The COVID-19 crisis forced businesses everywhere to fast track their digital transformation efforts. Faced with the stark choice of becoming a digital-first business, or having no business at all, companies that were previously behind the curve had to implement everything from remote working to entire digital storefronts in a matter of days. According to research by McKinsey, the digital initiatives unleashed in response to the pandemic leapfrogged seven years of progress in a matter of months as companies acted 20 to 25 times faster than they had believed was possible. In the process, this acceleration of digital during the crisis brought about a sea change in executive mindsets with regard to the role of technology in business. Fast forward to today, and corporate leaders are now investing in technology for competitive advantage, refocusing their entire business around cutting-edge technologies, and initiating a business culture where experimentation and innovation is actively encouraged.
Before the global pandemic struck in 2020 and the world was turned on its head, artificial intelligence (AI), and specifically the branch of AI known as machine learning (ML), were already causing widespread disruption in almost every industry. The Covid-19 pandemic has impacted many aspects of how we do business, but it hasn't diminished the impact AI is having on our lives. In fact, it's become apparent that self-teaching algorithms and smart machines will play a big part in the ongoing fight against this outbreak as well as others we may face in the future. AI undoubtedly remains a key trend when it comes to picking the technologies that will change how we live, work, and play in the near future. So, here's an overview of what we can expect during what will be a year of rebuilding our lives as well as rethinking business strategies and priorities.
Across industries, value chains are facing increasing uncertainty from climatic anomalies, market volatility, and the COVID-19 pandemic, among other factors. Industries as diverse as agriculture, oil and gas, and mining face essentially the same problem: they need the ability to both run with increased efficiency and recover quickly from unforeseen or unexpected challenges. But these two goals often conflict. If companies simply increase production levels, they'll inevitably run into bottlenecks--and if failures occur that worsen those bottlenecks, the entire network can slow down and become less resilient. For more on how COVID-19 has affected supply chains, see Knut Alicke, Richa Gupta, and Vera Trautwein, "Resetting supply chains for the next normal," July 21, 2020. Resolving this conflict presents several challenges.
As vaccine production & procurement processes are ramping up, the distribution of vaccines is a thing of concern. As large amount vaccine units roll out, the first step is strategic & wise distribution among regions, considering conducive & causative factors raising the urgency of requirements. For this, organizations & governments may look upon the predictive suggestions  backed by data to chart out further plans. Many countries, particularly those in the developing world, where governments are struggling to procure vaccines to vaccinate their residents. One of the decisions to be taken strategically is the wise & calculated distribution of the vaccine received. Although few countries are actively trying to increase vaccination rates, the overall 56% world population is yet to take their first vaccine dose.
Artificial intelligence is more present in our lives than ever: it predicts what we want to say in emails, helps us navigate from A to B and improves our weather reports. The unprecedented speed with which vaccines for covid-19 were developed can also partly be attributed to the use of AI algorithms that rapidly crunched the data from numerous clinical trials, allowing researchers around the world to compare notes in real time. The data sets used to build AI often aren't representative of the diversity of the population, so it can produce discriminatory practices or biases. One example is facial recognition technology. This is used to access our mobile phones, bank accounts and apartment buildings, and is increasingly employed by police forces.
In December 2020, UNESCO organized the International Forum on AI and the Futures of Education'Developing Competencies for the AI Era' and produced a synthesis report. UNESCO carried out two surveys on government-approved AI curriculum targeting UNESCO Member States and non-governmental organizations, which provide AI curricula. The results of these surveys will inform the development of a guiding framework on AI competencies. UNESCO launched a call for applications on the use of AI to support education during the COVID-19 pandemic by non-governmental agencies and a survey for UNESCO Member States. The results of this exercise will inform a report on the main areas of AI use in education and help examine the effectiveness of these tools in supporting education during and beyond the COVID-19 learning crisis.
Retailers are now adopting micro-fulfilment strategies for instant consumer gratification and improved product accessibility, as a competitive advantage. The supply chain industry grew during COVID-19 crisis and so did the need for faster operational processes and automation of human tasks. As part of it, the logistics sector is struggling to meet the growing consumer demands, high labour costs, regulatory measures, and siloed data, whilst complying with a dynamic environment. Complexities woven in the industry are not just occasional but tend to create a ripple effect across the infrastructure. Ultimately, the warehouse workforce strives to meet customers' requirements by managing incoming orders through multiple layers, regardless of inventory processes.
Microsoft have added a new aspect to their AI for Good Projects and have released a first-of-its-kind artificial intelligence model that will help combat the illicit trade of illegal animal trafficking – and it is being praised by everyone, including Prince William himself. Project SEEKER, as the project has been aptly named, was designed and trained to identify animals or animal products that are used in medicines. Illegal Wildlife Trafficking is a $23 Billion industry – it impacts well over 7000 different species and plants with one of the biggest transportation manners being that of storing animals in cargo or shipping them in planes and on boats. We saw a huge decrease in the number of trafficked animals during the height of the COVID-19 pandemic when almost all countries had shut their borders! TechQuarters are a Gold Microsoft Partner and award-winning IT Managed Services Company in the UK – they have noted that this kind of technology will open up new doors and possibilities for all of us in the future. Project developers spent hundreds of hours uploading images of animals and animal parts and manually labelling them so that the AI model could learn to automatically identify these items – it is easily installed in luggage and cargo scanners at airports, border patrol sites, or shipping ports and will be able to automatically alert authorities if any illegal substance is detected.
Revenue NSW has turned to using AI and data analytics to help it work through compliance efforts to assess whether people were overpaid or if there were fraud cases as a result of recent COVID-19 businesses grants that were provided by the state government. "[We're] using a rule-based system where we can enhance irregular patterns in the data that we're seeing and quickly move them through a modelling process into investigation for fraud and compliance," Scott Johnston, Revenue NSW deputy secretary and State Revenue chief commissioner, told the audience at the 2021 digital.NSW event. "A quarter of a million businesses received grants through this process. There's extreme urgency to ensure that people got the money that they needed to but also to do it in the right way, and a lot of responsibility over the next six months and 12 or more will fall on us to effectively drive this this effort." This will not be the first time Revenue NSW has turned to AI and data analytics.