Predictions for the Future of Work in 2021

By Vijoy Pandey, Vice President, Engineering, Emerging Technologies and Incubations Group, Cisco

It is safe to say that none of us could have predicted the pandemic in 2020.  

The application-first digital economy and future of work that was slowly taking shape over the past few years, suddenly got a jolt of adrenaline. Before the pandemic hit us, it was expected that 50% of companies polled by the World Economic Forum expected that automation, AI, robotics and remote work capabilities would lead to some reduction in their current workforce and require significant re-skilling of their future workforce. 

COVID-19 has significantly accelerated and exacerbated this trend - forcing everything from digital computing, healthcare, collaboration ecosystems, large scale supply chain, the service economy, and even personal home and family life to reinvent themselves. The stay-at-home paradigm in almost all countries across the globe has shown us that about ~15% of jobs are likely to be automated, and an additional ~30% of jobs are likely partially automated. And these trends will only accelerate as the autonomous systems driving these environments get better and better. 

My predictions for 2020 focused on digital computing - including the application-first digital economy, AI and ML trends, quantum computing, hybrid and edge cloud and more. My predictions for 2021 and beyond will look at the bigger picture for the future of work, as so many of us are reimagining what that will be, and how some things have changed forever.

First Up: The Application-first digital economy 

The business agility and quality of experience provided by modern cloud native applications has led to the mantra that the application experience is the new brand. Increasingly more transactions are taking place through modern distributed cloud native applications spanning healthcare, education, entertainment, agriculture, supply chain and more. This trend was a spot-on prediction for 2020 and will exponentially grow in 2021 and beyond.  

Containerization was another key trend observed from 2012 through 2020, but we are rapidly moving up the abstraction stack. Serverless computing is gaining mindshare with developers, and is especially seeing a meteoric rise as the de-facto programming model in universities and colleges. This is only a hop-step away from the No-Code/Low-Code movement that still has some ways to go beyond simple workflow-based use cases. 

Meet the New Edge  

For the longest time, it felt like the edge was always waiting to happen. Last year I predicted an increased deployment of edge-specific applications such as gaming, connectivity access, and other latency sensitive use cases, which has all come true. Although, edge computing, so far, has been used primarily either in a hub-and-spoke architecture, with edge nodes tethered back to a mothership as in the case of offers from cloud providers, or in a completely autonomous manner with independent control.

Starting in 2021, we will see the beginnings of a true distributed edge computing paradigm, where hardware, caching and software architectures will be designed and delivered to operate in a headless highly distributed manner, free from the control planes sitting centrally in large cloud regions. A manufacturing enterprise, for example, would have all their edge nodes under this un-tethered distributed control, while keeping the latency, decision making, and governance aspects localized to the plant. Full production deployments of such paradigms are still a couple of years away. 

Future of Collaboration 

The way we work, collaborate, consume live entertainment and events, vote, access healthcare, and interact with friends and family are all going to drive a dramatic change in collaboration tools. 

During 2021, we will find ourselves solving these newer use cases by retrofitting our current tools in new, intriguing, and always sub-optimal ways.  

By late 2021 though, there will definitely be a small crop of startups and software vendors that will start taking a fresh look at the problem space, work at a higher layer than current tools, and start solving some of these use cases in evolutionary ways. As an example, being able to asynchronously have hallway discussions based on the "virtual" location of individuals (with folks all hanging out near the proverbial virtual watercooler or with people in the same conference room), or as another example, being able to merge disparate audio-video streams and collaborate on a movie set design, car interior and exterior design, or video game environment in an immersive manner. 

Seamless healthcare and supply chains 

Autonomous control loops, robotics and drone technologies, remote monitoring via new types of high bandwidth streaming sensors to monitor manufacturing floors, personal health state and healthcare environments, AI/ML assisted diagnosis systems, and most importantly, software applications and systems that provably track data and asset flow between teams and organizations will attract significant mindshare in 2021. 

-Smart wearables are already seeing quite a bit of traction, but the space is quite large when it comes to comprehensive Remote Patient Monitoring (RPM). While we will see an expansion in the types of sensors being deployed for RPM,  we will also see a rise in the delivery and integration of these sensors with backend healthcare systems in 2021 and beyond.  

-The disparate and disjointed manufacturing and supply chain control systems, built in a pre-cloud-native era are due for a massive disruption for zero-touch, agile, end to end automation. The learnings from cloud-scale data center supply chains will be applied to the myriad operational problems in manufacturing environments, solving the autonomous operations, agility and flexibility gaps that exist in these supply chains today. 

Significant research, startups and engineering funding will move towards solving these problems in narrow slices in 2021, with production deployments hitting in late 2021 and beyond, paving the way for end-to-end autonomous operations. 

AI/ML is still hip, but Quantum-X is getting hip-per 

Through 2019, there had been talks of a second AI winter, which happens when significant advances in the field slows down resulting in lowered research funding and reduced interest. A quick look at the features released from all major smartphone manufacturers this year, for example, clearly shows the pace in computational photography has dramatically slowed down in the past year, compared to the advances made in the years prior.  

As predicted last year, we are seeing more of a refocus of AI talent and technologies into different areas, particularly in the areas of ML-Ops and systems design. Starting 2021, we will begin to see the usage of AI/ML in production operational systems, though we will still be learning through niche use cases, limited to either narrow problem statements, single domains, or a single layer of the stack.   

But as I predicted last year, Quantum Computing is definitely starting to hit the hype cycle. There has been a massive influx in funding (or funding intent) in Quantum this past year (e.g, [1] [2] [3]) and a significant rise in marketing mindshare as well, since no one wants to lose out on being the first to talk about Quantum-X. The VC money still hasn't formed any unicorns in this space yet, but my bet would be on a few unicorns being easily formed in the next 5 years. 

To Conclude 

It would be an understatement to state that 2020 has been a rough year. But as with all rough years or decades, they also force humankind to reassess priorities, focus on the important, and accelerate innovation. The next decade will see unprecedented technology innovation and growth because of our rendezvous with this pandemic. 

##

About the Author

Vijoy Pandey is Vice President, Engineering for Emerging Technologies and Incubation (ET&I) at Cisco. ET&I is chartered to create and drive the next Bold Bets for Cisco in an agile, ambitious and entrepreneurial manner. Vijoy runs both engineering and a global framework of co-innovation labs for these ventures. He is also the CTO for Cloud at Cisco.

Vijoy has held various strategy and engineering leadership roles, and has over 20 years of expertise in planetscale distributed systems, cloud, operational excellence, and application-first software infrastructures which serve to complement his role as a technical visionary for a software-focused digital future. Before joining Cisco, he served as Head of Engineering at Google for the company’s global cloud networks, where he was responsible for developing software systems for intent-driven automation, ML/AI-based data analytics, and application-level awareness. Vijoy has held the CTO role at various companies including IBM Cloud, IBM Systems and Software Group, and Blade Network Technologies. He has also led large geo-diverse agile engineering teams at Blade Network Technologies, Nortel, Alteon and Google.

Vijoy has a Ph.D. in Computer Science from the University of California, Davis. He currently holds over 80 patents in cloud, networking and distributed systems.