
The IT industry is an important contributor to the burgeoning digital economy and feeds the domestic economy through two primary channels: the production of cutting-edge technologies and the distribution of scale of innovation across other economic sectors. The IT services sector distributes innovative technologies from consulting services to downstream business organizations seeking to improve efficiency, generating significant multiplier effects across the industry value chain. The IT industry is also impressively robust. It persevered through the U.S. economy’s slow recovery, growing from an annual value-add of $835 billion in 2008 to $1,480 billion in 2017—an increase of 77 percent. In 2017 alone, the IT industry’s contribution to real economic output exceeded that of the professional and business services, finance and insurance, and manufacturing sectors. Despite the changing cost structure of the technological distribution channel, growing IT spending should continue to have a net positive impact on the industry and on aggregate real economic output.
- The global information technology industry will grow at a rate of 3.7% to 2021
- India holds 65% of the outsourced IT jobs
- The explosion of Internet of Things (IoT) devices, combined with the increased portability of computing power and AI-driven tools, the time is right for edge computing to experience significant growth
- 45 percent of IoT-generated data will be stored, processed, analysed, and acted upon close to or at the edge of networks in the next 3 years
- IT spending on services, infrastructure, and software is on track to rise to $3.8 trillion, a 3.2 percent increase from $3.7 trillion in 2018.
- The IT services-producing sector, grew 20 percent from 2008-2017
Rapid change is happening across the IT channel today, affecting business models, the competitive landscape, customer types, buying patterns, M&A activity and more. Technology and the business of selling it has grown far more complex. Additionally, channel firms today are making larger investments in marketing as they become more services-oriented in nature and rely less on hitching their brand to that of the vendors they sell. This is new territory for many smaller firms, in particular, that have never had devoted marketing headcount. The allocation of spending will vary from country to country based on a number of factors. In the mature U.S. market, for example, there is robust infrastructure and platforms, a large installed base of users equipped with connected devices, and available bandwidth for these devices to communicate. This paves the way for investments in the software and services that sit on top of this foundation.
- IBM has committed $1 billion to training and development programs for its U.S-based employees over the next four years
- AI investments to boost by10% or more and 80 percent indicated that their AI investments had driven return on investments (ROI) of 10 percent or more
- Targeted ICT investments in 5G technologies and infrastructure along with R&D innovation combine to bolster the digital economy and accelerate the ICT-sector’s diffusion effect to less technologically-intensive sectors
- Policy-guided investments can augment the capital contributions that ICT sectors make toward GDP growth and will boost labour productivity as a result
- India’s spending on R&D tripled, whereas China’s spending increased more than tenfold
Artificial Intelligence, or AI, has already received a lot of buzz in recent years, but it continues to be a trend to watch because its effects on how we live, work and play are only in the early stages. AI refers to computer systems built to mimic human intelligence and perform tasks such as recognition of images, speech or patterns, and decision making. AI can do these tasks faster and more accurately than humans. Machine Learning is a subset of AI. With Machine Learning, computers are programmed to learn to do something they are not programmed to do: they learn by discovering patterns and insights from data. In general, there are two types of learning, supervised and unsupervised. The Machine Learning market is expected to grow to $8.81 billion by 2022. Machine Learning applications are used for data analytics, data mining and pattern recognition. Like AI and Machine Learning, Robotic Process Automation, or RPA, is another technology that is automating jobs. Less than 5 percent of occupations can be totally automated, but about 60 percent can be partially automated.
- Artificial intelligence (AI) and machine learning
- The Internet of Things (IoT)
- Wearables and augmented humans
- Big Data and augmented analytics
- Intelligent spaces and smart places
- Blockchains and distributed ledgers
- Cloud and edge computing
- Digitally extended realities
- Digital twins
- Natural language processing
- Voice interfaces and chatbots
- Computer vision and facial recognition
- Robots and Cobots
- Autonomous vehicles
- 5G
- Machine co-creativity and augmented design
- Digital platforms

International Conference on Computer Science
Date : 30 - 31 Jul 2020
Place : University of Quebec in Montreal, Montreal, Canada