As COVID-19 began surging across the globe in the early months of 2020, it almost immediately flooded health care providers with challenges and demands the industry had never before seen. Suddenly doctors' offices were closed to patients, hospital emergency departments and ICUs were running out of beds, and healthcare workers were battling a new and unknown disease. Today, in the waning months of 2021, some of these pressures have eased, while others keep coming back along with the Delta variant. Either way, the insights they produced remain vitally important. Lessons learned during this stressful time have already inspired fundamental changes in healthcare--changes that are here to stay.

Since the 1970s, digital technologies have changed teaching, learning and assessment. From the advent of the personal computer in the late 70s and early 80s, the explosion of the internet in the 90s, to the period of ubiquitous computing through the smartphone and all that came after, we have seen a fundamental change in the way we engage with teaching, learning and assessment through the digital medium. When computers first appeared in our classrooms, they gradually superseded older legacy technologies. Over time, the first iteration of computers and associated software was likewise replaced by newer networked devices and software applications. The hardware refresh cycle continues at pace today, and software developments appear to be accelerating further still. Despite these developments, it is only the medium of teaching and learning that has changed.

The rapid development of converging technologies is bringing about fundamental changes to the insurance industry. In the long term, organisations that are slow to embrace these new technologies will struggle to compete and to retain their place in the market. In the insurance sector, the use of technology to innovate or disrupt is known as'insurtech'. This is an elastic term that takes in the use of new technologies by both start-ups and incumbent insurance companies to transform access to and analysis of data, build new products, drive customer engagement and squeeze inefficiencies from the current insurance model. Technologies such as telematics, the internet of things including smart home technologies, aerial imagery and drone technologies are giving insurers new ways to access data while developments in artificial intelligence (AI), machine learning and natural language processing are enabling insurers to process, analyse and gain insights from these large data sources.

In 2013, the Oxford Martin School at the University of Oxford published a paper studying activities over the spectrum of employment that could potentially be automated by computers. While this is certainly contentious, given its potential impact on the human workforce, many businesses have already begun to take the road towards automation. For example, outside of the industrial sector, Pizza Hut has experimented with robotic servers, Amazon has opened several grocery stores with no checkout staff, while China has pioneered'cloud hospital' telemedical services as well as, more recently, robot-serviced field hospitals for coronavirus patients. One of the original premises of the IoT was to introduce a higher level of automation; while the impact of this was limited up until now, the pandemic will certainly lead many enterprises to examine what, and how processes can be automated in order to reduce any future business impact from similar wide-ranging events. Gregory Gundelfinger, CEO of Telna advises that "businesses will need to adapt their business models in order to remain operational and relevant in our rapidly changing society. This means adopting technology that supports automation and reliable connectivity."

The following is a guest post by Pete McCain, a technology startup enthusiast associated with App Velocity. If you would like to submit a guest post, please contact us. There was a time when we all were highly skeptical about online education because we couldn't fathom a computer screen replacing our classrooms and the education ideals that come with them. But now examining the impact of online education, we can clearly see how eagerly we've embraced the idea of e-learning. It has levelled up education in the developed parts of the world and democratized education where schools and teachers couldn't reach.

Arnand Rao: We are moving away from reading or learning a body of knowledge, whether its physics, chemistry, biology, to how do you learn about learning, how do you practically think about problems, breaking them down quickly to into different pieces to bring the right knowledge to bear. Those are some of the skills you will need. And also, how do you deal with people, how do you empathise with them. So, in addition to the content we are teaching, we also should be teaching and learning about new ways of solving problems using technology using people and all sorts of combinations. So, learning math at a very fundamental level; it is the underlying base.

Platinum Seed recently appointed Ally Behr as design director, as part of its strategy to expand its service offering and leadership team. Behr is responsible for the conceptualisation and execution of digital touch points for clients. She has worked on a multitude of international brands in a variety of environments, from conceptualising through-the-line campaigns, to operating within specialised teams that built complex products. Prior to joining Platinum Seed, Behr was an art director at Ogilvy & Mather, senior creative and user experience designer at Gloo. Artificial intelligence and machine learning is definitely the trend everyone is talking about, even though it been a part of our daily lives for years, from predictive text to chat bots.

In Munich, Germany, the technology conglomerate Siemens AG is betting $1.1 billion on digital technologies, such as the proposition that blockchain data can be leveraged by machine learning to improve the secure transmission of data used in energy trading. Siemens is welcoming its employees and independent firms to bid for the money if they are willing to research how Siemens can develop businesses that use artificial intelligence. Siemens is just one of a number of companies embracing machine learning--the combination of artificial intelligence and deep analytics that enables enterprises to make predictions on large amounts of data and allows developers to experiment by incorporating features like speech and pattern recognition, as well as statistical techniques, into their analysis. And HPE's recent announcement of "machine learning as a service" (MLaaS) is aimed at helping the process really take off. Speaking at HPE Discover Las Vegas 2016, HPE Executive Vice President Robert Youngjohns called machine learning and deep analytics the most fundamental change we're ever going to see.

In Munich, Germany, the technology conglomerate Siemens AG is betting 1.1 billion on digital technologies, such as the proposition that blockchain data can be leveraged by machine learning to improve the secure transmission of data used in energy trading. Siemens is welcoming its employees and independent firms to bid for the money if they are willing to research how Siemens can develop businesses that use artificial intelligence. Siemens is just one of a number of companies embracing machine learning--the combination of artificial intelligence and deep analytics that enables enterprises to make predictions on large amounts of data and allows developers to experiment by incorporating features like speech and pattern recognition, as well as statistical techniques, into their analysis. And HPE's recent announcement of "machine learning as a service" (MLaaS) is aimed at helping the process really take off. Speaking at HPE Discover Las Vegas 2016, HPE Executive Vice President Robert Youngjohns called machine learning and deep analytics the most fundamental change we're ever going to see.

Just as fintech is transforming the banking world, "insurtech" has set its sights on the insurance industry. There are firms like Trov, which provides insurance on-demand and enables consumers to catalogue insured belongings. Buzzmove uses home removals data to create a new distribution model for insurance – people are more likely to renew or buy insurance when moving house – and helps customers track the value of their assets. FitSense helps employers leverage data from wearable tech, while massUp capitalises on open APIs to connect insurers to retailers. As a consumer, you can cover your gadget at the point of sale – ideal if you know it might not be covered by your household policy. Start listing the players currently in the market, though, and while the added visibility and speed brought by innovative technology is evidently beneficial, "'disruption' can be a misleading word", says Jonathan Howe, UK insurance lead at PwC. "We take that to mean the whole industry has been thrown in the air and we've seen major new players emerge.