WHY IT MATTERS: Digital Transformation

In Human + Machine, Accenture leaders Paul R. Daugherty and H. James (Jim) Wilson show that the essence of the AI paradigm shift is the transformation of all business processes within an organization - whether related to breakthrough innovation, everyday customer service, or personal productivity habits. As humans and smart machines collaborate ever more closely, work processes become more fluid and adaptive, enabling companies to change them on the fly - or to completely reimagine them. AI is changing all the rules of how companies operate.

Companies benefit from optimizing collaboration between humans and artificial intelligence. Five principles can help them do so: Reimagine business processes; embrace experimentation/employee involvement; actively direct AI strategy; responsibly collect data; and redesign work to incorporate AI and cultivate related employee skills. A survey of 1,075 companies in 12 industries found that the more of these principles companies adopted, the better their AI initiatives performed in terms of speed, cost savings, revenues, or other operational measures.

Companies benefit from optimizing collaboration between humans and artificial intelligence. Five principles can help them do so: Reimagine business processes; embrace experimentation/employee involvement; actively direct AI strategy; responsibly collect data; and redesign work to incorporate AI and cultivate related employee skills. A survey of 1,075 companies in 12 industries found that the more of these principles companies adopted, the better their AI initiatives performed in terms of speed, cost savings, revenues, or other operational measures.

In today's "digital age," the dominant narrative is that e-commerce has fully eclipsed physical retail. The truth looks a bit different.

As machines increasingly complement human labor in the workplace, we will all need to adjust to reap the benefits.

The future of retail is playing out in China's mom-and-pop shops. Alibaba says that over the last year, it has redone about 1 million mom and pop shops like the Huangs' across China. It has done the same with about a hundred superstores. Big and small, these outlets buy all their goods through Alibaba's platform and pay using its affiliate Alipay app.

Innovation is critical for established companies to stay relevant in the face of disruption. Here's our list of corporate innovation labs.

Leading organizations that are characterized by continual learning and experimentation require new skills, approaches, and capabilities.

Think of the trends we’ve seen emerge in recent years:

• Sensors and actuators, including implantables and wearables, that let us capture more data and impressions from more objects in more places, and that affect the environment around them.
• Ubiquitous computing and hyperconnectivity, which exponentially increase the flow of data between people and devices and among devices themselves.
• Nanotechnology and nanomaterials, which let us build ever more complex devices at microscopic scale.
• Artificial intelligence, in which algorithms become increasingly capable of making decisions based on past performance and desired results.
• Vision as an interface to participate in and control augmented and virtual reality
• Blockchain technology, which makes all kinds of digital transactions secure, verifiable, and potentially automatic.

Essentially, they identified eight ways people look at it:

1. Employee productivity. For 52 percent of executives, "becoming a digital business means enabling worker productivity through tools such as mobile, data access and AI-assisted processes."
2. Data-driven business performance. Close to half, 49 percent, also see digital transformation as "the ability to better manage business performance through data availability and visibility."
3. Customer experience. "For 46 percent of decision-makers, digital transformation "means meeting customer experience expectations, while 44 percent see it as "understanding customer needs through data collection and analysis."
4. Mobile capabilities. Another 46 percent see digital transformation as "providing secure, optimized anywhere/anytime access to assets."
5. Process automaton. At least 37 percent say digital transformation means "digitally modifying business and/or processes ."
6. Revenue streams. One-third, 33 percent, say digital transformation means developing new digital business/revenue streams.
7. Product innovation. Another 31 percent see digital transformation as achieving top-line growth through digital product enhancements/new digital products or services.
8. Supply chain optimization. For more than a quarter of companies surveyed (27 percent), digital transformation means digitizing "the flow of data and information worldwide which enables the movement of goods, services, finance and people."

Welcome to the now “annual” Canadian AI Ecosystem Map. What a year it’s been. The point of creating this map was to emphasize that the strength lies in the Canadian AI Ecosystem, as opposed to just one city’s. This year, we’ve seen ties strengthen, but also some weaknesses exposed. What I see now is a corridor of cities, each remarkable in their own right, coming together into a cohesive form that is comparable in size and influence with the US East Coast or Paris and London.

An analysis of more than 400 use cases across 19 industries and nine business functions highlights the broad use and significant economic potential of advanced AI techniques.

Economist Andrew McAfee suggests that, yes, probably, droids will take our jobs -- or at least the kinds of jobs we know now. In this far-seeing talk, he thinks through what future jobs might look like, and how to educate coming generations to hold them.

While there is evidence that the retail apocalypse is real offline. There are mixed signs about whether online retailing is experiencing a full apocalypse.

In May, J.P. Morgan’s quantitative investing and derivatives strategy team, issued the most comprehensive report ever on big data and machine learning in financial services.
Titled, ‘Big Data and AI Strategies’ and subheaded, ‘Machine Learning and Alternative Data Approach to Investing’, the report says that machine learning will become crucial to the future functioning of markets. Analysts, portfolio managers, traders and chief investment officers all need to become familiar with machine learning techniques. If they don’t they’ll be left behind: traditional data sources like quarterly earnings and GDP figures will become increasingly irrelevant as managers using newer datasets and methods will be able to predict them in advance and to trade ahead of their release.

Keynote at Andreessen Horowitz's annual 'Tech Summit' conference, talking about the state of tech today and what's likely to happen in the next decade: mobile, Google / Apple / Facebook / Amazon, innovation, machine learning, autonomous cars, mixed reality and crypto-currencies.

It may come as no surprise that technology-centric roles stole the show among emerging jobs in the United States, but the prevalence of machine learning and data science roles and skills indicate a shift in the types of technology we can expect to be using in the near future, as well as what professionals should be preparing themselves for.

Having an academic background and a comprehensive suite of skills were also strong trends, especially among professionals who are now machine learning engineers and data scientists. Both of these roles are also often held by professionals with 10 years or more of professional experience, so for those just starting out and having trouble landing one of these titles, don’t be discouraged!

It’s always a good reminder that soft skills will always be important, no matter the profession. The ability to collaborate, be a leader, and learn from colleagues will stand out in interviews, and even more once starting a job.

Google has gathered so much data, in so many areas, that it’s now crunching it together and creating features that Apple can’t make—surrounding Google Maps with a moat of time.

In response to growing concerns about autonomous weapons, a coalition of AI researchers and advocacy organizations released a fictitious video on Monday that depicts a disturbing future in which lethal autonomous weapons have become cheap and ubiquitous. The video was launched in Geneva, where AI researcher Stuart Russell presented it at an event at the United Nations Convention on Conventional Weapons hosted by the Campaign to Stop Killer Robots. Russell, in an appearance at the end of the video, warns that the technology described in the film already exists and that the window to act is closing fast.

Dimitris Papageorgiou, Partner, People Advisory Services, Ernst & Young LLP
John Van Reenen, Professor, MIT Department of Economics and MIT Sloan School of Management
Krystyn Van Vliet, Professor of Material Science and Engineering and Biological Engineering, MIT Department of Materials Science and Engineering

The AI Index is an open, not-for-profit project to track activity and progress in AI. It aspires to be a comprehensive resource of data and analysis for policymakers, researchers, executives, journalists and others to rapidly develop intuitions about the complex field of AI.
AI is the new electricity, and is transforming multiple industries. The AI Index will help current generations track and navigate this societal transformations. It will also help future generations look back and understand the AI's rise.

The robots are coming. We (as in the people who attend TED talks and things) tend to think we will probably be fine. You know, knowledge folks and all. We might not be. What will be our coping mechanisms? What can we do to be OK?

The Hype Cycle for Emerging Technologies provides insights gained from evaluating more than 2,000 technologies. The eight added in 2017 include 5G, Artificial General Intelligence, Deep Learning, Deep Reinforcement Learning, Digital Twin, Edge Computing, Serverless PaaS and Cognitive Computing.