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Artificial intelligence and genome editing embody a new era of digitalization that is poised to spur the next stage of globalization and catalyze advancement, potentially for decades. This report explores what that means for society — and for investors.
A lot has changed in the 70 years since scientists first coined the phrase “artificial intelligence.” Here, we look at what AI is now — and where it’s going next.
Simply put, AI combines the fields of computer science, psychology, philosophy, and linguistics in an attempt to make machines do things that would otherwise require human intelligence.1
Today, researchers classify AI into Type 1 and Type 2.
Type 1 AI is based on capabilities and includes Narrow AI, General AI, and Super AI.
Type 2 AI is based on functionalities and includes Reactive Machines, Limited Memory, Theory of Mind, and Self-awareness.
Only recently have AI’s three key ingredients — big data, faster computers, and machine learning algorithms — converged to propel the technology increasingly into new uses.
A sign of increasing popularity: The forecasted cumulative global revenue of AI through 2025, by use case (in billions).
The bar chart shows the forecasted cumulative revenue from Artificial Intelligence from 2016 through 2025 in U.S. dollars. Static image recognition, algorithmic trading, and processing of patient data are the top three use cases.
There are three key areas where artificial intelligence and machine learning are likely to have a material impact in the near term.
Current forecasts estimate that this year alone, 90% of large and very large organizations will incorporate some version of robotic process automation, up from 55% in 2019.2 Not only do we expect this trend in AI-facilitated digital supply chain management to accelerate this decade, but a recent survey of process manufacturers suggests that two-thirds expect operations may be autonomously managed by 2030.3
AI is critical in the hardware needed for autonomous driving — namely, in the light detection and ranging (LiDAR) radar and cameras for vision, mapping, and computing power. Car-to-car communication is also possible through AI, where autonomous vehicles can alert others about upcoming congestion, construction, and accidents.
Rapidly advancing AI technology allows researchers to build maps of cell genomes and structures that aid in drug discovery. Over the next decade, AI may help scientists build proteins and maps to facilitate gene therapy treatment.
The best way to predict the future is to create it.
The discovery of clustered regularly interspaced short palindromic repeats, now known simply as CRISPR, ushered in the equivalent of the space race in the 21st century. Here’s what it is — and why it matters.
The short version: CRISPR allows for DNA editing — it can isolate and remove strands of DNA, and replace damaged DNA with healthy DNA.
The image show the process of gene editing using CRISPR/Cas9. In the first step, the Cas9 protein and the guide RNA locate the targeted strand of DNA. The strand is then cut, allowing scientists to edit the gene by either deleting the DNA, or modifying it.
CRISPR has ushered in a new era of life science.
Faster and more-precise techniques will define the next decade of gene therapy.
Today, researchers are focusing on site-specific recombinases, or SSRs, which edit DNA without relying on a viral vector to introduce new DNA at the break. With SSRs, locating and simply switching the orientation of a DNA segment — much like a railroad switch — has applications within synthetic biology in the use of biocomputers.
Advances in gene therapy will allow for new treatments for a broad spectrum of diseases.
| Research classification | Current and future areas of focus | Role of CRISPR |
|---|---|---|
| Cancer | Chronic Myeloid leukemia (CML), Ewing Sarcoma, anaplastic large cell lymphoma (ALCL), prostate and breast cancers | Prevention and treatment of various cancers by isolating and removing DNA mutations and replacing those sequences with normal, healthy DNA |
| Cardiovascular disease | Childhood onset cardiomyopathy, Marfan syndrome, congenital heart disease, long QT syndrome and other hereditary heart conditions | Repair mistakes in cardiac muscle tissue |
| Metabolic disease | Obesity, diabetes, and hyperlipidemia | Researchers are applying CRISPR/Cas9 technology to stem cells to understand better the molecular mechanisms of diabetes |
| Neurodegenerative disease | Huntington’s, Alzheimer’s and Parkinson’s diseases | Gene editing platforms are offering researchers a better method of studying gene functions and their impact on neurodegenerative diseases. |
| Viral diseases | COVID-19, HIV, human papillomavirus, Hepatitis B | Aside from CRISPR/Cas9 being an invaluable tool in constructing the COVID-19 vaccine, scientists have used gene editing to produce HIV-resistant T cells. |
| Hematological diseases | Hemophilia and Sickle Cell Anemia | Chromosome inversions, which can be corrected using CRISPR/Cas9, can affect how genes direct blood clotting. |
Wells Fargo Advisors Global Securities Research analysts believe that disruptive technology such as AI and CRISPR will touch multiple sectors and industries over the next decade. Here’s what to know.
| Artificial intelligence | CRISPR/genomics | |
|---|---|---|
| Sectors to benefit | Information technology
Communication services |
Biotechnology
Pharmaceuticals |
| Industries that may benefit | Software, hardware, semiconductors, semiconductor capital equipment, communications equipment
Interactive media services, telecom infrastructure |
Gene therapy, gene editing, gene silencing, cell therapy |
| Near-term expectations | Companies with “deep pockets” of capital and data should prevail. Existing R&D efforts give them a first mover advantage in data, alongside elevated levels of cash on balance sheets. | Growth of gene therapy and genomics-related companies expected to continue, aided by private equity funding. Significant R&D efforts alongside strategic investments. |
| Areas to watch | Impact of AI on cybersecurity, autonomous driving and Metaverse | Heightened M&A as large pharmaceutical companies collaborate or acquire smaller players and clinical data de-risks products under development. |
| Technology exchange-traded funds (ETFs) | Technology mutual funds (MFs) |
|---|---|
| Most technology ETFs passively replicate a particular technology index. One advantage of technology ETFs relative to other vehicles is that they provide investors with instantaneous access and near instantaneous liquidity. ETFs also tend to charge low fees and have full, daily portfolio transparency. | The majority of technology MFs are actively managed. The relative opacity of MFs’ holdings (compared with ETFs’ holdings) shields some proprietary strategy features, allowing them to implement an effective, active investment approach. Their variety of investment strategies seek to outperform the broader technology market or a targeted technology segment. |
The full Transformative Technology report from Wells Fargo Investment Institute contains additional guidance and considerations for investors, including:
