Technology has the real potential to transform the business and thereby enhancing customer service. But for several reasons, its adoption into business practices has been gradual and took time in almost all the industries. Gartner, the global research and advisory firm has said that the adoption of Artificial Intelligence(AI) into business has risen from 4% to 14% between 2018 and 2019. Despite the increase in the AI adoption rate, Cognizant says that around 37% of the projects are in the pilot stage whereas only 22% is fully implemented. Some of the companies are unwilling to invest in AI and Machine Learning technologies due to the increased cost as well as they are unaware as to what benefits AI can bring into their business.
Depending on where the organization stands in its digital maturity curve, the benefits that AI provides to the business vary. AI can significantly increase the contact center through Machine Learning technology. Similarly, voice transcription which uses speech intelligence reduces the burden of manual search for articles to the agents. According to research conducted by Cognizant, around two-thirds of the executives believed that AI is extremely important to their company’s success in today’s world.
There has been fear in various industries as to whether the adoption of AI into the business will have an impact on the workforce. This fear increased further when chatbots replaced call center agents. But as the technology matures, there is evidence of a human-AI partnership approach to business. This partnership is called augmented intelligence where humans are mediating the decision making done through AI and Machine Learning. Gartner says that this augmented intelligence is expected to generate $2.9 trillion of global business value by the end of 2021.
AI, a high demand technology is expected to put a lot of pressure on the network for fast and secure connectivity. The massive volume of data from various data sources fed into AI requires superior connectivity. In the future, Artificial Intelligence, data analytics, and machine learning algorithms will definitely need guaranteed, and flexible bandwidth, especially as more complex computing process is done closer to the edge of the network.
