Points to consider when investing in AI
Implementation of the multifactorial capabilities of AI into reality can both significantly improve the quality of life of many people and also bring profit. Let’s discuss the most interesting trends in the AI world to figure out what projects are worth investing in.
Incredible growth in AI investment
Investment in AI development and implementation projects grows annually — over $46.5 billion in the first quarter of 2018. Robots with high intellectual development and digital technology in the field of healthcare were the most attractive for investors.
Most of all the investments in AI projects are made by American investors — $21.9 billion in 2018 and an unprecedented record of $26.6 billion in 2019.
Many large companies such as Nvidia, Google, Amazon, Microsoft and IBM invest heavily into AI technologies, and their investments are already making profits. For example, the value of Alphabet from Google or Amazon service today is estimated at $1 trillion — this could not be achieved without the development and implementation of AI. Even young companies, such as Alteryx, developing AI technologies for data processing and analytics, bring profits to their investors. Its success in machine learning can predict a revenue growth of 30 % by 2021.
Areas of Interest
Until recently, significant sectors of the economy developed exclusively under the control of the state, but now the business community plays a big role in their development. For example, since 2014, intensive investments in space programs by private investors have begun, and by 2018, total volume of venture investment in space projects reached $3.25 billion dollars. Major entrepreneurs such as Elon Musk (founder and chief engineer of SpaceX) or Jeff Bezos (founder and owner of the aerospace company Blue Origin) have been investing in this area for several years. It was private investments that made significant progress in space exploration.
A trend of growth in investment into the AI technology in healthcare is also of particular interest. In 2015, only 100 million dollars (49 deals) were spent by venture investors for the development of medical AI algorithms, and in 2017, it was $1.3 billion already (103 deals). In 2019, interest in AI in the field of healthcare increased even more — investments in this sector of the economy amounted to $4 billion (367 deals). This area of interest is attracting more and more private investors.
AI-based solutions help to improve the quality of medical care as well as reduce its cost. By reducing their expenditures through the introduction of AI technologies, healthcare providers get the opportunity to increase profits by 2–3 times.
Competition on the AI market
Google and Amazon invest tens of billions of dollars into AI development and research. Huge enterprises have access to large amounts of data and established markets. However, that doesn’t mean start-ups cannot compete with them.
Start-ups and private AI developers have a number of advantages:
● willingness to provide services for mid-size companies and small businesses that do not have enough resources and capacity to develop their own AI solutions;
● quality and diverse data for AI training (their own, generally accessible via Internet, and data from their customers). AI can collect and analyze enormous amounts of information (big data) and self-learn on their basis.
In addition, some large corporations are increasingly engaged in partnership relations with AI development startups. They are looking for novel projects that can help them compete with new companies in the AI market. For example, NVIDIA has partnered with Paige.AI, which has developed an AI algorithm for cancer diagnosis.
Key components of success
The AI market offers a huge number of PC-based tools and useful applications daily. But only a few achieve success on the international platform and make decent profits. What should you pay attention to when choosing an object for investment?
The main components of the promising AI project are:
● large and high quality data sets for AI training;
● sufficient processing power of the algorithm;
● engineering talent of developers;
● practical importance (acceleration, automation and improvement of the quality of work);
● wide applicability (cross-platform).
When choosing medical AI, it is also worth paying attention to the clinical data on the efficacy and safety of the algorithm in real-world conditions.
Investing in healthcare
The growth of investments in AI technology in healthcare can be explained by the following:
● growing demand for new effective medicinal products;
● growing demand for medical services, including preventive examinations and early diagnosis of diseases;
● the need to reduce health costs;
● lack of healthcare professionals.
In addition, AI can help automate administrative processes and find solutions to personalize treatment.
According to a survey conducted by a major medical company Optum in 2019, many U.S. institutions already use AI algorithms in their work or are at the late stages of the AI implementation strategy.
Founder and CEO of the fast-growing healthcare IT-startup Biofourmis Kuldeep Singh Rajput believes that investment in the health care system is not only useful, but also profitable. Prices for the purchase of shares in this area have not yet managed to rise too high, but the funds spent on the development and implementation of AI in healthcare are already making profit to their depositors.
Half of the respondents of Optum 2019 survey believe that investment in AI will recover quickly enough — within 3 years. And profits from investments in healthcare will be the driving force for new investments in the development of medical AI.
Prospective direction
One of the important areas in the healthcare sector, in which the development and implementation of AI has not only significant prospects but also high social importance, is oncology. FDA had already approved and released to the market AI applications for digital image-based cancer diagnosis such as:
● Arterys Oncology DL (analysis of CT and MRI images);
● Koios DS for Breast (ultrasound evaluation algorithm);
● QuantX (uses MRI data) etc.
They already help specialists to improve their productivity and reduce the risk of diagnostic errors.
Histological studies of biopsy and operative materials play a special role in cancer diagnostics. Currently, active development and clinical studies of AI are ongoing. The purpose is to teach AI to recognize malignant neoplasms and classify the changes found in test material.
Our company PathVision.AI has developed its own neural network, which applies markings to digital images of histological samples exactly as a pathologist. This neural network is trained to detect prostate cancer and classify detected changes according to the Gleason score (a score for assessment of tumor grade and for treatment planning). Its introduction into clinical practice will significantly accelerate and improve the accuracy of prostate cancer diagnosis.
We employ a responsible approach to each stage of creation of a really efficient algorithm. Our neural network training is based on a large amount of quality data under the guidance of talented specialists. And it is planned to verify its efficacy in real conditions in a multicenter study.
After passing all the necessary tests, AI from PathVision.AI can become a good assistant for any medical institution. PathVision may be installed on histology scanners and computers, and can work via a web interface, making this application extremely convenient.
Further development of AI technologies in this direction will not only improve the accuracy and speed of diagnosis of malignant neoplasms, but it will also help to effectively use healthcare resources.
Conclusion
Currently healthcare is a sector of the economy with a steady demand for goods and services, including digital technologies. An aging population, growing prevalence of chronic diseases and comorbidities, and improved patient awareness combined with expectations of high quality medical care ensure a constant increase in demand in the healthcare market.
The gradual digitalization of all economic sectors increases the need for the development of medical IT technologies, including AI. However, today, consumer requests remain not fully realized due to insufficient funding of healthcare and low efficiency in the development of public funds. In these circumstances, the role of private investors, willing to invest in innovative developments, as well as of startups engaged in the development of digital technologies, becomes particularly important.
