The Current State of AI Adoption

Irving Wladawsky-Berger

In the past few years, the necessary ingredients have finally come together to propel AI beyond early adopters to a broader marketplace: powerful, inexpensive computer technologies; advanced algorithms; and huge amounts of data on almost any subject. AI is seemingly everywhere.

Five Ways People Adopt And Love Change

Adaptive Path

Luckily, a communications expert named Everett Rogers looked deep and long at how human beings actually look at and choose to adopt something new and innovative. I love this because Rogers doesn’t look at what sells, but at what actually gets adopted and really, truly used.

Social Software Adoption

Tony Karrer

You can find all sorts of interesting resources via eLearning Learning around Adoption. Not surprising, the terms most closely associated with Adoption are Adoption of Social Software and Adoption of Enterprise 2.0. adoption Facilitating Adoption of Web 2.0

Wikipatterns - A Pattern to Emulate

Tony Karrer

Found this via a post on EdTechPost: Wikipatterns It provides patterns for various roles and adoption patterns. What's great beyond just finding out about Wikis is the beauty of how the information is presented - as patterns. FAQs are a great tool, patterns applied like this is also a good tool

Tools For New Thoughts: A Special Webinar For "Early Adopters" Of My Book

Steven Berlin Johnson

So laced through the seven chapters on the different patterns of innovation, in between all the stories of world-changing creativity, there are a number of passages that talk about useful tools or strategies for bringing some of these insights into your own life. Where Good Ideas Come From is an idea book about the history of ideas, but I have always thought of it as a book that would have real practical value as well.

Adoption of Web 2.0 and eLearning 2.0 Revisited

Tony Karrer

A consistent pattern in our response to new technologies is we simultaneously overestimate the short-term impact and underestimate the long-term impact. - and eLearning 2.0 , I got asked about adoption.

Toward a Pattern Language for Enterprise 2.0 : Andrew McAfee’s Blog

Andy McAfee

Andrew McAfee’s Blog The Business Impact of IT Home Home RSS Search Toward a Pattern Language for Enterprise 2.0 June 10 2009 Comments to this post A Pattern Language , published in 1979 by Christopher Alexander and his colleagues, was a landmark book in architecture that also became a landmark in other fields like computer science ; one review called it “The decade’s best candidate for a permanently important book.&# First is a set of patterns where 2.0

Edge Perspectives with John Hagel: Patterns of Business Innovation in China and India

John Hagel

From a strategist’s viewpoint, though, what I miss in such coverage is any deep analysis of the patterns of business innovation that might help to explain the explosive growth in both economies or the implications for Western companies.

I'm sorry, you're just not incompetent enough to get it

Martijn Linssen

Do you see the pattern here? adopt knowledge management marketing maturity social media trustOlivier Blanchard made me do it. martijnlinssen :D As far as I can tell, incompetence isn't a driver of failure. It's a driver of advancement.

We have engaged in unnatural communications

Martijn Linssen

Subscribe Top Posts Generations, Social and Enterprise: adopt vs adapt Enterprise 2.0: Adopt vs adapt Microsoft and Cloud - they just don't get it, do t. Business or Pleasure? -

Edge Perspectives with John Hagel: Retailers and Customers

John Hagel

Almost a decade ago, I detected an intriguing pattern regarding the unbundling and rebundling of firms (purchase unfortunately required). Of course, the pace and trajectory of unbundling (and related rebundling) differs across industries and geographies – the patterns are complex and fractal.

Ask Idealware: Solutions for Tagging and Archiving a Discussion List | Full Circle Associates

Nancy White

It also made me realize that this was yet another thing contributing to my recent pattern of “not getting to blogging.&# It is finally pretty well adopted by the KM4Dev community, but after 2 years of bugging by yours truly, now known as the wiki pest from the west. Will people go back and use the archived and tagged material, or will they follow the age old pattern of just asking again?

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Edge Perspectives with John Hagel: Gladwells Cellular Church

John Hagel

They adopted and refined the technique of organizing in small cells to achieve change. I look for patterns. We are seeing this same pattern play out in the evangelical movement.

Manufacturing: Where the Jobless Recovery Is Most Evident

Andy McAfee

Unfortunately for job seekers, I expect that pattern to resume in the very near future. The historical pattern is very clear and very regular here, and I see no reason it won’t repeat itself.

The Impact of AI on the World Economy

Irving Wladawsky-Berger

It looked at their adoption of five broad categories of AI technologies: computer vision, natural language, virtual assistants, robotic process automation, and advanced machine learning. AI adoption could widen gaps between countries, companies, and workers.

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Twelvetide 18:09 habits & the soul

Dave Snowden

However with life come habits of personal behaviour, was of working and thinking that become patterns we can’t escape. We are not in detox January and we know an absolute change of that period is sufficient to break a pattern of approaching alcoholism or at least dependency.

Artificial Intelligence is Ready for Business; Are Businesses Ready for AI?

Irving Wladawsky-Berger

asks McKinsey in a recently published report - Artificial Intelligence: the Next Digital Frontier. “AI adoption outside of the tech sector is at an early, often experimental stage,” is the report’s succinct answer. “Few firms have deployed it at scale.”. AI is now seemingly everywhere.

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A Framework for Building AI Capabilities

Irving Wladawsky-Berger

But, despite its market acceptance, a recent McKinsey report found that AI adoption is still at an early, experimental stage, especially outside the tech sector. The report adds that the gap between the early AI adopters and everyone else is growing.

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Buyer/organisation alignment

Dave Snowden

It contrasts early and late adoption between buyer and organisation. So you have four options: Early adopter buyer in an early adopter organisation. Early adopter buyer in a late adopter company. Late adopter buyer in early adopter organisation.

Machine Learning and Knowledge Discovery

Irving Wladawsky-Berger

The article told the story about Google’s adoption of an AI first strategy , and in particular, its use of deep machine learning to dramatically improve Google Translate , one of its more popular online services.

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A Framework for Building AI Capabilities

Irving Wladawsky-Berger

But, despite its market acceptance, a recent McKinsey report found that AI adoption is still at an early, experimental stage, especially outside the tech sector. The report adds that the gap between the early AI adopters and everyone else is growing.

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Defend your mess

Euen Semple

Most of the early adopters, myself included, were happy with the really simple structure and organic growth that had helped it find its place in the organisation. They thought that people would find it difficult to navigate if it didn’t follow the familiar patterns. The forum worked because it didn’t fit the patterns. The patterns didn't work. The silos bore little relationship to the real patterns that emerged from our day to day exchanges with each other.

Getting on the AI Learning Curve: A Pragmatic, Incremental Approach

Irving Wladawsky-Berger

Machine learning methods are particularly valuable in extracting patterns from complex, unstructured data, including audio, speech, images and video. After decades of promise and hype, AI is now seemingly everywhere.

The MIT Intelligence Quest

Irving Wladawsky-Berger

AI was reborn in the 1990s when it adopted a more applied, engineering-oriented paradigm. How does human intelligence work, in biological as well as in engineering terms? And how can we use such an understanding of human intelligence to build wiser and more useful machines?

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The Top Ten Emerging Technologies of 2017

Irving Wladawsky-Berger

As new data is ingested, the system rewires itself based on whatever new patterns it now finds. Deep learning looks for patterns of patterns, with each successive layer looking for patterns in the previous layer.

Determinism, Best Practice, and the ‘Training Solution’

Charles Jennings

Anyone who has even the most rudimentary understanding of chess knows that to adopt a strategy based on determinism is to often invite failure.

5 uncertainties that will shape the future of wearable technology

Ross Dawson

While it is always hard to predict consumer response to new technologies, it is safe to say that any early adopters will take to the next generation of devices with alacrity. Now that wearables are in the market there are major uncertainties around the acceptance of interfaces that are a step beyond what we are used, for example using smaller screens for smartwatches, wearing glasses that are (initially) difficult to make stylish, or adopting contact lenses as an information interface.

Will There Be Enough Work in the Future?

Irving Wladawsky-Berger

For each of this six countries, the study modeled the potential for employment changes in more than 800 occupations based on different scenarios for the pace of automation adoption and for future labor demand. Will there be enough work in the future?

On virtue

Dave Snowden

We are creating a generation isolated in virtual echo chambers in which the patterns of habituation or personal satisfaction and computer games.

Peering into a Confusing, Paradoxical Future

Irving Wladawsky-Berger

To what extent will major state powers, as well as individuals and groups, craft new patterns or architectures of international cooperation and competition?”. “To

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BlueIQ at IBM Finally Goes External!

Luis Suarez

So, as I am ramping up the last few hours of my holidays, yesterday afternoon I found out, through my colleagues, that, after a long while, our IBM Social Software Internal Adoption Program is now ready to transcend the firewall and go external. ( Note: You see?

Artificial Intelligence is Ready for Business; Are Businesses Ready for AI?

Irving Wladawsky-Berger

asks McKinsey in a recently published report - Artificial Intelligence: the Next Digital Frontier. “AI adoption outside of the tech sector is at an early, often experimental stage,” is the report’s succinct answer. “Few firms have deployed it at scale.”. Only 20 percent of respondents had adopted AI at scale in a core part of their business. 40 percent were partial adopters or experimenters, while another 40 percent were essentially contemplators.

The Disruption Debate - What's Missing?

John Hagel

This demise is typically brought about by one or more players adopting a different approach to a market or arena that represents a significant challenge to the established position of existing participants. One of the issues with a case study approach is that it obscures the more fundamental and systemic trends and patterns that are playing out around us. But there’s one key difference that helps to explain a sustained and increasing pattern of disruption today.

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Mastery and competence

Dave Snowden

In one of the breakouts today a few of us spent three sessions working on a wider education initiative around Agile adoption. My point was not to challenge the success, or the value of what had been achieved, but I am more cautious about its adoption.

A Framework for Building AI Capabilities

Irving Wladawsky-Berger

But, despite its market acceptance, a recent McKinsey report found that AI adoption is still at an early, experimental stage, especially outside the tech sector. Based on a survey of over 3,000 AI-aware C-level executives across 10 countries and 14 sectors, the report found that 20 percent of respondents had adopted AI at scale in a core part of their business, 40 percent were partial adopters or experimenters, while another 40 percent were still waiting to take their first steps.

Serious AI Challenges that Require Our Attention

Irving Wladawsky-Berger

Despite wide adoption, predictive policing is still in its infancy, open to bias and hard to evaluate…”. Equating locations with criminality amplifies problematic policing patterns.”.

Integration and an alarmist implication

Dave Snowden

That lack of diversity allows for new ideas to emerge in the fringe of the system (the early adopters). Before and immediately after this we pay attention to the tails of distributions and we hit negative patterns early and fast – there is no predictability.

If Your Enterprise Social Network Is a Ghost Town It’s Probably Due To Your Corporate Culture

Dan Pontefract

They’re windowless and the carpets look as though designers around the world have colluded with one another to see who can come up with the most bizarre patterns possible.

Liminal Cynefin, stepping over the threshold

Dave Snowden

Part of the power of Cynefin is that it is multi-layered in adoption. This is difficult to do in the concrete as old patterns assert themselves to quickly, hence the use of abstraction to prevent that.

Getting on the AI Learning Curve: A Pragmatic, Incremental Approach

Irving Wladawsky-Berger

Machine learning methods are particularly valuable in extracting patterns from complex, unstructured data, including audio, speech, images and video. These findings suggest that companies seeking to adopt AI in their operations should leverage and ramp up their existing analytics capabilities. There projects were starting to use machine learning algorithms to detect patterns in vast volumes of data and interpret their meaning, a kind of analytics on steroids.

The Real Value of Labor

John Hagel

Can you see the pattern? If we adopt this mindset, labor is now about learning, everywhere and all the time. It’s Labor Day in the US, so what better day to reflect on how misunderstood workers are? Truth be told, workers are often viewed as a cost by many institutions. In fact, that’s where they appear on financial statements – they’re a major expense item on the income statement. That view of workers naturally sets up an “us vs. them” and “win/lose” mindset.

iPad swiftly becomes the dominant medium for reading and entertainment

Ross Dawson

Laptop/ computer is in the lead at 33% (reflecting the very tech-oriented community that have been the early adopters of iPad), with iPad at 24% beating out mobile phones at 22% and TV languishing in fourth place at 19%. The question is of course where usage patterns go to from here.

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A Playbook for Improving Customer Journeys

Adaptive Path

Well, it’s a little easier when you know what to look for, what the patterns of success are. From a wealth of work in this space, we’ve found some common patterns that have emerged when we travel from current-state experience maps to bringing about future-state experiences.