Alexa, hack my business model. With AI.
Blog: Capgemini CTO Blog
“What would Amazon do?” If you happen to be caught in an innovation workshop, out of inspiration and at a loss for words, here’s the simple line that may break the inertia. We introduced this mantra years ago as part of our TechnoVision trend series and have been using it ever since with remarkable success.
And, it works for Artificial Intelligence as well; a topic every business and IT leader is fascinated by, and not just occasionally, followed by silence and procrastination, but regularly, because it turns out to be difficult to articulate next steps and tangible action.
Clearly, there are plenty of examples of AI applications that have a low complexity and deliver real benefits. Take a look at our recent report Turning AI into Concrete Value, that highlights dozens of these.
Still, having a look at how Amazon deals with the topic is quite instructional in itself. If you want to understand what an “AI-first” enterprise consists of, look no further: Amazon has convincingly infused literally all aspects of its business with AI.
Its recommendation engine becomes more and more spot-on, to the point that it will be able to identify products and services that you really, desperately, want before you know it yourself (psychic pizza, anyone?). Its warehouses are manned by autonomous, AI-driven robots. Its delivery drones completely rely on AI too. Amazon Alexa’s AI-based conversational system is getting better and better at understanding speech, and it does a pretty convincing job at generating it as well.
The Amazon Web Services cloud is built on a brilliantly designed hardware and software infrastructure, including AI that optimizes its performance and prevents it as much as possible from malfunctioning and breaches. Oh, and being the entrepreneurial retailer that they are, Amazon will also sell you all of their AI technology to use for your own purposes.
All of this AI goodness comes fluently together in the Amazon Go store, where different AI applications are used to the full extent to enable a literally frictionless shopping experience, without a check-out or anything else that might annoy you in getting what you want.
In retrospective, it’s fascinating to see how visionary Amazon has been with its Mechanical Turk “artificial” intelligence. Launched more than 12 years ago when the industry was still recovering from yet another AI winter, it already published a catalogue of web services to match supply and demand for “human intelligence” services. Hidden behind the API is a global crowdsourced community of real people, picking up and delivering Human Intelligence Tasks (HITs). In 2005, many of these HITs—such as image recognition, audio and video analysis, sentiment detection, and natural language understanding—indeed could not be effectively delivered by technology. Nowadays, AI—with its powerful smart automation and cognitive capabilities—can routinely deal with it. Lots of low-hanging fruit for the picking.
Makes you wonder what’s next though. With rapid advances in deep learning and reinforcement learning, AI will go way beyond what we would consider HITs. It will be able to combine training data from a variety of sources and in volumes and frequencies that humans simply are not able to absorb; not even with help from statistics, logic, or algorithms.
It’s this exotic, out-of-this-world potential of AI that will provide the material for new products, services, processes, and even hacked business models that we deemed impossible before (sure, let’s use that word “disruptive” one more time—for old times’ sake).
So, AI comes in many different flavors—from automating simple human tasks, to augmenting humans in their work with cognitive capabilities, all the way to exploring the unknown and enabling the unthinkable. No need for awkward silences in your innovation discussions: inspiration is all around and we can learn from the best.
Alexa, hold that thought.