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Here’s what a tech-enabled world will look like for future pandemic phases

15 minutes read

The COVID-19 pandemic or what may be more suitably described as a black swan event that disrupted the general mechanism of daily life and businesses globally has also led to life in the new normal. This paradigm shift relies on automated services, contactless payments, digital healthcare including the rise of mental health apps, Artificial Intelligence and Augmented Reality-led innovations, e-customer support, video conferencing for remote work possibilities, amongst others. 

The World Robotics 2020 Industrial Robots report, published in September 2020, shows a record of 2.7 million industrial robots operating in factories around the world – an increase of 12%. Sales of new robots remain on a high level with 373,000 units shipped globally in 2019. This is 12% less compared to 2018, but still, the 3rd highest sales volume ever recorded.

Researchers from the University of Palermo programmed SoftBank’s Pepper robot to voice its “thinking process” while carrying out a series of tasks, including running restaurant operations, thus giving it a human touch with a scope of emotional intelligence. 

“If you were able to hear what the robots are thinking, then the robot might be more trustworthy,” co-author Antonio Chella explained in a press release, describing first author Arianna Pipitone’s idea that launched the study at the University of Palermo.

“The robots will be easier to understand for laypeople, and you don’t need to be a technician or engineer. In a sense, we can communicate and collaborate with the robot better,” Chella continued.

Amid the pandemic, a NASSCOM report suggests that the technology industry has grown by 2.3 percent despite COVID-19, and India has emerged as the third-largest tech startup globally. 

In their Strategic Review 2021 report titled ‘New World: The Future is Virtual’, NASSCOM said that India’s technology industry contributes around 8 percent relative share to the national GDP, with 52 percent relative share in services exports, and 50 percent share in total FDI (based on FDI inflows from April to September 2020), as reported by YourStory. 

“The technology industry has weathered past crises and found novel ways to emerge stronger each time. In fact, tech companies have led the way on a variety of strategies other industries are now using to cope in this crisis — from remote working to a globally dispersed supply chain to managing through disruption. This crisis might well spark further creativity and innovation,” says PwC in a report titled ‘COVID-19 and the technology industry.’ 

What may be termed as a seismic shift in consumer behavior, owing to the long spate of lockdown and people increasingly staying home over the last many months, here are some of the noteworthy changes we’ve noticed thus far: 

Eating out, ordering in, and the behavioral shift

The pandemic amounted to huge losses to the hospitality and service industry globally when lockdowns were imposed. While most countries began easing restrictions as the first coronavirus wave plateaued, there were also plenty of innovations that came to light during this time. From quirky social distancing measures such as noodle hats that ensured 3ft distance from the next customer at a cafe in Europe to mannequins filling empty tables so diners wouldn’t feel alone and robots managing restaurant operations in Japan, the year 2020 has also given rise to the best alternatives as most people stay home. 

Additionally, the year was also one with a surge in food deliveries, while restaurants and QSRs ensured that customers regained trust in the hygiene and packaging techniques followed by them amid this time. With introductions like voice-based instructions within food delivery apps, no-contact deliveries, and special instructions possible, food and essential delivery services have seen a significant upward trend. 

“Health and social schedules are only two of the most common worries that consumers express about the ongoing crisis. There are still many more who worry about the overall economy and their personal finances, however, and others who feel no fear at all,” reads this report by pymnts.com released in early May 2021. 

Virtual Shopping meets Augmented Reality Experiences

Luxury fashion brand Gucci is expanding its presence on Roblox, a metaverse and gaming platform immensely popular with pre-teens, with a virtual two-week art installation. Visitors here can enter through a lobby in which their virtual avatars can view, try on and purchase digital Gucci items.

Image Courtesy: blog.roblox.com 

ALSO READ: Augmented Reality: A solution to the timeless insurance concerns

“Of course, it’s no surprise that luxury fashion brands want to position themselves at the center of an industry that made $175 billion in 2020, one with an increasing number of women. A 2020 report from the Entertainment Software Association found that women account for 41 percent of all gamers in the United States. Esports are also infiltrating popular culture, with an audience that’s predicted to reach 729 million in 2021, according to research from Newzoo,” reads an article by The Wired titled Luxury Fashion Brands Turn to Gaming to Attract New Buyers

In the year 2020, Ralph Lauren collaborated with Snapchat, thus revealing a quirky side to the luxury fashion house by letting younger customers try on the brand’s wear in various avatars. 

On the social media front, Snap announced the latest (fourth) generation of its Spectacles, a ‘60s-style design in black. These AR-capable Spectacles arrive shortly ahead of Facebook’s upcoming smart glasses, which will be a collaborative effort between the social media giant and Ray-Ban. These glasses are said to rely heavily on other forms of input as they won’t be released with built-in displays. Apple, too, is rumored to be working on augmented reality glasses, says a report by TechCrunch.

The German decor lighting app, Luminaire, which lets you try out light fixtures at a space of your choice, uses AR to bring a store-like experience closer to home. Its functioning is nearly akin to IKEA’s app that too, via AR, allows consumers to try out furniture before placing an order for the physical addition to their homes or offices. Fashion giants Burberry and Dior experimented with similar technologies for the handbags and sunglasses collections, respectively. Lipstick sales that saw a dip last year because of mask fashion taking over are back with a bang (almost) but multi-brand store Sephora had introduced their AR innovation which allowed consumers to try on lipsticks on their face (instead of the age-old try-on method). 

Instagram, previously only a photo-sharing app is now a revolutionary space for brands to connect with their consumers. The best part could probably be the addition of the shopping tag within the app so you can buy what you like almost instantly instead of waiting for it to hit the stores or looking for the same product on an e-commerce site. 

Remote Work, The Rise of Ed-Tech and more

Video conferencing is now an integral part of every professional’s life at work, even with family members or pets accidentally popping into your screens. What had begun with a month of proposed work from home has gone on for over a year and so, is a defining moment of the new normal. 

Zoom, Google Meet, Windows Meeting Room, are some of the most widely used apps for work calls, webinars, online sessions, and have also helped bridge the gap between teachers and their students in the recently-concluded academic year. Ed-Tech, hence, is being touted to be one of the fastest growing industries aided by the pandemic-led lockdowns. 

“Although EdTech is an emerging market that was steadily gaining pace, COVID-19 gave it the extra momentum, making way for the sector’s massive expansion. India’s EdTech market is all set to increase by 3.7 times in the upcoming five years, growing from US$ 2.8 billion (in 2020) to US$ 10.4 billion by 2025),” said UpGrad on their official blog. 

In this year’s edition of Google I/O, we also met the proposed 3D conferencing service titled Project Starlight, which will let you ‘see’ the person on the other side of the screen just like they were sitting across from you in person. 

E-consultation

The COVID-19 pandemic and the subsequent lockdown was also a year of spiked cases of anxiety, depression, and other mental health-related issues. For any physical ailments (non-COVID-related primarily), apps came to the rescue for online consultations and diagnosis. 

AI facilitated the rise and growth of emotionally intelligent apps such as Wysa or meditation-led apps such as Headspace and Calm. 

Take a look at a short conversation I had with Wysa to help me understand how she could walk with me through a stressful day. There are options to listen to music that helps relieve stress and in more stressful situations, seek professional help through the app. 

Contactless payments, Banking services, and more
Even though net banking and mobile banking were already on the rise pre-pandemic, the years 2020 and 2021 have shown a significant change in the way a customer banks and uses other financial services. Seeing this shift, banks including the State Bank of India changed their strategy and also introduced ‘at home’ banking that even allows one to open bank accounts at the comfort of their homes instead of the usual rule of visiting the home branch to do the needful. 

AI-led bots also work closely with customer support teams, helping with the first-level customer service and if the need arises, then speak to a human being on the other end of the line. This innovation has been significant in truncated any need for IVR systems, previously employed at contact centers. But that’s not all, you can also use AI to help with queries around insurance, whether you need insurance and which one to get that’s best suited to your needs. 

What’s next? 

There’s a high probability of XR and MR-led innovations taking over the market and further altering consumer behavior in terms of their food, recreation, fitness, shopping habits. Imagine a world of drone-led food deliveries and more sympathetic aka emotionally intelligent artificial intelligence that guides you to the right choice. 

Take a look at how the now delayed Tokyo 2020 Olympics were all-set to work closely with robots of different kinds during the games:

Life in the new normal has pushed most industries to innovate beyond their best-known practices were pre-pandemic. Even with a trial and error that may look like growth and substantial change is slow, there’s been a significant behavioral change which gives impetus to a renewed way of approaching business strategies and more. 

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AI Code Assistants: Revolution Unveiled

AI code assistants are revolutionizing software development, with Gartner predicting that 75% of enterprise software engineers will use these tools by 2028, up from less than 10% in early 2023. This rapid adoption reflects the potential of AI to enhance coding efficiency and productivity, but also raises important questions about the maturity, benefits, and challenges of these emerging technologies.

Code Assistance Evolution

The evolution of code assistance has been rapid and transformative, progressing from simple autocomplete features to sophisticated AI-powered tools. GitHub Copilot, launched in 2021, marked a significant milestone by leveraging OpenAI’s Codex to generate entire code snippets 1. Amazon Q, introduced in 2023, further advanced the field with its deep integration into AWS services and impressive code acceptance rates of up to 50%. GPT (Generative Pre-trained Transformer) models have been instrumental in this evolution, with GPT-3 and its successors enabling more context-aware and nuanced code suggestions.

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  • Adoption rates: By 2023, over 40% of developers reported using AI code assistants.
  • Productivity gains: Tools like Amazon Q have demonstrated up to 80% acceleration in coding tasks.
  • Language support: Modern AI assistants support dozens of programming languages, with GitHub Copilot covering over 20 languages and frameworks.
  • Error reduction: AI-powered code assistants have shown potential to reduce bugs by up to 30% in some studies.

These advancements have not only increased coding efficiency but also democratized software development, making it more accessible to novice programmers and non-professionals alike.

Current Adoption and Maturity: Metrics Defining the Landscape

The landscape of AI code assistants is rapidly evolving, with adoption rates and performance metrics showcasing their growing maturity. Here’s a tabular comparison of some popular AI coding tools, including Amazon Q:

Amazon Q stands out with its specialized capabilities for software developers and deep integration with AWS services. It offers a range of features designed to streamline development processes:

  • Highest reported code acceptance rates: Up to 50% for multi-line code suggestions
  • Built-in security: Secure and private by design, with robust data security measures
  • Extensive connectivity: Over 50 built-in, managed, and secure data connectors
  • Task automation: Amazon Q Apps allow users to create generative AI-powered apps for streamlining tasks

The tool’s impact is evident in its adoption and performance metrics. For instance, Amazon Q has helped save over 450,000 hours from manual technical investigations. Its integration with CloudWatch provides valuable insights into developer usage patterns and areas for improvement.

As these AI assistants continue to mature, they are increasingly becoming integral to modern software development workflows. However, it’s important to note that while these tools offer significant benefits, they should be used judiciously, with developers maintaining a critical eye on the generated code and understanding its implications for overall project architecture and security.

AI-Powered Collaborative Coding: Enhancing Team Productivity

AI code assistants are revolutionizing collaborative coding practices, offering real-time suggestions, conflict resolution, and personalized assistance to development teams. These tools integrate seamlessly with popular IDEs and version control systems, facilitating smoother teamwork and code quality improvements.

Key features of AI-enhanced collaborative coding:

  • Real-time code suggestions and auto-completion across team members
  • Automated conflict detection and resolution in merge requests
  • Personalized coding assistance based on individual developer styles
  • AI-driven code reviews and quality checks

Benefits for development teams:

  • Increased productivity: Teams report up to 30-50% faster code completion
  • Improved code consistency: AI ensures adherence to team coding standards
  • Reduced onboarding time: New team members can quickly adapt to project codebases
  • Enhanced knowledge sharing: AI suggestions expose developers to diverse coding patterns

While AI code assistants offer significant advantages, it’s crucial to maintain a balance between AI assistance and human expertise. Teams should establish guidelines for AI tool usage to ensure code quality, security, and maintainability.

Emerging trends in AI-powered collaborative coding:

  • Integration of natural language processing for code explanations and documentation
  • Advanced code refactoring suggestions based on team-wide code patterns
  • AI-assisted pair programming and mob programming sessions
  • Predictive analytics for project timelines and resource allocation

As AI continues to evolve, collaborative coding tools are expected to become more sophisticated, further streamlining team workflows and fostering innovation in software development practices.

Benefits and Risks Analyzed

AI code assistants offer significant benefits but also present notable challenges. Here’s an overview of the advantages driving adoption and the critical downsides:

Core Advantages Driving Adoption:

  1. Enhanced Productivity: AI coding tools can boost developer productivity by 30-50%1. Google AI researchers estimate that these tools could save developers up to 30% of their coding time.
IndustryPotential Annual Value
Banking$200 billion – $340 billion
Retail and CPG$400 billion – $660 billion
  1. Economic Impact: Generative AI, including code assistants, could potentially add $2.6 trillion to $4.4 trillion annually to the global economy across various use cases. In the software engineering sector alone, this technology could deliver substantial value.
  1. Democratization of Software Development: AI assistants enable individuals with less coding experience to build complex applications, potentially broadening the talent pool and fostering innovation.
  2. Instant Coding Support: AI provides real-time suggestions and generates code snippets, aiding developers in their coding journey.

Critical Downsides and Risks:

  1. Cognitive and Skill-Related Concerns:
    • Over-reliance on AI tools may lead to skill atrophy, especially for junior developers.
    • There’s a risk of developers losing the ability to write or deeply understand code independently.
  2. Technical and Ethical Limitations:
    • Quality of Results: AI-generated code may contain hidden issues, leading to bugs or security vulnerabilities.
    • Security Risks: AI tools might introduce insecure libraries or out-of-date dependencies.
    • Ethical Concerns: AI algorithms lack accountability for errors and may reinforce harmful stereotypes or promote misinformation.
  3. Copyright and Licensing Issues:
    • AI tools heavily rely on open-source code, which may lead to unintentional use of copyrighted material or introduction of insecure libraries.
  4. Limited Contextual Understanding:
    • AI-generated code may not always integrate seamlessly with the broader project context, potentially leading to fragmented code.
  5. Bias in Training Data:
    • AI outputs can reflect biases present in their training data, potentially leading to non-inclusive code practices.

While AI code assistants offer significant productivity gains and economic benefits, they also present challenges that need careful consideration. Developers and organizations must balance the advantages with the potential risks, ensuring responsible use of these powerful tools.

Future of Code Automation

The future of AI code assistants is poised for significant growth and evolution, with technological advancements and changing developer attitudes shaping their trajectory towards potential ubiquity or obsolescence.

Technological Advancements on the Horizon:

  1. Enhanced Contextual Understanding: Future AI assistants are expected to gain deeper comprehension of project structures, coding patterns, and business logic. This will enable more accurate and context-aware code suggestions, reducing the need for extensive human review.
  2. Multi-Modal AI: Integration of natural language processing, computer vision, and code analysis will allow AI assistants to understand and generate code based on diverse inputs, including voice commands, sketches, and high-level descriptions.
  3. Autonomous Code Generation: By 2027, we may see AI agents capable of handling entire segments of a project with minimal oversight, potentially scaffolding entire applications from natural language descriptions.
  4. Self-Improving AI: Machine learning models that continuously learn from developer interactions and feedback will lead to increasingly accurate and personalized code suggestions over time.

Adoption Barriers and Enablers:

Barriers:

  1. Data Privacy Concerns: Organizations remain cautious about sharing proprietary code with cloud-based AI services.
  2. Integration Challenges: Seamless integration with existing development workflows and tools is crucial for widespread adoption.
  3. Skill Erosion Fears: Concerns about over-reliance on AI leading to a decline in fundamental coding skills among developers.

Enablers:

  1. Open-Source Models: The development of powerful open-source AI models may address privacy concerns and increase accessibility.
  2. IDE Integration: Deeper integration with popular integrated development environments will streamline adoption.
  3. Demonstrable ROI: Clear evidence of productivity gains and cost savings will drive enterprise adoption.
  1. AI-Driven Architecture Design: AI assistants may evolve to suggest optimal system architectures based on project requirements and best practices.
  2. Automated Code Refactoring: AI tools will increasingly offer intelligent refactoring suggestions to improve code quality and maintainability.
  3. Predictive Bug Detection: Advanced AI models will predict potential bugs and security vulnerabilities before they manifest in production environments.
  4. Cross-Language Translation: AI assistants will facilitate seamless translation between programming languages, enabling easier migration and interoperability.
  5. AI-Human Pair Programming: More sophisticated AI agents may act as virtual pair programming partners, offering real-time guidance and code reviews.
  6. Ethical AI Coding: Future AI assistants will incorporate ethical considerations, suggesting inclusive and bias-free code practices.

As these trends unfold, the role of human developers is likely to shift towards higher-level problem-solving, creative design, and AI oversight. By 2025, it’s projected that over 70% of professional software developers will regularly collaborate with AI agents in their coding workflows1. However, the path to ubiquity will depend on addressing key challenges such as reliability, security, and maintaining a balance between AI assistance and human expertise.

The future outlook for AI code assistants is one of transformative potential, with the technology poised to become an integral part of the software development landscape. As these tools continue to evolve, they will likely reshape team structures, development methodologies, and the very nature of coding itself.

Conclusion: A Tool, Not a Panacea

AI code assistants have irrevocably altered software development, delivering measurable productivity gains but introducing new technical and societal challenges. Current metrics suggest they are transitioning from novel aids to essential utilities—63% of enterprises now mandate their use. However, their ascendancy as the de facto standard hinges on addressing security flaws, mitigating cognitive erosion, and fostering equitable upskilling. For organizations, the optimal path lies in balanced integration: harnessing AI’s speed while preserving human ingenuity. As generative models evolve, developers who master this symbiosis will define the next epoch of software engineering.

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