today, which is expected to go up to 71% by 2025.
  • 75 million jobs to be displaced by automation and 133 million new jobs to be created between 2018-2022.

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What is cloud computing?

Simply put, cloud computing is the delivery of computing services—servers, storage, databases, networking, software, analytics, intelligence and more—over the Internet (“the cloud”) to offer faster innovation, flexible resources, and economies of scale. You typically pay only for cloud services you use, helping lower your operating costs, run your infrastructure more efficiently, and scale as your business needs change.

Top benefits of cloud computing

  • Cost
  • Speed
  • Global scale
  • Productivity
  • Performance
  • Security

Types of cloud computing

  • Public cloud
  • Private cloud
  • Hybrid cloud

Types of cloud services:

  • IaaS
  • PaaS
  • serverless
  • SaaS

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Uncovering the ROI in AI

Artificial intelligence is loosely defined as a broad set of technologies that think and act like people. These intelligent machines can understand, interpret, reason and engage people in a natural way, as a human would do. It’s clear from working with clients across several industries that there are different AI maturity levels. AI maturity isn’t just about the technology you use; it’s also determined by the people you have in place and the supporting business processes. Understanding what you’re doing today gives you a clear starting point, so you know where to focus your efforts.

Finding the ROI in AI

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In the market, there is variety in the number and types of problems that AI can solve, and it will be rare that an organization will buy or even build one AI product that will be able to solve all its problems. Instead, companies will be able to better maximize their ROI by applying different AI technologies to their existing specific business problems. Today, we see several companies finding the biggest ROI with the combination of automation and cognitive service technologies.

For example, Avanade has been working with an insurance company that began by automating rote, manual processes to prioritize claims and assign them to workflows. The company took the next step by adding cognitive services that could read all customer query tickets and understand the customer’s intent. The queries were then categorized and assigned to the right workflow. By using AI to answer more standard tickets, the company liberated people to answer more complex questions, resulting in up to 60 percent gains in efficiency and resolution time.

This example shows that you don’t need to take big steps to see positive results from AI implementations. Simply find the right process, get started and then evolve your approach to deliver business results.

Solve the problem first, then apply the right technology

While it’s easy to view AI as a single technology, it is in fact various technologies that range from automating with cognitive services, all the way to advanced analytics and deep learning to proactively solve problems.

Today, many organizations begin their AI implementation with automation, in areas with lots of manual and repeatable tasks like call centers or back office process like finance and accounting. It’s important to understand the human processes and behaviors that are driving your business and decide how AI can augment them, not replace them. Think less in terms of the technology, and more about the impact that you want AI to have on the people connected to your business – both customers and employees. This is human-centered AI – an approach that focuses on augmenting the workforce to improve customer and employee experiences.

For example, a financial services company in Europe was finding that they were losing a significant number of customers to their competitors. They engaged with Avanade to create machine learning models to better predict customer churn. Looking over a 3-month period and over 100 factors as inputs, the model was able to predict which customers were most likely to churn, and the financial services firm was able to take appropriate action and targeted messages in their next marketing campaigns, reducing the numbers of customers likely to churn by 50 percent.

Shifting to AI-first

Across almost every industry, we are seeing significant ROI for those organizations applying strategic AI technologies. Some of that is quantitative, while others are more qualitative, such as better customer and employee experiences, tracked through net promoter scores and other similar engagement measures. And while benefits are being realized, the true leading companies are beginning to determine how to apply AI more holistically outside of the siloed projects running within specific business units throughout their company.

These leaders are recognizing how to bake AI into their business, across all core functions. Stitch Fix, a leading online and personal shopping subscription service, is a great example of a model-driven company that sold almost $1B of clothing in 2017. You can see just how pervasive the models are in every element of their business. But it’s not all automation, as it’s truly a great example of human-centered AI. Their stylists were able to utilize the data and alter or override the styling the algorithm delivered. This is important because neither the person nor the algorithm can be perfect.

Every business looking to embrace AI should be clear about what data is being used and for what purposes. According to Avanade and Wakefield’s research, 89 percent of IT decision-makers say they have encountered an ethical dilemma at work caused by the increased use of smart technologies and digital automation, with 87 percent admitting they are not fully prepared to address the ethical concerns that exist in this new era. We encourage any organization working to implement AI to create a digital ethics framework that sets out how you will manage the bias that can be inherent in any AI algorithm. This includes internally built applications and purchased solutions. To help address this, Avanade recently created an ethics task force that is developing a digital ethics framework to help us internally and to guide our clients.

Leading companies that take a holistic, AI-first approach, driven by strategic business needs, will see significant ROI in their bottom line and for their shareholders.


Realizing the true magic of AI by delivering Transformative Experiences

It’s all about data, analytics and human-centric design

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Transformative user experience and intelligent action – these are the magical things that AI provides. Now that we can integrate mountains of data and process it with machine learning models, we’re starting to realize the true magic of AI. It’s most valuable when we deliver intelligence at the end point of interaction– with employees and customers – on a day-to-day basis.

And it doesn’t take in-your-face robots to make that happen. Effective AI is subtler; it’s a transparent extension of human intuition that serves to simplify interactions without being intrusive or annoying, which is accomplished with human-centric design.

AI is all around us

Let’s examine some of the ways AI is transforming the way we go about our daily lives – at work and at home.

  1. Computer vision experiences are some of the most dramatic being delivered by AI. Deep neural networks enable computers to understand images and video, and the content within them. These models are used on the edge to deliver experiences such as augmented reality.

Factory of the future. Microsoft HoloLens – a holographic computer – provides information, instructions and alerts based on the objects it recognizes so you don’t have to fumble around with a laptop or a mobile device and are free to use your hands to get your job done.

File insurance claims quickly and efficiently. Being in a car accident is stressful enough; filing an insurance claim doesn’t have to be. By reading data from photos taken with your mobile device (driver’s license, license plates and damaged cars), computer vision can recognize makes and models of vehicles and assess damage. Through intelligent automation, your claim gets filed, and tow trucks and rental cars get ordered – all automatically.

  1. Natural language processing is transforming the graphical user interface into the natural language interface through the use of chatbots, virtual agents, and intelligent search applications.

A hassle-free way to resolve computer problems. You no longer have to pick up the phone or write and respond to emails in order to open a ticket for helpdesk service. An enterprise virtual agent can understand issues, such as a broken printer, and then automatically generates a ticket. Need an update? Simply ask the virtual agent a question.

Easily find the information you’re looking for. Now you can search the contents of unstructured documents just by asking a question. Natural language understanding enables the enterprise virtual agent to understand the contents of unstructured documents, and provide you with the relevant passage of text.

  1. Speech recognition has changed the way we interact, and with whom we interact. Cortana, Siri, and Alexa have infiltrated and enhanced almost every aspect of our lives.

Cortana helps you be more efficient at work, understands your schedule and plays music for you.

Alexa orders your pizza, turns on your lights and adjusts your home’s temperature.

Siri finds a restaurant for you, guides you there and helps you find a parking spot.


Top 5 AI Trends for Business Leaders

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Artificial intelligence has been one of the technologies to make heads of people from diverse industries turn. Apart from laymen and consumers who were fascinated by the potential and functionality of artificial intelligence, it is the business leaders, corporate managers and industry influencers who have joined the bandwagon of the population to be stunned by the technology. Thanks to this, they are now increasingly looking to bring in the technology to their businesses for optimized performances and experiment on various levels. If you are business leaders, looking to incorporate the benefits of artificial intelligence in your business, you need to know the following.

Business-Centric Applications

Conducting experiments with artificial intelligence for your business is way different from conducting business-centric experiments. Instead of exploring the potential of artificial intelligence for your business, you need to find areas of shortcomings in your business and focus on implementing artificial intelligence to it. That is would fetch you better results in the longer run. If you are a publishing house, focusing on delivering books using smart drones makes sense. But you know what’s more sensible? Using artificial intelligence systems to fight attrition, turnaround times, quality optimization, project management and more!

Always Put Your End-user First

The very aspect of technology is to make the lives of customers and laymen better. That is why businesses and brands exist. So when you are working on implementing artificial intelligence for your business, put your customers and employees first and see how they would react, respond and adapt it. This begins by understanding the behaviour of each persona and reverse engineering the designing process. When you analyze the behaviour, you would also be surprised to see that a few areas would not actually need the application of artificial intelligence. This again ties back to the first supporting idea we mentioned.

ai blog 6Have a Uniform Understanding About AI In Your Organization

A good business organization is one where every employee has a holistic idea about the business his or her company is into. From the CEO who runs the show to the last level of employee who ensures it runs smoothly, everyone needs to have an understanding of artificial intelligence as much as you do, at least the basic jargons. You need to talk about in your boardroom meetings and ensure your people talk about it during their breaks and work so that you get the topic of artificial intelligence implementation going around at your workplace.


Machine Learning is Here to Stay

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Welcome to the fourth industrial revolution—a world where artificial intelligence (AI) drives today’s technological disruption, blurring the lines between tangible and digital realities. Companies continue to shift toward AI and machine learning (ML) processes, and business leaders are quickly realizing the potential gains from investing in them. These gains include faster, smarter automation, predictive analytics, and new-and-improved ways to establish customer connections—among countless other possibilities.

According to the International Data Corporation (IDC), spending on AI and ML will grow from $12B in 2017 to $57.6B by 2021. Deloitte Global predicts the number of machine learning pilots and implementations will double in 2018 compared to 2017, and double again by 2020.

These predictions are beginning to play out. In 2018, the Massachusetts Institute of Technology announced its plan to create a new college (backed by a planned investment of $1 billion) dedicated to “educating the bilinguals of the future: people in fields like biology, chemistry, politics, history, and linguistics who are also skilled in the techniques of modern computing that can be applied to them.”

AI and ML strategies are rapidly evolving. No longer just an intangible concept, AI solutions have already entered our daily lives in the form of smart speakers, customer service chatbots, and autonomous vehicle features.

So, what is machine learning?

By offering a specific set of guidelines, scientists enable machines to create their own logic, thereby developing the ability to explore and analyze data on their own. The term “machine learning” helps to define this process. Machine learning is one of the main ways artificial intelligence is created.

What makes machine learning tick?

Think of algorithms as the rules machines are instructed to follow. Initially, machines are introduced to a set of data and “asked” to begin exploring that information. This introductory set of data is called training data. Once the machine has worked through its training data, it can begin recognizing patterns and even make decisions according to specific algorithms.

Some computers can even aim for specific goals and receive rewards upon meeting them. As this “learning” process evolves, computers are able to alter new inputs into outputs. These outputs might include: new data, labeled data, decisions, and more.

While ultimately machines might arrive at an operations state where human intervention is no longer necessary, we’re not there yet. According to a recent report from the McKinsey Global Institute, AI techniques require models to be retrained to match potential changing conditions, so training data must be refreshed frequently. McKinsey notes that in one-third of the cases, the model needs to be refreshed at least monthly, and almost one in four cases requires a daily refresh.

How is AI at work today?

AI is everywhere. It backs the speech recognition system in your smartphone, and will power the robotic vision of your future self-driving car. It also drives the risk-management methods improving the security of your local bank. AI continually improves your government’s emergency response and national defense initiatives. Counting on your doctor to securely manage your health information? AI protects that data. Shopping online for that perfect product? Chances are, AI powered your chatbot customer service rep, as well as populated your search results with relevant items to purchase.

Just scan the latest headlines—organizations are rapidly realizing the benefits of AI-backed systems and incorporating them into their daily processes.

Taking inspiration from the NYPD, the London Assembly police and criminal committee recently announced that implementing AI technologies would enable the addition of over 500 officers to their current ranks, as well as save up to £30 million. MIT researchers are currently developing a fully automated molecule-design process, potentially leading to faster, more consistent pharmaceutical products.

AI is even getting artistic. An auction house recently planned to sell an AI-produced work of art. Crafted from an AI-powered algorithm, the canvas portrays an image based off of a dataset of 15,000 portraits painted between the 14th and 20th centuries.

Whether offering AI-powered purchasing suggestions or featured insights tailored to specific shoppers, the world of retail is constantly exploring the many benefits of AI. Sephora now utilizes a chatbot that offers beauty tips to customers within a one-on-one environment. Coca-Cola recently unveiled an AI-backed vending machine that communicated with users, encouraging them to recycle via tailored “facial” expressions.

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Getting started with AI

Even if you’ve yet to jump on the AI train—it’s not too late. AI has already proven to be a profitable investment, and will only continue to improve business solutions as technology advances. Since every organization is different, every AI investment strategy also varies. Ultimately, an AI investment strategy should strengthen and solve for the overall business strategy. Where could machine learning shorten product development feedback loops? How can data on customer behaviors and preferences be used to drive better, more personalized customer experiences, in real-time? How could predictive modeling refine your competitive focus?

Your organization’s ML and AI will be as strong as the data you use to train it. Appen can help. With over 20 years of data expertise behind us, we’re providing high-quality training data that is used by leading global technology companies, governments, and other organizations, across a variety of data types, to help them build better machine learning-based products. We collect and annotate speech, sound, image, video, and text data to power machine learning and AI solutions. We also review and annotate data from existing products and services to evaluate content relevance and improve user experience.