Where AI Gives a Competitive Edge

Use of Artificial Intelligence (AI) is growing. According to International Data Corporation (IDC) forecast statistics, spending on the technology will reach $97.9 billion in 2023, which is two and a half times what it was in 2019.

David Schubmahl, IDC research director, said, “The AI market continues to grow at a steady rate in 2019 and we expect this momentum to carry forward,” adding, “The use of artificial intelligence and machine learning (ML) is occurring in a wide range of solutions and applications from ERP and manufacturing software to content management, collaboration, and user productivity. Artificial intelligence and machine learning are top of mind for most organizations today, and IDC expects that AI will be the disrupting influence changing entire industries over the next decade.”

Who is leading AI spending?

According to IDC: “Spending on AI systems will be led by the retail and banking industries, each of which will invest more than $5 billion in 2019. Nearly half of the retail spending will go toward automated customer service agents and expert shopping advisors & product recommendation systems. The banking industry will focus its investments on automated threat intelligence and prevention systems and fraud analysis and investigation. Other industries that will make significant investments in AI systems throughout the forecast include discrete manufacturing, process manufacturing, healthcare, and professional services. The fastest spending growth will come from the media industry and federal/central governments with five-year CAGRs of 33.7% and 33.6% respectively.”

Marianne D’Aquila, IDC research manager in the Customer Insights & Analysis department said, “”Artificial Intelligence (AI) has moved well beyond prototyping and into the phase of execution and implementation.” She also remarked, “Strategic decision makers across all industries are now grappling with the question of how to effectively proceed with their AI journey. Some have been more successful than others, as evidenced by banking, retail, manufacturing, healthcare, and professional services firms making up more than half of the AI spend. Despite the learning curve, IDC sees higher than average five-year annual compounded growth in government, media, telecommunications, and personal and consumer services.”

The biggest AI use cases

The three largest use cases for AI currently are: automated customer service agents, automated threat intelligence and prevention systems, and sales process recommendation and automation. But in the future, the use cases that will see the fastest spending growth over the 2018-2023 forecast period are automated human resources (43.3% CAGR) and pharmaceutical research and development (36.7% CAGR). However, eight other use cases will have spending growth with five-year CAGRs greater than 30%.

Where is AI investment happening?

According to IDC, the United States will deliver more than 50% of all AI spending throughout the forecast, led by the retail and banking industries. In second place is Western Europe where banking and discrete manufacturing will show the biggest demand. China will be the third largest region for AI spending with retail, state/local government, and professional services being the leading users, and Japan is another country to watch as its AI use is predicted to have a 45.3% CAGR growth in spending on AI up to 2023.

AI Speeds up Drug Design as World Searches for Covid-19 Cure

The use of Artificial Intelligence (AI) is surging, and one area in which its use is even more important in 2020 – The Year of a Global Pandemic –, is in health technology, or healthtech.

Berlin-based, non-profit think tank dGen has just released a new report, AI, Privacy, and Genomics: The Next Era of Drug Design”, which looks at the issue of privacy and access to genetic data for companies using AI to speed up and improve drug design.

With articles about work on a vaccine for Covid-19 flooding newspapers every day, most people are now more aware of the typical timelines involved in creating new drugs. They certainly don’t appear overnight: as the dGen report states, “the average drug today takes 10-12 years and cost $2 billion.” However, the arrival of the new coronavirus has forced researchers to think more in terms of 12-18 months, which is like exchanging a leisurely world cruise for supersonic flight.

Enter AI, which in 2020 is only just entering drug R&D where it is being used to test and improve candidate drugs before they can be fully accredited by regulators, such as the FDA in the USA.

But there is one area of concern: genetic information is central to many AI-enabled drug discovery startups. To expand this innovation, a number of issues with using genetic data must be resolved. The dGen report lists these as:

  • ownership
  • secure storage
  • availability to multiple research parties.

In order for all of us to accept the wider use of AI in drug design, privacy concerns must be addressed using the privacy-preserving techniques in Machine Learning. These allow researchers to process genetic material without fully revealing its source.

While this is crucial for privacy, the techniques do not address the issue of ownership, or ways to audit the system. What the dGen report proposes is a decentralised pan-European biobank network that makes information available to researchers, but all access requests have to be logged. In that way, we all know who has looked at our genetic data. Furthermore, it would allow us as individuals to grant or deny these requests and track the use of our information.

dGen’s Top Predictions for 2030

Based on better privacy-preserving technologies and an access network, dGen’s top predictions for 2030 are:

  • Better collaboration networks will emerge.
  • Genetic privacy laws will be overhauled.
  • AI will become a fundamental part of drug discovery.
  • Pharmaceutical giants won’t be toppled, but they won’t get out unscathed as biotech startups take the field.

The views of industry leaders

It is also interesting to note the responses to the dGen report from those working in AI and healthtech. The think tank interviewed industry leaders from Aidence, Gero, Alphanosos, e-Estonia, Qunatlib and Turbine amongst others.

Maxim Kholin, Gero Co-Founder said,‘We believe that AI can accelerate the drug discovery process by proper understanding of human diseases from large biomedical data. The data-driven approach should help establish the genetic determinants and molecular markers of the disease’. While, Pascal Mayer, Founder of Alphanosos, which is specialised in plant-based pharamaceuticals, told dGen: ‘While currently working really well on bacteria, we are confident AI-enabled plant-based drug discovery shall be successful in fighting viruses as well’.

This work is important for all of us who have an interest in how emerging technology can contribute to a decentralised future in Europe and what this might mean for people, society, private entities, and the public sector over the coming decades. It is, of course, of a signifiant interest to us all right now, as the search for a Covid-19 cure continues.

For a copy of the Full Report contact:

Francisco Rodríguez

francisco@dgen.org

7 Trends of the 4th Industrial Revolution?

Things are moving fast in our world, with technology leading the transformation of businesses, job and society generally. The next decade is going to define the latest Industrial Revolution and there are a number of technology trends that are playing a core role.

Artificial Intelligence

Artificial intelligence (AI) and machine learning refer to the ability of machines to learn and act intelligently. We are already using it at home as Amazon presents us with products we might be interested in based on previous purchases. But it is going to get even bigger, and we will see it carry out a wide range of human-like processes, such as seeing (facial recognition), writing (chatbots), and speaking (Alexa).

The Internet of Things

This refers to everyday devices and objects that are connected to the Internet and which gather and transmit data. We have smartphones already, but soon we will have smart fridges, and smart everything.

Big Data

This is all about the explosion in the amount of data that is being generated as more ‘thing’s and services are digital. By analysing masses of data with intelligent algorithms, companies can identify patterns and relationships that they couldn’t see before, allowing them to offer more personalised services.

Blockchain

Although blockchain has been around since 2009, it is still expanding and changing its uses beyond cryptocurrency. Expect to see blockchain being used for storing, authenticating, and protecting data, and transforming banking.

Robots

Robots are intelligent machines that can understand and respond to their environment and perform routine or complex tasks by themselves.

We will see more Cobots in the next few years. These enhance the work that humans do and interact safely and easily with the human workforce. They are your new work colleagues!

5G Networks

5G is the fifth generation of cellular network technology, and it will deliver much faster and more stable wireless networking. It is necessary for all the ‘smart’ things we’re going to have, as mentioned above.

Quantum Computing

Quantum computing will make our current systems look as though Fred Flintstone used them. It will completely redefine what a computer is, and is bound to be a game changer in the world of AI.

Technology will drive this decade

This year the global pandemic has forced most of the world to rely more on technology. With more people working from home — something that is almost certain to become the new normal for those who can perform their job remotely –plus the need for more apps to assist with work and in monitoring public health, there has surely never been a bigger opportunity for the tech sector.

Bernard Marr in Forbes has identified 25 ways in which technology will define this decade, including an area I am particularly interested in, which is Artificial Intelligence. This he believes, and I agree, will be a driving force behind many of the other tech solutions.

AI will be central to the development of the Internet of Things, which is the ever-growing number of “smart” devices and objects that are connected to the Internet. We will also see a boom in ‘wearables’ that will go way beyond the current fitness trackers. There will be an industry dedicated to “wearable technology designed to improve human performance and help us live healthier, safer, more efficient lives.”

Big Data refers is another feature of the next ten years. It refers to the massive amount of data created worldwide and we’ll see advance augmented analytics emerge to deal with it, supported by AI.

Blockchain is another important tool that could revolutionise many parts of business, particularly as it facilitates trusted transactions, as Marr says.

For those of you who are of a sci-fi frame of mind, there will be “digitally extended realities. These will include virtual reality, augmented reality, and mixed reality, all aimed at enhancing the virtual experience.

The concept of “digital twins” is also pretty futuristic. Marr explains: “A digital twin is a digital copy of an actual physical object, product, process, or ecosystem. This innovative technology allows us to try out alterations and adjustments that would be too expensive or risky to try out on the real physical object.” The potential applications are numerous, from the arts to science and more.

I’m sure you’ve guessed that there will be more Alexas and Siris, with chatbots being our first point of customer service for many brands, and facial recognition will grow, although the regulations about its use do need to be ironed out.

Many of us are also waiting for the quantum computers to be unleashed, and that could happen before 2030.

You can read about all the other opportunities at Marr’s Forbes article (linked above), or in his book, Tech Trends in Practice: The 25 Technologies That Are Driving The 4th Industrial Revolution.

Prepare yourself for what’s coming!