Artificial Intelligence: Complicated answers to simple questions
Artificial Intelligence (AI) is becoming increasingly important as our world relies excessively on technology. AI has begun to play a more prominent role in our lives and societies. However, we are still unclear about its capabilities and limitations. As AI gets better at completing tasks that humans are traditionally responsible for, I want to offer my understanding of AI and record some practical implications in business with this post.
What is AI?
Artificial Intelligence (AI) is “the theory and development of computer systems able to perform tasks normally requiring human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages” (Artificial Intelligence, Oxford Dictionary, 2022). Similarly, AI is defined as a “branch of computer science dealing with the simulation of intelligent behavior” as well as “the capability of a machine to imitate intelligent human behavior” (Artificial Intelligence, Merriam-Webster, 2022). Both dictionaries and many other available definitions of AI give human ownership to the word “intelligence.” Despite the two definitions’ circular nature, mentioning the word ‘intelligence’ twice, they both point out that humans and machines are equally capable of cognitive processes.
The term AI refers to machines acting in ways that seem intelligent (Malone, 2018) and performing cognitive functions we still believe only human brains could do. The head of AI at the Chinese social media firm Baidu, and well-known for AI inventions, Andrew Ng, offers a less formal definition of AI. Ng argues that AI machines can replace any cognitive process humans need less than one second to process. Marvin Minsky, one of the fathers in the field, uses the term “suitcase” to define AI as a simple concept that contains multiple terms, ideas, and concepts. I would dare to define AI as a form of computer science that enables computers to learn and perform tasks that would otherwise be difficult or impossible for them to do.
What can you do with AI?
In the business world, AI is nothing new. It has been used to help businesses automate tasks, improve customer service, and make better decisions. AI improves daily life by automating streamlined tasks and advancing human knowledge. We find examples of AI systems in home appliances such as Amazon’s Alexa and Google Home, virtual phone assistants Siri, Cortana, or Google’s Assistant, smart compositions in Gmail, customer service chatbots, predictive searches in Google, workout suggestions based on our wearable devices, and sales recommendations in Booking or Amazon.
AI already impacts the way we do business and make decisions. New markets, business models, and jobs are created due to AI disruption, applying augmented and virtual reality, wearables, robotic process automation, and biometrics. AI evangelists claim that the early adopters of AI will disproportionately gain share over those companies that will hesitate or resist change. AI posits both a “huge opportunity and an ominous threat wrapped up in a bewildering bundle of algorithms and jargon” (Burges, 2018, p.1).
Some ways AI is already being used in business include:
- Automating customer service: Chatbots are a type of AI that can automate customer service (Daniel et al., 2019; Luo et al., 2019). They can answer questions, provide recommendations, and make bookings.
- Tracking and predicting patterns: AI can track the spread of diseases by monitoring factors such as travel patterns and social media posts (Balwani et al., 2019). AI can also predict how people buy things or move in physical environments (shopping malls, parks, etc.) (Leung, Paolacci, and Puntoni, 2018).
- Helping with decision-making: AI can help businesses make better decisions by providing recommendations based on data (Bennett & Hauser, 2013). For example, companies like Amazon and Netflix use AI to recommend products and movies to customers based on their purchase history and viewing preferences.
What else should we know about AI?
Today, AI systems are being implemented in organizations to offer a new business reality, which involves image and speech recognition, big data, clustering information, Natural Language Processing (NLP), optimization of business solutions, and prediction of risks and benefits. The need for market expansion and customer experience personalization has led managers to seek innovative ways to introduce and integrate digital technologies into their business models through big data, image processing, and customer service.
- The use of big data consumer analytics transforms the business on its infrastructure, human capital, and organizational structure (Erevelles et al., 2016).
- AI is in its infant stage of recognizing images and turning them into words and then aiming to give meaning to those words.
- AI-powered service agents offer real-time available customer service to initiate discussions and build customer relationships (Mimoun et al., 2017). Godey et al. (2016) argue that as machines learn from interactions with humans, AI applications improve accuracy and increase performance. Brands in the fashion industry such as Burberry, Tommy Hilfiger, H&M, and Louis Vuitton have adopted automated service agents as part of their AI-powered marketing communication strategies.
There is a wide range of applications of AI in business, ranging from fraud detection, research insights, crisis response, inventory optimization, and talent acquisition to medical diagnosis, customer service chatbots, digital assistants on smart devices, learning tutors, and e-commerce recommendations (Martin, 2018). AI is being utilized to help enterprises source materials and goods from vendors, as well as integrate vast amounts of data for strategic decision-making. Because AI technology can analyze data at a fast speed, it plays a vital role in speeding up the costly trial-and-error process of product development — an essential step toward efficiency. Also, healthcare consultants believe that the most significant impact will be in data analysis, imaging, and diagnosis. They feel that AI has the potential to search and filter medical knowledge about a disease for humans to make the final decision for treatment.
Is everybody excited about AI?
Not all researchers share the same excitement about AI. Many believe that the actual integration of AI in business is a slow process, not worth the buzz and the investment at the present state. AI researchers are concerned about adopting AI from businesses that do not rely on digital services, such as hotels, restaurants, and education. An actual worry about AI is to what extent organizations can leave a machine to decide on strategic goals when AI lacks empathy, intuition, and real-life experience. Past examples in business have shown that decisions that have been based solely on intelligence and facts did not work well with humans.
Scholars argue that AI is the next wave of digital disruption. However, many business leaders seem unsure of what to expect from AI and how it fits into their business model. On the one hand, technology leaders examine methods to use AI to improve customer service quality, responsiveness, and business effectiveness. On the other hand, scholars highlight doubts about AI’s disruption in business. The 2017 MIT Sloan Management Review and Boston Consulting Group global survey highlights that almost 85% of more than 3,000 executives, managers, and analysts across business sectors see positive outcomes from AI’s disruption (Ransbotham, 2017). Nevertheless, less than 39% of all companies participating in the global survey follow an AI strategy. Only half of the largest companies (>100,000 employees) admitted that they would consider AI in the future.
What’s next?
As we try to understand AI, it is essential to remember that AI is still in its early stages. There is a lot of research being done in the area. However, there is still a long way to go before saying that AI truly understands people as much as people understand AI. The rapid proliferation of technology has set the ground for integrating AI into our lives. Broadband internet connections, powerful computer processing, cloud storing, smart devices penetration, and ubiquitous mobility shape today’s business technological landscape. AI will fundamentally impact our lives only when we develop empathetic applications that understand and react to people’s emotions and needs.
References
Artificial intelligence, n. (2022). Oxford English Dictionary; Oxford University Press. https://www.oed.com/view/Entry/271625?redirectedFrom=artificial+intelligence#eid
Balwani, N., Dash, A., Das, A., Das, L., Misra, S., & Ghose, S. (2019). Robo-Advisory: An Investor’s Perception. International Journal of Psychosocial Rehabilitation, 23(3), 874–884. https://doi.org/10.37200/ijpr/v23i3/pr190376
Bennett, C. C., & Hauser, K. (2013). Artificial intelligence framework for simulating clinical decision-making: A Markov decision process approach. Artificial Intelligence in Medicine, 57(1), 9–19. https://doi.org/10.1016/j.artmed.2012.12.003
Daniel, G., Cabot, J., Deruelle, L., & Derras, M. (2019). Multi-platform Chatbot Modeling and Deployment with the Jarvis Framework. Advanced Information Systems Engineering, 177–193. https://doi.org/10.1007/978-3-030-21290-2_12
Definition of ARTIFICIAL INTELLIGENCE. (2022). Merriam-Webster.Com. https://www.merriam-webster.com/dictionary/artificial%20intelligence
Erevelles, S., Fukawa, N., & Swayne, L. (2016). Big Data consumer analytics and the transformation of marketing. Journal of Business Research, 69(2), 897–904. https://doi.org/10.1016/j.jbusres.2015.07.001
Godey, B., Manthiou, A., Pederzoli, D., Rokka, J., Aiello, G., Donvito, R., & Singh, R. (2016). Social media marketing efforts of luxury brands: Influence on brand equity and consumer behavior. Journal of Business Research, 69(12), 5833–5841. https://doi.org/10.1016/j.jbusres.2016.04.181
Leung, E., Paolacci, G., & Puntoni, S. (2018). Man Versus Machine: Resisting Automation in Identity-Based Consumer Behavior. Journal of Marketing Research, 55(6), 818–831. https://doi.org/10.1177/0022243718818423
Luo, X., Tong, S., Fang, Z., & Qu, Z. (2019). Frontiers: Machines vs. Humans: The Impact of Artificial Intelligence Chatbot Disclosure on Customer Purchases. Marketing Science, 38(6). https://doi.org/10.1287/mksc.2019.1192
Malone, T. W. (2018). Superminds: The surprising power of people and computers thinking together. Little, Brown And Company.
Martin, N. (2018, November 11). How AI Is Revolutionizing Digital Marketing. Forbes. https://www.forbes.com/sites/nicolemartin1/2018/11/12/how-ai-is-revolutionizing-digital-marketing/#48272c331f62
Mimoun, M. S. B., Poncin, I., & Garnier, I., M. (2017). Virtual Sales Agents: The Reasons of Failure. In C. L. Campbell (Ed.), The Customer is NOT Always Right: Marketing Orientations in a Dynamic Business World. Developments in Marketing Science: Proceedings of the Academy of Marketing Science. Springer, Cham.
Ransbotham, S. (2017, September 6). Reshaping Business With Artificial Intelligence. MIT Sloan Management Review. https://sloanreview.mit.edu/projects/reshaping-business-with-artificial-intelligence
