Technology Innovation is Supporting the Digital Ad World

2021 so far is showing an acceleration of the strong growth trend in Digital Advertisement. As businesses re-open worldwide and previously canceled campaigns are resumed, advertisement budgets have been increasingly directed towards Digital Ad because the use of social media platforms and streaming services have risen almost everywhere.

Digital vs. Traditional Ad Spending (US)

Source: eMarketer

Not surprisingly, the main beneficiaries in the Digital Ad ecosystem are Alphabet, Facebook, and Amazon, which all reported strong growth in Ad revenue in 2020. Among these, Alphabet continues to dominate the Digital Ad market: In 2020, Google accounted for about 29% of the total Digital Ad revenue in the US, followed by Facebook and Amazon with 25.2% and 10.3% respectively.

US Digital Ad Revenue Share, By Company, 2019 & 2020

% of Total Digital Ad spending

Source: eMarketer

Google built its success in Digital Ad by leveraging AI software to collect and integrate data from users in a more sophisticated and faster way. While Google’s platforms connect businesses with billions of people every day through Search and YouTube, AI helps them to create highly tailored content based on consumers’ needs and preferences of the moment.

With an impressive 1.87 billion daily active users in 1Q21, Facebook can count on one of the largest and most diverse advertising audience ever and collect a huge amount of data for the benefit of advertisers. Facebook also introduced innovative features to its Ad service: The use of Machine Learning helps determine the likelihood that a given user will act as the advertiser wants, such as visiting the advertiser’s website, installing their app, or buy a product. And then, the algorithm will rank the quality of Ad content through an Ad quality score so that the advertiser can fix the campaign following the best way to achieve his goals.

In recent years, Amazon’s Ad business also experienced a tremendous growth, mainly fueled by the acceleration of online shopping: According to EMarketer, Amazon advertising revenue in the US will surpass $20B in 2021. To keep up with the competition, the e-commerce giant also implemented an AI driven algorithm which analyzes real-time data generated by shoppers’ behavior, allowing advertisers to provide specific content to a narrowly targeted audience.

Digitalization is changing consumers’ behavior and companies must be increasingly data-driven to be able to communicate with people who spend more time navigating through the Internet while scrolling social media, checking emails, or reading the news. Digital Ad is becoming mandatory for companies to attract new customers and build a relationship with their brand.

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The information in this article should not be regarded as a description of services provided by Delian Partners SA. The opinions expressed in this article are for general informational purposes only and are not intended to provide specific advice or recommendations for any individual or on any specific security or investment product. It is only intended to provide education about the financial industry. The views reflected in this article are subject to change at any time without notice.

From Work Automation to RPA: A Revolution in the Digital Workers’ Era

In recent years the level of interest in the Robot-as-a-Service ecosystem has increased together with the acceleration of digitalization worldwide. Compared with Traditional Automation, where a machine’s software is programmed and updated by humans to execute specific repetitive tasks, Robotic Process Automation (RPA) is run by an Artificial Intelligence-powered software that allows a machine to autonomously learn and mimic user’s actions and subsequently execute a high volume of repetitive tasks and transactions, with limited human interaction.

RPA is bringing organizations into a new automation era. Digital robots can do a wide range of tasks in a faster and more efficient way than humans. At the same time, with a higher degree of accuracy, they help organizations to reduce workflow costs while improving productivity.

UiPath is among the fastest-growing RPA software Companies in the world. The company developed a high-scale automation software solution for enterprises which operate in different sectors – such as healthcare, finance, or manufacturing, to help them automate repetitive and boring office tasks: By combining different capabilities of AI, Machine Learning, and Deep Learning, the UiPath RPA system can save organizations million-hours of work office and allow employees to be focused on more important things to do.

Another example is Nintex, a global management and automation system developer which provides companies with an RPA bot to control and orchestrate workflows through a simple web interface. Nintex RPA software uses “digital workers” to perform actions similar to human workers, but non-stop, at a higher speed, and without errors, by replicating the same mouse clicks performed by humans. In summary, tasks delegated to the RPA bot interact with apps, systems, websites, and services, allowing people to focus on more relevant aspects of their job.

RPA represents a fast-growing segment as businesses need automated technology to interact more efficiently with their customers and process complex, data-hungry tasks in a faster and more efficient way. According to Gartner, the RPA industry is expected to grow at double-digit rates through 2024. The addressable market is huge, as RPA could disrupt data collection, data processing and predictable physical activities which collectively represent $1.3tn in wages in the US and 51% of time spent in US jobs. As an example, 70% to 80% of both front and back-office processes could be automated in the future.

Of course, human employee performance continues to be critical for the correct functioning of business operations. But RPA is going to be a key component to automate time-consuming processes, limit repetitive tasks, enable quick data entry, and ultimately provide a competitive advantage in the marketplace.

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The information in this article should not be regarded as a description of services provided by Delian Partners SA. The opinions expressed in this article are for general informational purposes only and are not intended to provide specific advice or recommendations for any individual or on any specific security or investment product. It is only intended to provide education about the financial industry. The views reflected in this article are subject to change at any time without notice.

Tech innovation is shaping the future of the healthcare sector

Historically driven by analog processes, healthcare activities have been significantly altered by the technology revolution. The increasing application of Artificial Intelligence (AI) systems is becoming more common in the healthcare industry and is helping healthcare businesses to be faster and more efficient.

Already pre-pandemic, about 80% of hospital leaders said cloud investments were a moderate, high, or critical priority for 2020. Going forward, the convergence of Artificial Intelligence (AI), Blockchain, and the Internet of Things (IoT) will further accelerate innovation adoption and related applications in the healthcare realm.

Technologies like Cloud computing, AI, IoT and machine learning are disrupting the health market and providing patients with new innovative services: for example, by engaging with digital providers, today patients can receive personalized medicines tailored to their specific needs, lifestyles, and genetic code, or can be visited by doctors directly through their smartphone.

Population aging around the world is another major tailwind for digital, patient-centric healthcare services. According to the World Health Organization (WHO), there were 703 million persons aged 65 years or over in the world in 2019. The number of older persons is projected to double to 1.5 billion by 2050. Technological advancements in screening processes, smartphones and wearables can bring point-of-care testing to the patients and represent a strong opportunity for providing sensitive, low-cost, rapid, and connected diagnostics.

There is increasing awareness that AI applications enable to analyze patient's health conditions and identify anomalies at a speed that humans cannot achieve, helping physicians to optimize and avoid time-consuming tasks, and reduce margins of error of diagnosis.

For example, today AI is already just as capable as (if not more capable than) doctors in diagnosing patients heart diseases, blood infections, and detect signs of potentially cancerous cellular growths. IBM’s AI program called Watson was recently challenged to analyze the genetic data of tumor cells. The human experts took about 160 hours to review and provide treatment recommendations based on their findings. Watson took just ten minutes to deliver the same kind of actionable advice.

Despite the rapid advancements in AI and machine learning in HC, we are still a long way from a total replacement of human intervention in medical processes. A research from Harvard showed that patients are reluctant to use health care provided by medical artificial intelligence even when it outperforms human doctors. The main reason is that patients believe that their medical needs are unique and cannot be adequately addressed by algorithms. For this reason, patients were less likely to utilize AI based services and wanted to pay less for it

The most likely evolution is that doctors will be supported by AI to perform repetitive tasks and increase quality of diagnosis at a fraction of time and costs. A recently developed machine-learning algorithm based on deep learning nearly matched the success rate of a human pathologist in interpreting pathology images, at about 96% accuracy. But the truly exciting thing was that combining the pathologist’s analysis the AI diagnostic method, the result improved to 99.5% accuracy,”

In summary: when it comes to healthcare, implementing AI solutions and machine learning will not necessarily mean replacing doctors, but optimizing and improving their abilities. The convergence between the healthcare industry with AI, Cloud computing, IT, and machine learning systems will further catalyze new innovative applications, providing patients with an early and accurate response to treatment and enabling healthcare organizations to reach new quality standards at a lower cost.

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The information in this article should not be regarded as a description of services provided by Delian Partners SA. The opinions expressed in this article are for general informational purposes only and are not intended to provide specific advice or recommendations for any individual or on any specific security or investment product.  It is only intended to provide education about the financial industry. The views reflected in this article are subject to change at any time without notice.