The real world of artificial intelligence
In my last post—Winter is coming…—I explained that we are embarking on a program of sustained research, to deepen and broaden our understanding of how born-analog businesses are responding to digitisation and digital disruption, and in particular to identify those who have relevant experience and lessons learned.
One aspect of that is looking for the illuminating case studies of how established enterprises are making the most effective use of these new digital technologies, and in particular how they’re using them to become digital explorers.
One of the five key digital technologies that are having an enormous economic, social, political and environmental impact is Artificial Intelligence.
We already have some really interesting and insightful examples of these technologies.
AI has developed the capability to automate even high-end knowledge work, long thought the domain of highly-paid professionals. Kira Systems’ contract review platform counts half of the top 10 American law firms as customers. CaseMine builds on document discovery software with its “virtual associate,” CaseIQ, to deliver better briefs.
AI’s reach now extends to automating narrow and routine tasks that go way beyond administrative work. Affectiva’s face sensing, Cogito’s listening skills and Soul Machines ‘digital humans’ exploit AI to encompass even work that involves sensing human emotions, and portraying emotion with sufficient realism that we cannot help responding to it.
AI’s impact now also goes way beyond businesses, offices and our homes, into healthcare for example. In a recent clinical trial in the UK, Google’s DeepMind, for example, matched the performance of skilled specialists in diagnosing eye disease, and did so in way that facilitated collaboration with human clinicians. A trial at Stanford demonstrated that AI could was capable of classifying skin cancer with a level of competence comparable to dermatologists.
Even so, the current state-of-the-art of AI still suffers from significant limitations; although great at routine and narrow tasks, they rely on having great data to make machine learning work, and they are not yet capable of generalizable learning, or of dealing with out-of-context questions. The real power will come increasingly from AI augmenting human capabilities, racing with the machine, rather than against the machine.
Although these are amazing technologies, in this context we’re interested not so much in the technologies and their potential, but in the real-world commercial application of AI by born-analog businesses…
What are the most interesting ways that born-analog businesses, and in particular large established enterprises, are using AI?
The applications can be at every stage in the journey to becoming digital—as described in my previous post—from becoming digitally efficient through being digitally enabled to becoming a digital explorer.
I am particularly interested, however, in real-world applications of AI by born-analog that make them digital explorers, creating significant new value.
We would love to talk with you, if you’re interested in these issues — you can reach me at michael@endeavourpartners.net, or through LinkedIn
