Here’s how Artificial Intelligence will transform Pharma Drug Discovery, Work from Home, and Edge Computing in the coming year.
What were the golden periods of innovation in modern history? Significant innovation did not occur during phases of economic prosperity or when business was conducted peacefully.
Contrary to expectations, innovation has always flourished during times of deep economic turmoil or prolonged world conflicts. For example, if we look at the patents filed in the past 250 years, the biggest surge in inventions came during the Great Depression.
Economic historian Alexander Field considers the 1930s to be the most technologically progressive decade of the 20th century. The Great Depression produced several important inventions such as the analog computer, jet engine, frozen food process, the electron microscope, radio telescope, and even the car radio.
If periods of crisis serve as catalysts for technological advancement, perhaps, there is a silver lining to the current global pandemic. The future might look back at the 2020s as the golden era when the most remarkable innovations in artificial intelligence went mainstream in the enterprise.
Artificial intelligence will transform 2021 by accelerating pharmaceutical drug discovery beyond Covid. It will change the face of telecommuting and will make devices around us truly intelligent through edge computing. Before we look at these trends, we must first recognize three critical changes in how business was done in 2020. This created the foundation for next year’s trends.
2020: The pandemic that created the perfect storm
Enough has been written about the different ways in which Covid-19 changed the world as we knew it. The coronavirus pandemic forced companies to take several extreme actions to stay in business. Let’s look at three such reactionary data initiatives taken by companies in 2020:
a. Companies became digitally transformed in days, not months
With the world going virtual, companies got a digital makeover. A survey by Baker McKenzie found that 58% of firms that had not begun a digital transformation program had fast-tracked it in 2020. McKinsey senior partner Kate Smaje says that organizations are now accomplishing in 10 days what used to take them 10 months.
With the entire business value chain getting digitized, this has eased collaboration amongst technology and business teams.
b. Companies slashed budgets, but increased their technology spend
As consumers cut spending and industries went into decline, enterprises announced steep budget cuts in 2020. Gartner’s 2021 Board of Directors Survey found that even as funding was slashed across the board, technology spending was increased by 6.9% on average.
Companies turned to technology and data analytics to save them during the pandemic. They tasked Chief Data Officers (CDO) with disruptive, executive responsibilities. CDOs were now asked to drive business innovation initiatives apart from their traditional focus areas such as data governance and compliance. They now led strategic engagements in areas such as product innovation and customer experience.
c. Teams realized that actionable insights from analytics required better quality data
“As the pandemic set in, businesses realized that they didn’t have the right data and were driving blind through the pandemic,” says Tom Redman, Founder of Data Quality Solutions. “Similarly, in their personal lives, people experienced bad data in new ways – ‘when was the store going to have toilet paper?’, ‘would their kids be back in school?’, and so forth.” This led many to think far more deeply about their need for high-quality data.
Hence, enterprises instituted processes to collect new data. They turned to public data sources to get additional market intelligence. Within enterprises, there was increased scrutiny on data quality. These actions led to the availability of higher volume, better quality data.
What are some of the critical ingredients for artificial intelligence to get adopted at enterprises? An overarching purpose, the right leadership, a healthy budget, good quality data, and an organization that embraces digital.
All these boxes have been checked off in 2020. Let’s look at how this will enable AI to deliver transformational value next year.
The top three artificial intelligence trends to watch out for in 2021
1. AI will transform drug discovery and development well beyond Covid-19
AI helped fast-track the Coronavirus vaccine tremendously, cutting timelines from 10 years to 10 months. Moderna has used a digital-first approach since its inception in 2010. It accumulated a wealth of drug discovery data and applied algorithms to fast-track its mRNA vaccine. However, this use of artificial intelligence for drug discovery was just a pilot. We will see more significant advances in 2021.
Hundreds of pharma and biotech startups have sprung up in recent years. These companies apply AI in drug discovery to find potential drug candidates for a variety of diseases. For example, Dyno Therapeutics is a Cambridge-based biotech startup. It focuses on gene therapy, an experimental technique that uses genes to treat or prevent diseases.
Dyno uses AI and high-throughput in vivo experimentation to accelerate tests on living organisms. It delivers DNA sequences to affected cells in a highly targeted manner to treat diseases.
Dyno recently announced a partnership with Roche Pharma and its subsidiary Spark Therapeutics Inc to focus on diseases of the liver and central nervous system. This is a win-win deal since it helps large pharma companies find potential drug candidates faster while giving the startups access to funds and crucial research data. Many such big-ticket partnerships are underway in the pharmaceutical industry.
Another critical breakthrough from late 2020 will turbocharge drug discovery. AlphaFold, an AI-driven system developed by DeepMind, cracked the 50-year old problem of protein folding. The shape of a protein dictates its function in the body. By finding a protein’s structure, scientists can synthesize protein-based drugs to treat diseases.
“Finding the 3D structure of proteins is time-consuming in drug discovery”, says Pushmeet Kohli, the principal and team lead at DeepMind. AlphaFold could make AI drug discovery more efficient by helping researchers predict the structure of proteins more accurately.
2. AI will transform telecommuting and unlock the future of work
We spent a sizable portion of our work time this year on Zoom, Microsoft Teams, or Google Meet. The battle for supremacy will continue amongst these top players into 2021. Startups that aren’t burdened by legacy product features will reinvent this space. For example, Vowel is a venture-funded video conferencing tool that lets you transcribe, search, and share your meetings.
However, the most significant transformation in 2021 will be the shift from virtual meetings to virtual workspaces. We will see companies replicate their physical presence in the digital world. This virtual replica of organizations will get richer and more detailed over time, thereby creating a digital twin of organizations. Employees will take on avatars in this virtual enterprise, as they work from home. They will not just meet online but also collaborate and socialize virtually.
Businesses will invest in technology to enable a seamless handover of work between digital and physical spaces. The confluence of mixed reality, 5G, and AI will power this trend. This year, Facebook’s Virtual Reality (VR) headset brand launched Oculus for Business, an enterprise platform to help companies deploy VR at work.
Soon, you will be able to virtually grasp and inspect a digital model of your product prototype, sitting in your living room. Your colleagues will be able to join and brainstorm with you virtually. In 2021, we will move towards a remote-first, hybrid workplace.
This will be seen first in a few industries and occupations. McKinsey predicts that the highest potential for remote work is in sectors such as finance and insurance, management, business services, and information technology.
3. AI will transform edge computing and make devices around us truly intelligent
We are seeing an explosion of smart devices and IoT (Internet of Things) sensors. Over 35 billion devices are expected to be in use worldwide in 2021. Most of these devices aren’t smart. They depend on a centralized server for their intelligence. Data continuously travels between the devices and the cloud, where all the computing happens. This introduces latency and makes the devices expensive.
Edge computing solves this problem by moving the processing to the device, closer to where data is generated. Forrester predicts that 2021 will be the year when edge computing will take off. What will drive this transformation? The availability of high-speed chips from companies like Intel and Nvidia, and the rollout of 5G. Forrester says that edge computing will eat into the public cloud’s growth by shaving five percentage points off cloud growth next year.
Today, most enterprise AI applications depend on the cloud, not just for training models but also for making run-time predictions. In 2021, model training and prediction will move to the edge. Advances in machine learning techniques, such as federated learning, will accelerate this trend. By distributing algorithm training across many decentralized devices, federated learning avoids the need for data to be collected or governed centrally.
The intelligent edge will lead to an explosion of AI usage in business applications such as factory floor automation, customer experience, surveillance, and predictive maintenance.
For example, AI at the edge will transform your retail experience at brick-and-mortar stores. Intelligent customer consoles will understand your preferences and recommend garments. It will let you ‘try-on’ garments on a smart mirror and show color and size options based on stock availability. Finally, it will offer you a personalized promotion for visiting the store.
2021: The year when artificial intelligence will go mainstream
Artificial intelligence has been around for close to 75 years but is yet to see mainstream adoption. Over this period, it has gone through a few cycles of excessive hype. Each of these phases was immediately followed by extended periods of disillusionment at enterprises. These were called the AI winters.
In the last decade, AI shot back into prominence and has seen remarkable advances in techniques such as deep learning. It is back in vogue. However, there are questions on whether it will go mainstream this time or go into hibernation yet again. What led to the earlier AI winters? Despite sizeable business investments and sky-high expectations from AI, it was never fully commercialized.
This time, things are different.
In recent years, we see a steady rise in the adoption of AI. McKinsey’s 2020 State of AI survey found that over 50% of companies have adopted AI in at least one business function. Many companies reported that AI was creating an impact by generating revenue and reducing costs for those functions.
The business value from AI will continue to increase in the coming years. The pandemic has created the right conditions for businesses to realize the importance of AI, prioritize efforts to move AI to production, and ensure organization-wide adoption. 2021 will be the year when artificial intelligence sees widespread use across industries.