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Artificial Intelligence in times of Coronavirus
Artificial Intelligence is an ally in monitoring COVID cases and a weapon to create business digitization solutions
The world is in crisis due to the Coronavirus pandemic that has spread to several countries at an alarming rate. The economic effects of the spread of the virus, both on companies that are directly impacted, as well as the cascading effect of this impact, bring enormous challenges for governments, organizations and leaders.
I don't want to spread panic when I touch on this subject, quite the contrary, I want to bring relevant insights to business managers, and I will do it in the way that I can best contribute: presenting how Artificial Intelligence has helped or can help in times of crisis.
The uses of Artificial Intelligence that have made a difference since the beginning of the Corona Virus epidemic
Artificial Intelligence has already been used to monitor the epidemic very effectively. An algorithm developed by the Chinese technology giant, Alibaba, is able to diagnose with 96% accuracy whether a patient is infected with a corona virus in a matter of seconds, 20 to be more precise, using computed tomography images, much faster than the time of conventional methods that take an average of 15 minutes. The company must use computer vision and Deep Learning algorithms to find patterns apprehended in previously reported cases and use this knowledge to identify new cases.
Canadian company Bluedot has used artificial intelligence in another way by monitoring foreign language news, animal and plant disease networks and official proclamations to warn its customers in advance to avoid danger zones like Wuhan. The company managed to alert its customers as of December 31, 2019, before the information spread. The algorithm also accesses global airline ticket issuance data that can help predict where and when the new ones will be infected. Bluedot's algorithm correctly predicted that the virus would jump from Wuhan to Bangkok, Seoul, Taipei and Tokyo in the days following its initial appearance. Bluedot has made good use of Machine Learning algorithms to identify patterns and simulations to assess cities most likely to be contagious.
Bluedot explorer with real-time data and prediction algorithms
The Italian startup Paginemediche created a chatbot to interact and assess whether people have symptoms compatible with the Coronavirus, providing scalability to service people and bringing information quickly and efficiently.
Example of using Paginemediche chatbot
And the famous case of the South Korean biogenetics company, Seegene, which managed to get ahead and use its Artificial Intelligence algorithm to create in weeks (work that would take months), a test kit to identify the virus contamination. This allowed South Korea to control and reduce contagion much faster than other countries that have been through the same moment.
In Brazil, the Tribots (tribots.com.br) movement that works in the development of conversational solutions, created a chatbot to help clarify doubts about the very nice Coronavirus, in a simple format, objective that is helping the population in prevention. See: http://bit.ly/SobreCoronavirus
These are just a few examples of how AI has been used in a way to directly combat the epidemic and its spread.
How AI can help in times of crisis
Now, for most companies, in addition to the possible impact on the health of their employees, the major impact is the economic one. And in that sense there are also countless opportunities to use Artificial Intelligence.
Artificial Intelligence allows for cost reduction, resource optimization and organizational flexibility. The construction of digital assets allows access to the global market and the focus on regions that are recovering from the crisis, in addition to more easily enabling alternative and digital paths to important tasks.
One of the technologies linked to Artificial Intelligence, RPA, Robotic Process Automation, or Robotic Process Automation, allows the automation of repetitive tasks with a high degree of efficiency. The automatic sending of emails in a sales campaign, the analysis of information and the construction of automatic reports, the updating of information in systems, reading and checking of documents, just to name a few applications can bring speed and cost reduction in a moment where every penny matters.
The construction of digital assets such as algorithms for logistics, sales, operations, marketing, among others, and make use of a very current business model, Software as a Service, or SaaS, which sells the use of these algorithms as services in API format or customizable solutions creates greater flexibility in performance and a greater capacity for internationalization.
For example, if I want to maintain my sales activities even with the restriction of the circulation of people that can occur with varying intensities in different regions, I can migrate my channels with an emphasis on digital service, through Chatbots or through automation using RPA at all. my sales funnel.
If I need to reduce costs with rework and waste, I can create machine learning algorithms to identify patterns of failures and act assertively in maintaining manufacturing activities, for example.
We at I2AI have helped many companies in the use of Artificial Intelligence with a focus on optimizing and reducing costs and eliminating waste with very impactful results.
The secret to choosing good projects is to identify less complex opportunities where Artificial Intelligence can bring quick returns in relation to the necessary investments. And in our experience there is a lot of space, especially in the application of RPA, where the benefits are visible and the speeds and costs of implementation are quite adequate for the moment we are living.
If you haven't stopped to think about how to redesign your strategy to better face the crisis, the time is now, and I am sure that digital assets, especially Artificial Intelligence can help you a lot in this mission.
About the author
É sócio fundador da I2AI – Associação Internacional de Inteligência Artificial. Também é sócio-fundador da Engrama, sócios das Startups D2i e Egronn e investidor nas startups Agrointeli e CleanCloud. Tem mais de 20 anos de experiência em multinacionais como Siemens, Eaton e Voith, com vivência em países e culturas tão diversas como Estados Unidos, Alemanha e China.
Palestrante internacional, professor, pesquisador, autor, empreendedor serial, e amante de tecnologia. É apaixonado pelo os temas de Estratégia, Inteligência Competitiva e Inovação.
É Doutor em Gestão da Inovação e Mestre em Redes Bayesianas (abordagem de IA) pela FEA-USP. É pós-graduado em Administração pela FGV e graduado em Engenharia Mecânica pela Unicamp.
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