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Over a century ago, Sears grew from an upstart mail-order watch retailer to become one of the top retailers in the U.S., opening physical stores and expanding into other categories such as internet services, credit cards, and even insurance. Sears had a huge advantage in operational efficiency and customer insights over its competitors, knowing what customers were going to order next before their next visit. It was truly an “Everything Store”. Although its path sounds eerily similar to Amazon’s, Sears has recently become an albatross with 1,500 physical stores and no real differentiators to enable it to win, thus losing over half its market cap in the last few years.Armed with massive technology advantages in cloud computing and artificial intelligence (AI), Amazon has been able to achieve a leap in hyper-personalization and operational scale that traditional retailers never saw coming, until it was too late.
"Less than 50% of consumers trust their bank to keep their money safe"
And this story is repeating itself in every industry whether it’s delivery drones and self-driving cars, or robo financial advisors and virtual doctors. Just like with web and mobile, enterprises did not get a vote as customers and employees ultimately choose companies based on the digital experiences they deliver. Now the ante has been upped with emerging technologies like Augmented and Virtual Reality (AR/VR), Ubiquitous sensors, Machine Learning (ML), and Blockchain. Companies like Netflix, John Deere, and Progressive have made early bets on data and AI and are now reaping the rewards in terms of market advantages while other companies are playing catch up.
Information and Communication Technologies (ICT) is a term that has been used for decades to describe the intersection of IT and communication networks, especially more recently with internet and wireless systems. But as the infrastructure continues to deliver higher speeds and lower latency to more users, the new ICT is about creating Immersive, Cognitive, and Trusted applications.
Experiences are no longer just about translating existing interactions to screens, but rather moving these interactions to the ideal medium based on each user’s unique context. Context isn’t just about time and location, but also about situation and emotion. And the input side is morphing as well to include gestures (touch, swipe), biometrics (face, eye, thumb, heartbeat), and true haptics (real-time touch sensitive feedback) that will be fully unlocked with low-latency 5G networks. With the tech giants all making big investments in AR and VR development platforms (like Apple’s AR Kit), expect to see a new wave of immersive application on both the consumer and enterprise side like VR-based viewing of the 2018 winter Olympics in Seoul, Walmart and KFC training new employees using VR simulators, or Williams and Sonoma acquiring 3D Imaging and AR company Outward. This new generation of immersive apps will increase “bandwidth to the brain” while “humanizing” interactions with our surroundings.
It is hard to imagine an application getting built in the next 3-5 years that will not leverage ML or AI more broadly. The basic math has been around for decades. What’s different is the emergence of massive integrated data sets to train these models, a leap in computing horsepower like AI-optimized GPUs, and easy access to AI development platforms like Google Tensor Flow or Amazon AI.ML has already been a staple in areas like spam filtering and fraud detection, but is now being successfully applied in use cases ranging from diagnosing health conditions to personalized shopping. A Stanford AI program recently outperformed certified radiologists in diagnosing Pneumonia and Google demonstrated that deep learning could not only beat the best Go Player in the world, but with Alpha Go Zero, proved that reinforcement learning (the computer teaching itself) was more effective than being trained by humans. Marrying AI with immersive experiences opens up even more breakthroughs like the Amazon Echo Look which can capture an image of us with different outfits on, and anticipate what new apparel we need in our closet. It won’t be long until all of the routine decisions in our lives are performed by machines.
Living beneath the crypto currency craze is a powerful technology framework called Blockchain that provides distributed storage and processing along with consensus trust and immutability. These attributes make blockchain highly suitable for a range of multi-party enterprise applications such as product tracking, identity management, smart contracts, and financial settlements. Just like TCP/IP shifting the paradigm of communications, blockchain has the same game-changing potential. But it also has similar standardization challenges ahead of it with a wide range of architectural and platform choices such as bitcoin, etherium, hyperledger, blockstackall competing for attention. With the intensity of attacks and breaches like Equifax increasing, the need for trusted solutions is greater than ever. And it’s not just about traditional security. Less than 50% of consumers trust their bank to keep their money safe (E&Y, 2016 Survey). AI-based solutions will only make this worse as only 11% of consumers trust chatbots with financial information. Enterprises will need to be willing to explore more decentralized models like block-chain and user-driven privacy approaches to both increase their own level of resilience and increase the trust of end-users.
In order to “future proof” your organization to survive and thrive in the new ICT area, you will need to align your organization to both rapid changes in emerging technologies as well as user expectations.
1) Develop a two-speed business model for rapid experimentation at the pace of the external environment. This includes sandboxes where innovation opportunities can be piloted quickly and validated without disrupting production systems.
2)Extend your innovation ecosystem to co-create with innovators around the globe. This includes exposing APIs/ Data Assets and changing your legal, contracts and IT models to reduce the friction in working with external innovation partners (start-ups, universities, etc.)
3) Reframe your organization as a data company so that your business and technology efforts are focused on creating a data advantage through increased interactions and partnering to win the AI game longer term.
4) Redefine your critical skill areas around the 3Ds – Design, Development, and Data Science and recruit/ cultivate hybrid talent such as developers that can build AI-based applications.
5) Leverage the crowd to supplement your own skills and knowledge. Use crowd-sourced competitions like Kaggle or X-prize as a low-cost approach to tap into external data scientists and engineers around defined challenges.
The new ICT wave is coming and it means seizing the opportunity to disrupt your own business before others do it for you.
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