Technology represents the practical application of scientific knowledge, playing a key role in catapulting the world from the industrial to the information age. Today, technology is ingrained in every aspect of human life, and more so for organizations, affecting how they operate and engage with their customers. Cost projections indicate that worldwide expenditure on information technology (IT) systems will exceed $5.6 trillion in 2025. 

What are the parameters and costs behind this growth? Many factors are in play, and we are looking at the most defining moments of Tech growth in the last five years.

2020-2024: A period of accelerated transformation

Technology growth from 2020 to 2024 can be attributed to the proliferation of personal computing and smartphones, the widespread adoption of the internet, advancements in software development, and the ever-present need to address cybersecurity concerns. 

Tech growth Tech growth 

Here’s all the tech growth that happened in this short period. 

The COVID-19 pandemic accelerated digital transformation 

The global pandemic compressed into a short span of a couple of months the digital transformation that would have taken years. Remote work, online shopping, telehealth, and virtual classes became the new norm. It showcased the great human ability to adapt to the situation. 

AI has become a mainstay

Once the post-pandemic status quo was restored, large language models (LLMs) emerged as another dominant force. Artificial intelligence (AI) moved from an experimental entity to a business strategy where leaders pored over possible use cases that this technology could solve. 

Quantum computing has made data analysis easier than before 

The continued advancement of quantum computing has helped tackle complex problems beyond the reach of classical computers. Notable progress was made in quantum error correction and control, bringing the realization of fault-tolerant quantum computers closer to reality.

Edge computing gained traction 

Simultaneously, the computing infrastructure was getting advanced. Edge computing became a crucial paradigm for enabling real-time data processing by bringing computational resources closer to the data source. The market for edge computing experienced substantial growth, reflecting the increasing demand for low-latency, real-time data analysis across industries. 

Blockchain technology continued with its evolution 

Blockchain technology expanded its applications beyond cryptocurrencies. For example, it was used in healthcare to manage electronic health records and for secure and transparent transactions by the financial industry.

Sustainability became a key focus area 

Sustainability emerged as a critical driver of technological focus and advancement during the early 2020s. A growing emphasis on environmental, social, and governance (ESG) priorities led to a surge in demand for technology-enabled solutions to promote sustainability.    

Impact on customer service

Here’s the impact that the tech growth had on customer service. 

AI and ML are becoming integral 

AI and machine learning (ML) emerged as pivotal tools for enhancing both the efficiency and personalization of customer interactions. Their ability to analyze vast quantities of customer data to discern patterns and insights allowed businesses to anticipate customer behavior and preferences better. While these technologies enabled seamless customer experiences (CX), the arrival of generative AI made customer interactions more human-like and contextually relevant  – a significant leap from script-based chatbots. 

The COVID-19 pandemic accelerated the shift to digital channels 

With the increased adoption of digital channels, the COVID-19 pandemic amplified the demand for fast and personalized support. As younger generations matured during this period, their preferred channels for communication also became integral for businesses planning CX strategies. 

Cybersecurity, a differentiator in building trust 

In parallel, organizations placed a strategic emphasis on cybersecurity as a critical differentiator in building customer trust and reliability. The frequency and sophistication of cyberattacks increased exponentially during this period, bringing customer data security to prominence. Cybersecurity evolved from being solely an IT concern to a key element of brand reputation and customer loyalty.   

Our take: Companies continued to innovate to stay ahead of the curve 

The continuous advancement of technology, fueled by AI, prompted organizations to focus on innovation to gain a competitive advantage. Large language models, AI agents, and hyper-personalization became significant business areas. Innovation became necessary to meet evolving customer expectations and behavior; the fallout — brand risk oblivion. 

2025 and beyond

Organizations that proactively embrace technology advancements and develop strategies around the new AI, ML, and other innovations will be better positioned to unlock new growth opportunities.  

Agentic AI is set to play a key role in streamlining operations

Presently, generative AI (GenAI) has become a key driver of growth. Companies are now thinking of orchestrating autonomous systems capable of making decisions independently with the help of agentic AI, which can take actions without constant oversight and pre-defined workflows. 

Rise of RISC architecture

In the domain of computing architecture, the rise of RISC (Reduced Instruction Set Computing) architecture is expected to continue. RISC architecture prioritizes the execution of simple instructions at high speeds. It’s becoming customizable, scalable, and cost-effective. 

Extended reality (XR) is playing a key role in training  

Extended reality (XR), which encompasses virtual reality (VR), augmented reality (AR), and mixed reality (MR), is going to have a great impact on training methodologies. It will weave more immersive and interactive learning experiences, bridging the gap between digital and physical worlds. It will also offer safe and risk-free environments for skills development across various industries, including corporate training, healthcare, and warehousing.   

LLMs paving the road for micro-LLMs

Small language models have become highly popular as they focus on efficiency and domain expertise. Micro LLMs require less computational power and memory compared to their larger counterparts. Their ability to be fine-tuned quickly offers businesses greater flexibility and efficiency in addressing unique needs.  

Hybrid systems combining the strengths of on-premise and cloud infrastructure 

Hybrid systems offer great flexibility in managing and deploying applications. Hybrid computing models allow for adaptive data processing, where real-time operations can be handled at the edge for low latency. At the same time, computationally intensive analytics and large-scale storage are managed in the cloud. 

The emergence of spatial computing 

Unlike traditional computing that relies on screens, spatial computing enables machines to understand human environments and user intent through spatial awareness. It integrates AI, computer vision, and sensor technologies to create more fluid and intuitive interfaces between the physical and digital worlds. The AI integration is expected to further enhance spatial computing by improving its functionality, interactivity, and scalability. 

Conclusion 

The technological landscape is in a state of perpetual flux. The mammoth growth experience during the pandemic set a benchmark, allowing organizations to move from increased adoption of digital channels to autonomous systems, all in a span of five years. 

The future is in agility, backed by a holistic and adaptive approach to technology adoption. Organizations need to continue focusing on the potential benefits, ethical implications, and security requirements, especially in areas like customer interactions.

Connect with our experts to know more.